Building an ecosystem for better monitoring and communicating of medication safety in pregnancy and breastfeeding: validated and regulatory endorsed workflows for fast, optimised evidence generation

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Leistungen

Report on algorithms to define maternal, perinatal and childhood outcomes

"Task 1.3: Develop definitions and validate proposed algorithms to identify outcomes of interest, exposure and confounders and produce background and disease-specific prevalence rates (M12-M60) (SGUL, Lilly with collaboration from all relevant WP 1 partners and third parties and WP7).This task will focus on the outcomes as agreed during Task 1.2 (see table task 1.3 Part B).An Outcomes Validation Task Force across WP1, WP2 and WP7 will ensure compatibility and collaboration across WP. The validation studies will consider the issues pertinent to each outcome (by literature review, Brighton Collaboration definitions, CROWNE standards, expert consultation, data linkage and analysis), to arrive at proposed algorithms for implementation and quantification in WP7 and to be used in the demonstration projects. Examples of issues to address:•Non-livebirth outcomes: variation in stillbirth definition between countries, differences in recording neonatal deaths at the limits of viability and terminations of pregnancy. Consultation of EUROPERISTAT;•Congenital anomalies: ascertainment of late diagnosed congenital anomalies and terminations of pregnancy for foetal anomaly, exclusion of minor anomalies, verification of diagnosis in non-registry sources where possible by linkage with registries. Consultation of EUROCAT/EUROmediCAT;•Livebirth outcomes: whether to use country-specific in utero growth charts; testing of neonatal morbidity indicators if relevant. Consultation of EUROPERISTAT;•Long term neurodevelopmental outcomes: which data sources (e.g. referrals to specialists, health visitor records, academic examination results, childhood prescriptions, specialist registries) are most suitable for different dimensions of neurodevelopment (e.g. intellectual ability, language skills, memory functioning, autism spectrum disorder, learnt skills such as academic abilities) and the optimum age at assessment within each data source, testing which variables and combinations of variables can be used to increase sensitivity and specificity with and without a ""gold standard"" source, and using valproate exposure for validation to develop its use as a positive control for the demonstration projects; •Other childhood outcomes: depending on the results of Task 1.2, but likely to include issues such as use of childhood prescription data as surrogate, accuracy of diagnosis in healthcare databases versus specialised registries;•Maternal (pregnancy) outcomes: depending on the results of Task 1.2. with a special focus on sources of diagnostic variation.The proposed component algorithms will define core and additional maternal, perinatal and childhood outcomes, in addition to pregnancy episodes, underlying disease (severity) and timing of exposure, etc.Guided by data characterization activities in WP7 in year 1 for each of the defined maternal, perinatal and childhood outcomes, the population incidence/prevalence will be established in the data sources/populations used in demonstration projects, and the extent of variation according to methodological and population differences, and according to risk factors which may be considered confounders will be assessed. EFPIA partners (e.g. NVS, Merck KGaA, BMS and UCB) will contribute comparator data from secondary sources used in future medication safety studies addressing regulatory requirements. The validation and outcome incidence/prevalence studies will be coordinated across demonstration projects, focusing on the available data sources for these projects, to maximise harmonisation and efficiency and enhance study validity. The validation teams will check Demonstration Project output to check conformity with expectations."

Report describing existing coding systems, schemes and regulatory guidelines of reported medication exposed pregnancies

Task 2.3: Core data elements required for the prospective collection and follow-up of exposed pregnancies (M1-36) (UMAN, NUTH, UOSL, LAREB, UKZN, ENTIS, NVS, Novo Nordisk, Sanofi, AbbVie, Teva and WP7 partners). This task has two key components:1.Describe and evaluate existing coding systems, schemes and regulatory guidelines of reported medication exposed pregnancies (M1-12): Building on existing EMA and FDA regulatory guidance documents such as ICH E2B (R3) format for safety data exchange, ICH M1 MedDRA international terminology, IDMP/SPOR and ENTIS and OTIS protocols for prospective cohort collection, we will describe the requirements for spontaneous and solicited primary data collection format and coding, and the possibility and methods to map existing formats to those standards (in collaboration with WP7). Recommendations for changes to the current standards for data collection will be proposed where required following a gap analysis and assessment of content. This task will receive input from the outcomes task force, (operational across WP1, 2 and 7 to standardise and define data collection for assessment of key outcomes (maternal, foetal, perinatal, paediatric and stakeholder determined longer term outcomes to include, e.g., neurodevelopment). 2.Define core data elements for assessment of acute and long-term outcomes (e.g. neurodevelopment, immunological, cancer and potentially others) (M1-36): The recent valproate review and EMA scientific meeting on long term outcomes following pregnancy exposure have underscored the need to develop methods to assess risk of long term outcomes resulting from direct or indirect effects on reproduction. Data elements considered necessary to study both acute and long-term outcomes will be established through literature review, experience from recent global initiatives (e.g. OTIS/VAMPSS), an Expert Consultation Meeting and the cross-WP outcomes task force (WP1, 2, 7). The generated data elements will be tested and validated in demonstration projects (see below) and go through qualification advice by EMA. Recommendations will be developed a) for the standardisation of approaches to the collection of neurodevelopmental, oncological and immunological data; and b) for the analysis of neurodevelopmental, immunological and oncological outcomes in prospective data collection and in retrospective reports.

Final Data Management Plan

Task 8.3: Development and updating of data management plan (M1-M69) (UMCU, i~HD, BBMRI)In order to ensure the implementation of FAIR principles on all levels, ACRONYM will develop and further update a data management plan (DMP; in collaboration with WP7). A DMP describes the data management life cycle for all data sets that will be collected, processed or generated by the research project. ACRONYM’s DMP will detail: The handling of research data during and after the end of the project; What data will be collected, processed and/or generated; Which methodology and standards will be applied; Whether data will be shared/made open access, accessible for verification and re-use; How data will be curated and preserved.

Report with landscape analysis

Task 5.1: Landscape analysis of available information sources about drug use in pregnancy (M1-24) (UOSL, NVS, LAREB, ENTIS, SCC, the Synergist, EIWH, AbbVie, UCB, Pfizer, Sanofi). The aim in this task is to compile an inventory of key information sources that are available to HCPs and women of child bearing age about drug use before and during pregnancy and during the breastfeeding period and to explore their preferences in receiving/accessing such information. The task is subdivided in three subtasks: Sub-task 5.1.1: InventoryRationale: Different stakeholders (government, regulatory agencies, TIS, researchers, PV centres, HCP organisations, pharmacists, industry) are disseminating (different kinds of information) about the safety of drug use during pregnancy and lactation utilizing different delivery methods and with different purposes. Objective: To collect information on the current communication methodsMethods: For different categories of stakeholders an overview will be made of:1. The target group(s) of the communication; 2. The scope and purpose of the information; 3. The method(s) of information dissemination; 4. The process and methodology of interpretation of scientific research and how is this translated into up to date knowledge; and 5. Justification for and transparency about which sources are usedThe data will be collected using the most suitable data collection method including but not limited to desk research, interviews, surveys and digital channels. If stakeholder input is needed, this will be collected during a stakeholder event organised by WP6 in the beginning of the project. The task group will develop a briefing document for that meeting.Sub-task 5.1.2: Information discrepancies Rationale: A wide variety of information sources on medicines is available for women before and during pregnancy and during the breastfeeding period and the general public (which includes the women’s partners). Objective: assessing information discrepancies/conflictsMethods: Based on the landscape analysis above an assessment of the frequency and nature of information discrepancies, including discrepancies in the label, as well as the quality and health literacy level of the information between different sources will be made for at least 10 drugs in at least 3 different countries. The selection of drugs will be made by WP5 participants and stakeholder feedback (see 5.1.1)Sub-task 5.1.3: End-Users’ experiences Objective: To collect information on end users’ experience with the currently available information about the safety of drug use during pregnancy and lactation and to assess what their preferences would be in receiving such information in the future, both regarding content of the information and how it is delivered/made accessible to them.Methods: A survey and/or focus group discussions (in collaboration with stakeholders through WP6), with a good geographical spread within the European countries, with at least two groups (HCPs and patients) in at least 4 countries will be carried out on the following topics:1) information needs about drug use during pregnancy and lactation and the risks of untreated disease; 2) preferences for receiving this information; 3) perception on the importance of this information 4) channels do they use to access this information; 5) if there is information accessible, how understandable and useful it is; 6) if they use multiple information sources, how do they interpret conflicting information; and 7) socio-demographic, lifestyle, health literacy and health factors related to understanding and perception of this information.

Report with publications on results of component algorithms

Task 7.7 Quantification of the impact of choosing different algorithms (M9-M60) (ARS, UMCU, GSK, JAN, Sanofi, CNR-IFC, FISABIO, UOSL, ULST, CHUT, UMCG, LAREB in collaboration with the Outcomes Validation Task Force (WP1, 2) and third parties who will provide expertise and/or data). This task will document and quantify the impact of using different algorithms to extract data in health care databases. Moreover, the strategy will ensure support for sensitivity analyses aimed at addressing assumptions on data semantics. Finally, the strategy will aim to ensure compatibility with the OHDSI tools adopted by the EHDEN initiative, to facilitate data sources which are mapped to the OMOP CDMSome examples of data transformation that we envision follow: •Last Menstrual Period (LMP)/ Gestational age/ Gestational age: We will document how the time of start and end of pregnancy can be derived for each pregnancy in each data source and allow for sensitivity analyses (for instance, restricting to women whose LMP is directly recorded).•Drugs: Transforming drug prescriptions or dispensings in time-stamped episodes of treatment requires harmonisation or derivation from existing data, which is currently missing. We will develop standard algorithms using available information and standard sets of assumptions (for instance, that each study subject assumes the drug according to the recorded prescribed dose, or assumes one DDD per day, or assumes one tablet per day, or assumes the dispensed drug uniformly between dispensings) so that dose- and duration- specific analyses may be possible. In particular, standard sets of assumptions will be developed addressing timing of exposure relative to Last Menstrual Period. •Breastfeeding: different case identification algorithms will be tested to identify breastfeeding in different data sources. This will be validated where possible in collaboration with the outcomes taskforce of WP1/2/7. •Maternal child linkage: To study the effects of drugs during pregnancy and lactation on the child, it is essential to link maternal health records with the child. Based on a literature overview and the work from EU-Peristat we will further identify and test methods for both deterministic and probabilistic linkage of mothers and children in each of the DAPs, and cross-validate linkage whenever possible.The process of documenting and testing the study variables will follow the ‘component analysis’ workflow. We will test different case-finding-algorithms for WP1/2 maternal, neonatal and long-term paediatric outcomes, as well as for other key variables (see examples above). The outcomes taskforce of WP1/2/7 will validate the main variables whenever possible using a gold standard. Statistical techniques for outcome validation & misclassification ascertainment will be further explored, including (Bayesian) Latent Class modelling, imputation-based techniques like regression calibration, multiple imputation of measurement error and the simulation extrapolation technique). Component analysis using data from different sources will be used to evaluate impact of different algorithms on population-based incidence rates of events and to produce estimates of validity. Such ‘novel’ validation techniques will be compared with ‘classic’ validation studies in the demonstration projects that will be conducted in WP1. We will also apply existing methods to use the results of validation to correct the EHR-based disease risk estimates for misclassification.

Sampling, storage and handling standards, consent procedures and templates

Task 4.1: Setting up standards, facilities and operating procedures for collection and storage of breast milk and blood/plasma samples (M1-M12) (UPPS, BBMRI, NVS, UCB, Pfizer)A protocol template will be developed that specifies minimum quality requirements for sampling of human breast milk, including maturity of breast milk (established milk supply vs immature milk or very mature milk); volume and timing of sample collection (e.g., relative to start of feeding event and dosing), how samples are to be stored, handled, and shipped up to delivery to the biobank. The standard template will consider measures to reduce patient burden and will be optimised with input from patients, clinicians and regulators, in collaboration with WP6 for stakeholder engagement.For each specific drug, a sampling protocol will be developed including sample type, time for drug administration, type of collection, tube, labelling, centrifugation, information management etc. Instructions for transportation of frozen samples will be set up. Protocols will be tested and implemented for one site/one study at the time in close collaboration with task 4.6. At Uppsala Biobank the samples will be received, checked and registered in the biobank LIMS and stored in low-temperature freezers. The biobank has already established facilities set up for freezers with proper alarm systems and back-up freezers and processes for managing any failures. A process for withdrawals of samples for the needs of the project for analysis at the analytical centre is available at Uppsala Biobank. The process will be adjusted to further suit the project needs and managing the biobank.

Prototype of FAIR data catalogue -2nd

Task 7.4: Creation and filling of a FAIR data source catalogue(s) (M3-M36) (BBMRI, UMCG, GSK, JAN, Sanofi, SGUL). A FAIR data source catalogue will be created with specific search features that will be defined based on user requirements. We will use standard metadata models to make data resources findable, understandable, and provide fine-grained access control for researchers (FAIR implies access ‘under well-defined conditions’). Computer-readable terms that minimally describe the data resource (e.g. an ontology term or a (bio)schema.org term) are added for a searchable index of sources. The metadata defines the resource as a whole, the data sets, formats in which the data sets are, variables and provenance. The catalogue will also contain a private negotiation service to arrange data access, and a separate private site for simple analysis of data characterisation tables, which can be used in feasibility services following authentication. The catalogue will be filled by UMCG using the WP1 and 2 data.

Report with description of the functionality of the knowledge

Task 5.2 Developing an EU centralised open access digital knowledge bank (M6- 60) (LAREB, Sanofi SCC, ENTIS, ORC, the Synergist, EIWH, NVS, AbbVie, UCB, Pfizer) Rationale: By creating an EU centralised digital knowledge bank providing timely and high-quality general information and summary and interpretation of scientific research in literature and of data collected (from WP1 and WP2) this task will contribute to more harmonised and reliable evidence dissemination for the general public, pregnant or breastfeeding women and HCPs. Official labelling information will also be available in the knowledge bank.Members of ENTIS already have their own systems for keeping up to date knowledge of high quality. Some centres have a national knowledge bank, and some also available on their website. A common model to share the safety information they have collected is not yet in place. At this moment each country collects and interprets the scientific data themselves. By joining forces and introducing work-sharing between the members in a network, timely, uniform and high-quality information will be available to all European countries. Objective: The aim of this task is to develop an EU centralised digital knowledge bank for up to date information of drug use before and during pregnancy and breastfeeding and the risks of untreated disease (in English) for a selection of diseases and drugs that are common in pregnancy by combining information from different sources and providing common knowledge. The knowledge bank will start with information on drugs mostly used by women 15-45 years; drugs on which most often advise has been asked for. After the start the repository can be expanded and continuously be updated. General system requirements: The information in the digital knowledge database will be publicly available. The content of the database will be available (in English) through a website and interfaces will be built so that national translations will be accessible to share with 3rd parties such as other apps and websites in the country. A prerequisite for the digital knowledge databank is that all stakeholders have confidence in the quality and reliability of the information. ENTIS will be responsible for quality control. A peer reviewed system and protocol for screening and interpretation scientific research will be developed to add or change information into the knowledge bank to ensure reliability and that the information is up to date. This task is further sub-divided into the following sub-tasks:Sub-task 5.2.1: Agree upon the functionality of the databaseAim: To define the functionalities of the database. This includes; but is not limited to indexing of information, searching information, presenting information and presenting references for the information given. Method: Designing meeting with contributors and partners developing the tool will be organised to agree on the functionality of the database. Stakeholder feedback will be organised in collaboration with WP6.Sub-task 5.2.2: Build a knowledge management database Aim: To build the knowledge bankMethod: the knowledge bank will be built by ORCION in an agile way with the possibility to change things if deemed necessary, so that the final product will fit the needs of the end-users. To ensure usability the knowledge bank will be tested in cycles by WP5 members and stakeholders, to make sure that it fits with their needs. Sub-task 5.2.3: Interconnectivity Rationale: Making Translation of information possible to local language /national adaptations of the content is important. In local settings, it is possible that the safety information will need to be accessed at other points in the healthcare system than the central EU webpage, for example in apps or as part of other websites. A system to ensure the quality and reliability of the translation will be developed.Aim: to build Application programming interfaces (API) to allow for interconnectivity with local websites an

Overview of submitted manuscripts/abstracts of all five demonstration projects

Task 1.5: Execute five demonstration projects for established and newly marketed products to tackle methodological/data source issues where progress and innovation is needed (M12-M63): (UOSLO, JAN, Lilly, ULST, SGUL, CHUT, THL, USWAN, UMCG, CNR-IFC, FISABIO, FERR, INSERM, UMAN, EMA and Third Parties (institutions providing data, data expertise and clinical expertise), Sanofi, NVS, Pfizer, GSK, Merck) in collaboration with WP7.See also table task 1.5, Part B.The demonstration projects have been chosen according to the following criteria - high public health importance; address known knowledge gaps; together of sufficient variety (including established vs new medications, chronic vs acute condition, rare vs common condition) to innovate in their use of methodological approaches and new data sources. Data sources will be selected according to a combination of cost-effectiveness in terms of size of population and cost, and data quality but in addition priority will be given to use of new data sources.The five demonstration projects will each integrate multiple aspects for each therapeutic area i.e. medication use in pregnancy and in women of childbearing age; the impact of maternal disease on maternal, perinatal and childhood outcomes; and the impact of medications (medication classes) during pregnancy on outcomes. While one therapeutic area will take the lead for each methodological innovation, methods will be shared between demonstration projects. Each demonstration project follows a general process of subsequent steps: [Step1] data characterisation [M0-12] (WP7), [Step 2] protocol writing for each project and approval [M12-16], [Step 3] obtaining data access (WP7), [Step 4] Data validation and assessing variation in prevalence of adverse outcomes – see Task 1.3 - with the addition of validation of exposure and confounder data [M12-36], [Step 5] Statistical analyses starting with detailed Statistical Analysis Plans [M16-48], and [Step 6] Study report or manuscript [M48-54]. WP1 and WP7 will collaborate in the implementation of these demonstration projects according to a detailed process map (Appendix – after Section 5) to align and optimise the various tasks.The WP1 demonstration project teams will be made up of partners and third parties with substantive, methodological, and data source expertise, and will appoint clinical advisors to advise on treatment practice in Europe. Partners will be given the lead on various crosscutting methodological areas e.g. other than the demo project methodological leads already mentioned, UMCG will take the lead for medication utilisation protocols, USWAN will take the lead for integration of breastfeeding data when assessing confounding for long term outcomes, CNR-IFC will take the lead for validating non-prescription exposure data by linkage to prescriptions. A joint statistical method working group will be set up including representation of SGUL, GSK, JAN, Pfizer and WP7 (UMCU, ARS). The demonstration projects will follow the ENCEPP Code of Conduct for Scientific Independence and Transparency. A list of possible conflicts of interest for PP and EFPIA will be agreed before study teams for demonstration projects are finalised.

Minutes of annual general assembly meetings 3

Task 8.4: Planning and hosting of project & stakeholder meetings (M1- M60) (UMCU, NVS, UCB) In collaboration with WP6 for content of stakeholder meetings: Planning, organising, executing and post- processing of major project meetings such as the annual meetings, work group meetings, weekly coordination team meetings and monthly steering committee meetings monthly, as well as meetings with other IMI consortia and other adjacent projects

Database with reprotox data on platform

Task 7.9: Create a databank of reprotox data and pre-clinical physico-chemical, and target data (M1-M66) (RIVM, UMCU). In order to better predict which drugs may need to be targeted first for signal detection and evidence generation in WP1-4 it will be necessary to learn from pre-clinical data. Reprotox data that has been collected by CBG and RIVM and EFPIA will be linked to publicly available information on drug targets and kinetic parameters (through eTox) to develop prediction models of drugs that may need to be investigated pro-actively. This data source may also be inspected by WP1 and 2 for mechanistic explanation of findings. In this task we will explore machine learning tools based on positive and negative controls. The success of a sustainable ecosystem will critically depend upon the multi-stakeholder alignment and support we establish, especially via WP6, in financing, contributing data and new evidence, and in valuing and using this evidence to improve the confident and safe treatment of women. We will also leverage partner expertise in establishing and sustaining new not for profit ecosystems and in delivering scalable and interoperable data and information infrastructures, for example to sustain the knowledge bank.

Report on stakeholder meeting describing the model for a 21st century pregnancy data collection and signal detection system which should be able to replace traditional pregnancy registries

Task 2.1: Information and process needs, barriers and requirements (M1-36) (UKZN, NUTH, LAREB, UMAN, UOSL, MHRA, ENTIS, NVS, GSK, Sanofi, AbbVie).In this task we will prepare, in collaboration with WP1, content for a stakeholder workshop, to establish:a) What are the information requirements and how do they differ by various stakeholders to enable informed decisions about prescribing, dispensing, regulating, and using drugs in pregnancy and lactation;b) The requirements to instil Healthcare provider (HCP) and public confidence that reporting of medication exposed pregnancies is through a trusted, secure and confidential system which supports patient-prescriber clinical risk benefit assessment as well as regulatory guidance where use of a medicinal product has occurred or is being considered in pregnancy; c) The barriers that will need to be overcome to implement a harmonised pregnancy pharmacovigilance system (for both public and private organisations) that will be supported and accepted by various stakeholders d) A proposal as to how existing capacity, infrastructure and expertise could be better leveraged. The output of this workshop will be an agreed model for a 21st century system for early pregnancy safety data collection & analysis as an alternative to traditional pregnancy registries. Components of this system will be further developed and trialled in demonstration projects within task 2.5 and, based on the findings from these tasks, a framework for the operation of a future end-to-end PV system established in 2.6).

In vitro transport data for at least 10 model drugs in both in vitro models (including validated bioanalytical methods and drug-specific properties determining blood to milk transfer rates

Task 3.2: Development of an improved in vitro model to identify parameters determining the rate and extent of blood-milk excretion (M4-M57) (KUL, NVS, UNIBO, Bionotus, Covance). The aim is to develop and characterise an improved in vitro model for drug passage from maternal blood to human breast milk. The model will be based on cultured human mammary epithelial cells11,12. In parallel, a mammary epithelial cell model corresponding to the species selected for Task 3.3 will be established. Primary cultures of mammary epithelial cells, grown as monolayers or on inserts, will be utilised to determine transfer rate data for the model drugs across mammary epithelial cells13. The literature search performed in Task 3.1 will be used to inform the development of the in vitro models. At least 10 model compounds selected in Task 3.1 will be used in a first wave of in vitro experiments. High-throughput and sensitive LC-MSMS methods will be developed and validated according to EMA/FDA guidelines and EBF recommendations. These methods will be applied for accurate and precise measurement of drugs in in vitro samples.As a secondary objective, the data obtained in Task 3.2 will be compared to data generated on existing models of trans-epithelial transport (e.g., Caco-2 / MDCK / PAMPA) to investigate whether those existing models could predict the mammary cell culture data and could be used as replacement. This would allow utilisation of a large amount of existing data from easy-to-access assays that are commonly found in discovery programs across industry.

In vivo data on lactation transfer in one or more animal species

Task 3.3: In vivo experiments in lactating non-clinical species (likely Göttingen minipig and/or pig farm breed) (M4-M48) (UNIBO, Ellegaard, Bionotus, Covance, Lilly, NVS, Teva). The aim is to develop and characterise an improved in vivo model for drug passage from maternal blood to human breast milk. The primary criterion when choosing a preclinical animal model must be its translational value which is dependent on its analogies with the human species. The literature search performed in Task 3.1 will be used to inform and/or confirm the selection of the appropriate species. Currently, the use of rodent species leads to the common view that “animal data are generally not useful in predicting drug concentrations in human milk” 14. However, a porcine species may represent a more suitable model, with better anatomical and physiological, thus metabolic, similarities15. These in vivo studies will use innovative designs considering the possibility for micro-dosing, cassette dosing and blood sampling in offspring. Such approaches are expected to maximise the amount of data generated in the animal model, consistent with the 3R principle. Compound selection will be based on the criteria described in task 3.1 and the compounds already selected in Task 3.2. Sensitive LC-MSMS methods will be developed and validated according to EMA/FDA guidelines and EBF recommendations. Bioanalytical method details will be shared with WP4 for corresponding model drugs.

Annual reports on external communication results for impact assessment -3

Task 5.3: Engage HCPs, pregnant and breastfeeding women and general public and to stimulate pregnancy reporting through PV system and participation in research; (with WP2, WP6 and WP7) (M6-M60) (NUTH, ENTIS, LAREB, Synergist, UPPS, EIWH, (third parties such as EU organisation for GPs/ gynaecologist /midwives/pharmacists) Pfizer, Sanofi, NVS, AbbVie, UCB)Rationale: Based on the ethical discussions in WP7 (task 7.3) about the idea of a learning healthcare system where we have a moral duty to generate evidence on the use of medicines in pregnancy, we will translate the learnings from the ethical research into communication programs to stimulate HCPs and pregnant women awareness that they have can play an active role in increasing general knowledge about the safety of drug use during pregnancy and breastfeeding in the post-marketing phase of a drug by contributing to WP2 as well as WP4. Aim: To build awareness and stimulate actual participation from the targeted audience Method: Communications directed to relevant stakeholders will be developed using push-pull strategies and developing value propositions. A combination of very targeted communication on social media and other digital channels together with point of care material will disseminate the message and capture the audiences utilising health literacy methods and tailored messages to stimulate their participation. The campaign overarching messages will build on various awareness messages and value propositions for pregnant women and HCPs. Each exposure will be the opportunity to engage and offer participatory mechanisms. Messages and value propositions will be tested ahead and then will be assessed in terms of participatory rate and ultimately behaviours changes, partly measured through the channels we will deliver (online, apps, etc.) In the same countries as the information materials are tested, communication strategies (including through social media, promotion through pharmaceutical companies, national healthcare systems and international/national regulatory organisations) will implemented to inform the general population, pregnant women/women of reproductive age and healthcare professionals about the importance of reporting to the pregnancy pharmacovigilance system. The effects of the campaign will be measured, both in terms of increased reporting, but also in terms of increased awareness about the importance of reporting among HCPs.

Report with core data elements to collect long term outcomes

Task 2.3: Core data elements required for the prospective collection and follow-up of exposed pregnancies (M1-36) (UMAN, NUTH, UOSL, LAREB, UKZN, ENTIS, NVS, Novo Nordisk, Sanofi, Teva, BMS and WP7 partners). This task has two key components:1.Describe and evaluate existing coding systems, schemes and regulatory guidelines of reported medication exposed pregnancies (M1-12): Building on existing EMA and FDA regulatory guidance documents such as ICH E2B (R3) format for safety data exchange, ICH M1 MedDRA international terminology, IDMP/SPOR and ENTIS and OTIS protocols for prospective cohort collection, we will describe the requirements for spontaneous and solicited primary data collection format and coding, and the possibility and methods to map existing formats to those standards (in collaboration with WP7). Recommendations for changes to the current standards for data collection will be proposed where required following a gap analysis and assessment of content. This task will receive input from the outcomes task force, (operational across WP1, 2 and 7 to standardise and define data collection for assessment of key outcomes (maternal, foetal, perinatal, paediatric and stakeholder determined longer term outcomes to include, e.g., neurodevelopment). 2.Define core data elements for assessment of acute and long-term outcomes (e.g. neurodevelopment, immunological, cancer and potentially others) (M1-36): The recent valproate review and EMA scientific meeting on long term outcomes following pregnancy exposure have underscored the need to develop methods to assess risk of long term outcomes resulting from direct or indirect effects on reproduction. Data elements considered necessary to study both acute and long-term outcomes will be established through literature review, experience from recent global initiatives (e.g. OTIS/VAMPSS), an Expert Consultation Meeting and the cross-WP outcomes task force (WP1, 2, 7). The generated data elements will be tested and validated in demonstration projects (see below) and go through qualification advice by EMA. Recommendations will be developed a) for the standardisation of approaches to the collection of neurodevelopmental, oncological and immunological data; and b) for the analysis of neurodevelopmental, immunological and oncological outcomes in prospective data collection and in retrospective reports.

Protocols of selected demonstration projects 1-5 uploaded on EU-PAS register

Task 2.5: Demonstration projects (M12-M69) (LAREB, UKZN, NUTH, UMAN, ENTIS, MHRA, NVS, Teva, BMS. For WP7: UMCU, ARS, RIVM). The goal of this IMI project is to deliver a regulatory endorsed/approved and sustainable system to provide evidence on the effects of disease and drug use during pregnancy. WP1 focuses on secondary use of population-based health data, whereas WP2 focusses on the collation and analysis of reported pregnancies (exposed and non-exposed) as well as primary data collection. To test the system, we need to assess: i) ability to link/pool and use data in existing data sources on reported cases to be able to provide evidence on safety ii) alternative methods to collect prospective surveillance data; and iii) how primary data collection on pregnancies, exposure and outcome data can be analysed. The demonstration projects of WP2 will test these aspects of the system. System testing aspect: Analysis of existing case reports (active and passive surveillance) data across public and EFPIA data sources Demo Project 1: Analysis of existing pregnancy pharmacovigilance and active surveillance dataRationale: In Task 2.2 (cataloguing existing pregnancy exposure/outcome data in pharma and academia), it is likely that unanalysed data will be identified. Given that some of this data may relate to medications for which limited exposure/outcome data are available, collective analysis of these data may provide clinically useful information on safety.Objective: Analysis of existing pharmacovigilance/reported pregnancy data from diverse sources (pharmacovigilance databases, registries, teratology information centres) for the purpose of a) providing evidence on medications already in use, including prevalence of key pregnancy outcomes b) development of de-duplication and signal detection techniques using traditional and novel machine learning techniques and c) to inform methodological guideline development in Task 2.7. Method: Based on the type of exposure, descriptive (comparing observed vs. expected background rates) or controlled (comparing vs. disease-matched unexposed rates), analyses of pregnancy outcome rates of key interest will be conducted using these data (where possible). In collaboration with WP1, WP6, and WP7, using data sources identified in Task 2.2 and the common data analysis model (Task 2.4), a standardised end-to-end infrastructure for enhanced pharmacovigilance encompassing data collection methods, database structure, data definitions, data processing, signal detection, and statistical estimation of prevalence of key pregnancy outcomes can be developed and tested (see appendix 2 for process map). De-identified case reports or aggregated data (using distributed analytics) may be shared by both public and private partners using the secure digital research environment in WP7, offering the opportunity for integration in a central database of bespoke statistical algorithms to support automated signal alerts to further enhance pregnancy PV. The choice of disease or therapeutic areas will seek alignment with WP1 and are likely to include a) Multiple Sclerosis, b) Migraine/ NVP, c) breast cancer; d) depression; and furthermore, will be based on a hitlist that will be provided by WP7 (task 7.9) based on machine learning predictions.This task will be led by LAREB and NVS with support from all other WP2 partners, WP7 will provide technical support. System testing aspect: central database of medication exposed pregnancy cases Demo Project 2: Database of prospective pregnancy exposure and outcome data (M12-60)Rationale: several systems are already in place to collect information on pregnancies, we would like to overcome this fragmentation by finding ways (distributed or centralised) to analyse this data collectively.Objective: test whether and how currently used apps, web-based platforms, industry collected PV reports and other services for prospective data collection can feed into a common database to all

Way of working of Scientific Governance Board and members

Task 4.5: Organisation of a Scientific Governance Board (M48-69) (UPPS, NVS, UCB). A Scientific Governance Board including patient representatives and other stakeholders will be organised for reviewing and approving requests for milk samples for research purposes in accordance with legal and ethical principles. Scientific experts will be selected to secure sufficient expertise from relevant scientific domains as well as EFPIA partners.

Report on the core data elements and analytical standards for informing HCP and patients on risks associated with exposure during pregnancy and lactation as agreed during stakeholder consultation meeting

Task 1.2: Define core data elements to allow assessment of medication utilisation and safety in pregnancy to meet regulatory requirements and standards for inclusion in product label. (M1-M12) (CHUT, GSK, ULST, SGUL, UMAN, UOSLO, Novo Nordisk, JAN, Merck, Pfizer, Lilly, NVS, EMA). This task is aimed at reaching agreement with all stakeholders including but not limited to academic, industry, clinical experts, EMA (and other regulators) on •what the core (and additional) maternal, perinatal and childhood outcome data elements are, e.g. major congenital anomalies, foetal deaths, small for gestational age, long term outcomes; •the required number of exposed pregnancies to be tested (pending medication utilisation in pregnant women); •the required analytical methods and including hypotheses to be tested, e.g. doubling risk for outcome x as compared to disease comparator;•appropriate design (e.g. comparator) that would satisfy regulatory requirements (expedited reporting; PSUR; PASS) and•quality standards for inclusion in SmPC/product label to adequately inform HCPs and patients.In collaboration with WP2, WP6 and WP7, multi-stakeholder consultation meetings will be prepared. In advance of the multi-stakeholder meetings, Novo Nordisk will lead the collection of publicly available information on these elements from literature, regulator guidance documents and product labels. Merck and CHUT will write a briefing document and GSK and CHUT will lead the discussion for WP1 during the consultation meeting. JAN and CHUT will write a report summarizing the outcome of the consultation meeting.The agreed data elements and methods will be revisited as part of Task 1.6 in the light of demonstration project results.

Prototype of FAIR data catalogue-1st

Minutes of annual general assembly meetings 4

Annual reports on external communication results for impact assessment-2

Report on existing common data models and proposals for ConcePTION

Task 7.5: Create and operate a platform and common data models for sharing data and remote access (M1-M60) (UMCU, ARS, BBMRI, GSK, JAN, Elevate). A state-of-the-art digital research environment with ISO certified and GDPR proof services for remote collaborations will be subcontracted and operated. Access to the application server will be only allowed using two-factor authentication. The environment will be able to host multiple research projects, each with its own secured area to share data and results and provide access through remote desk tops clients. The infrastructure will offer several analytical tools (e.g. R, SQL database, Shiny, Stata) word processing software, and utilities. To streamline and conduct the data characterisation and distributed data analytics for the different WPs (1 & 2) that want to use the platform for distributed analytics, an operations team will be installed that will coordinate the various tasks This will involve the negotiations for data access and access rules, distribution of instructions and scripts, as well as facilitating the transfer of results to the DRE. For management, documentation and tracking of the different tasks we will operate TASKA which was developed in the IMI-EMIF project. Standard operating procedures & training webinars for DAPs will be developed, whenever necessary. Common data models for data characterisation and demonstration studies will be defined together with WP1 and 2 and based on existing CDMs (EUROlinkCAT, EU-ADR, OMOP, EMIF Use Cases, SENTINEL, PCORnet, LifeCycle) as a starting point, and standard procedures will be developed that run against the chosen CDMs. We envision that different CDMs will be chosen at different steps of the data flow. First, a set of common input files (D2), which will encompass approximately 4 tables (see Figure 3.1b, Part B): for instance, the identifiers of mothers and children with birthdate will be stored (in Population), each event of delivery with be stored (in Events), gestational age with the same date will be stored (in Measurement). Second, datasets of study-specific variables (D3 in the figure): for instance, LMP will be stored as a derived variable from the event of delivery and the gestational age. Third, datasets specific to the study design (D4 in the figure): for instance, if the study design is a case-control, D4 will encompass the dataset of case-sets. Even though we will aim to create syntactically stable CDMs, the content stored in the CDMs, and the values allowed for the different columns, will be data source- and project-specific: for instance, if in a data source Last Menstrual Date is directly recorded this will be stored and used along with the derived LMP. However, the data transformation procedures will be programmed centrally, as far as possible.All the datasets will remain stored within the premises of the DAPs up to D3. D4 will be shared within the study team using the secure remote environment. In case one or more of the study designs of the demonstration projects require that D4 contains information that the DAPs are not allowed to share, the distributed implementation of the statistical analysis (t4) will be developed. For instance, if estimation of a propensity score is needed, a distributed estimation of regression will be implemented, following similar experience in Sentinel To support the semantic and syntactic harmonisation, available tools will be leveraged, which include UMLS OHDSI ontologies and tools, the IDMP standards and Article 57 database, ADVANCE Codemapper and VaccO. DAPs will be trained with e-learning materials to use these tools. Since we are prepared to work both with data sources that have already been mapped to the OMOP structure, as well as data sources which are in the original format, different processes will be supported to map the local data to the common input files, according to whether the local data is in OMOP or not. In particular, if the local data is in OMOP, data so

Additional third party selection procedure description

Task 8.8: Management demonstration project funds (M1- M60) (UMCU)Within the third party budget funding is set aside to acquire additional data for quality assessment and demonstration studies (322.5K for WP1 (to be managed by ULST) and 150K for WP7 (to be managed by UMCU)). WP8 will manage a transparent procedure adhering to all relevant EU rules and institutional procedures to identify additional third parties/data sources that add value to the consortium. The WP1 and WP7 leadership will play a key role in this process.

Reports from Advisory Board and Ethic Report 5

Task 8.6: Implementation of the External Advisory Boards (M1-M69) (UMCU, NVS, UCB)In this task we will manage and prepare all necessary activities for an external advisory board, including Scientific, and Ethical KOLs in collaboration with WP5 and 6. As part of this task, the project management and coordination team will arrange and deal with all technical aspects of scheduling/organising meetings requested and the logistics of those meetings.

Reports from Advisory Board and Ethic Report 4

Task 8.6: Implementation of the External Advisory Boards (M1-M60) (UMCU, NVS, UCB)In this task we will manage and prepare all necessary activities for an external advisory board, including Scientific, and Ethical KOLs in collaboration with WP5 and 6. As part of this task, the project management and coordination team will arrange and deal with all technical aspects of scheduling/organising meetings requested and the logistics of those meetings.

Report on lactation characteristics of animal species (rodent, rabbit, (mini)pig, dog, non-human primate, etc; anatomy/histological structures, milk composition, duration of lactation, etc); Selection of the animal species to be used in in vivo studies

Task 3.1: Literature search (M1-M6) (UNIBO, TEVA, KUL, CHUT, ULAUSUNIGE UOSL, Bionotus, Covance, Ellegaard, NVS). First, literature searches will be conducted on: (i) lactation characteristics of non-clinical tox species (anatomy/histological structures, milk composition, duration of lactation); (ii) non-clinical (in vivo and in vitro) lactation models; (iii) computational approaches to determine drug milk excretion; (iv) non-clinical data available on concentration of drugs in milk, pup exposure; (v) human lactation data, in collaboration with WP4, including milk-mediated drug exposure in breastfed infants (as a benchmark for predictions generated in this WP; possible link to WP4 if/when human lactation data would be available). This knowledge mapping effort should reveal the current state-of-the art including limitations and shortcomings. This will aid in defining a consensus and starting points for development and characterisation of fit-for-purpose non-clinical (in vitro human & in vivo animal) and computational (in silico) models (subsequent tasks in this WP). Information gathered will be combined in structured overviews of existing non-clinical and computational models and clinical reference data on lactation and risk assessment of drug exposure in breastfed infants.The structured overview will be an important technical information source for selection of a set of 10 therapeutically relevant model drugs that will be used in subsequent tasks in this WP, i.e. for assessment of model performance and applicability (Task 3.2-3.4). Criteria for selection of model drugs will be: (i) different chemical structures, physicochemical properties; (ii) different modalities (both LMW and biologicals); (iii) clinical relevance including medical need in the pregnant population; (iv) quality and resolution of available reference data; (v) clinical data sets for which a robust popPK model is available; (vi) availability of PK data; (vii) consider the model drugs that would be(come) available from EFPIA partners and, if possible (dependent on timelines), in WP4 (the demonstration projects in WP4 will generate data sets on breast milk concentrations for selected model drugs).

Validation of an animal model for lactation transfer (including translation from animal to human using available human data)

Task 3.3: In vivo experiments in lactating non-clinical species (likely Göttingen minipig and/or pig farm breed) (M4-M63) (UNIBO, Ellegaard, Bionotus, Covance, Lilly, NVS, Teva). The aim is to develop and characterise an improved in vivo model for drug passage from maternal blood to human breast milk. The primary criterion when choosing a preclinical animal model must be its translational value which is dependent on its analogies with the human species. The literature search performed in Task 3.1 will be used to inform and/or confirm the selection of the appropriate species. Currently, the use of rodent species leads to the common view that “animal data are generally not useful in predicting drug concentrations in human milk” 14. However, a porcine species may represent a more suitable model, with better anatomical and physiological, thus metabolic, similarities15. These in vivo studies will use innovative designs considering the possibility for micro-dosing, cassette dosing and blood sampling in offspring. Such approaches are expected to maximise the amount of data generated in the animal model, consistent with the 3R principle. Compound selection will be based on the criteria described in task 3.1 and the compounds already selected in Task 3.2. Sensitive LC-MSMS methods will be developed and validated according to EMA/FDA guidelines and EBF recommendations. Bioanalytical method details will be shared with WP4 for corresponding model drugs.

Report confirming that all the relevant documents for using animal experiments (WP3) prior to the start of the research activity raising ethics issue and that they are kept on file

Task 7.10: Ethical feedback (M3-M58) (UMCU)In this task we will collect copies from all templates, IRB review comments and approvals and documentation from the sites that are required to comply with the ethical (see section 5) and IMI obligations. This task will deliverable five deliverables (D7.18-7.22), providing proof and documentation that ConcePTION partners and third parties are compliant.

Standard documents for pre-examination processes for breast milk handling

Task 4.4: Developing standard documents for pre-examination processes for breast milk handling and biobanking activities (M1-M69) (BBMRI, UPPS, CHUT, UOSL, Pfizer, CHUV). Building a ‘Breast Milk Biobank Analysis Center’ requires a comprehensive quality management approach, to secure and control all operations associated with conducting clinical trials, biobanking activities, and downstream analysis procedures at multiple process levels. The partners will develop the basic structure of this quality management system from a set of applicable European and International Standards for biobanking and pre-analytical sample handling (CEN/TS 16835, ISO 20387, ISO 9001, ISO 20186 etc.) and the guideline for good clinical practice E6 (R2), ICH-GCP for the protection of donor rights and safety. SOPs from the project partners and from the literature will be reviewed to verify key processes and methods. The collection, processing steps, processing times, storage temperature, freeze-thaw-cycles and so forth, will be addressed to optimize SOPs to optimal sample quality for subsequent analytical methods. The open structure of the standardization process allows transparency to all involved or interested parties. Building and hosting a BBMRI Technical committee will allow all partners to join guided standardization activities with the aim to develop standardized documents. Regular committee meetings will be initiated and hosted and will take place via web-conferences and/or f2f project meetings. Based upon project partners outcomes, standardization activities will be carried out jointly with the partners within the BBMRI Technical committee, aiming to result in the contribution to, and the preparation of, one or more standard document(s), with the focus on the standardization of the pre-analytical and analytical management of breast milk, based on collection, processing steps, processing times, storage temperature, freeze-thaw-cycles and analytical method for defined intended use. The transformation of research findings into application/product ideas transferred to the market afterwards is also assisted by such standardization activities, as they support the dissemination and implementation of innovative knowledge. With the aim to spread the awareness concerning standardization activities of the project, information about standards and standardization will be provided, e.g. via presentations at conferences and workshops, contribution to journals and scientific publications. The results may also be published in guidelines for the handling of human breast milk. Standardization activities will be provided on the website of Uppsala Biobank.

Test report of FAIR data catalogue 2nd

Templates and guidance for local and central Data Privacy Impact Assessments for datasources and repository for continuous collection of completed forms and approvals

Project management plans

Task 8.1: Internal project management and coordination (M1- M60) (UMCU and all WP leaders)Development of project management communication and quality assurance plans as a support to the consortium with the main goal to facilitate the collaboration between partners and ensure that IMI requirements are respected. Ensure clear internal communication and handle external project correspondence and the day-to-day requests from partners and external bodies; Implement and maintain internal reporting and monitoring procedures; Report progress, the results and the necessary changes to the work plan; develop risk management process; implement and maintain the project infrastructure and internal workspace; guard consortium principles. Furthermore, the project management team will further deal with any legal issues that may arise and install a complaints officer where complaints about research participation by women can be shared in a trusted manner. A complaints procedure will be established

Report with publications of demonstration projects

Detailed project plan, plus tracking tools, to be maintained throughout the life of the project

Report with procedures for evidence retrieval and synthesis for the knowledge bank

Report on scope and limitations of in vivo and in vitro non-clinical and computational models for drug milk excretion and breastfed infant exposure; Selection of a panel of at least 10 model compounds for initial evaluation of non-clinical models

Task 3.1: Literature search (M1-M6) (UNIBO, TEVA, KUL, CHUT, UNIGE UOSL, Bionotus, Covance, Ellegaard, NVS). First, literature searches will be conducted on: (i) lactation characteristics of non-clinical tox species (anatomy/histological structures, milk composition, duration of lactation); (ii) non-clinical (in vivo and in vitro) lactation models; (iii) computational approaches to determine drug milk excretion; (iv) non-clinical data available on concentration of drugs in milk, pup exposure; (v) human lactation data, in collaboration with WP4, including milk-mediated drug exposure in breastfed infants (as a benchmark for predictions generated in this WP; possible link to WP4 if/when human lactation data would be available). This knowledge mapping effort should reveal the current state-of-the art including limitations and shortcomings. This will aid in defining a consensus and starting points for development and characterisation of fit-for-purpose non-clinical (in vitro human & in vivo animal) and computational (in silico) models (subsequent tasks in this WP). Information gathered will be combined in structured overviews of existing non-clinical and computational models and clinical reference data on lactation and risk assessment of drug exposure in breastfed infants.The structured overview will be an important technical information source for selection of a set of 10 therapeutically relevant model drugs that will be used in subsequent tasks in this WP, i.e. for assessment of model performance and applicability (Task 3.2-3.4). Criteria for selection of model drugs will be: (i) different chemical structures, physicochemical properties; (ii) different modalities (both LMW and biologicals); (iii) clinical relevance including medical need in the pregnant population; (iv) quality and resolution of available reference data; (v) clinical data sets for which a robust popPK model is available; (vi) availability of PK data; (vii) consider the model drugs that would be(come) available from EFPIA partners and, if possible (dependent on timelines), in WP4 (the demonstration projects in WP4 will generate data sets on breast milk concentrations for selected model drugs).

Contact database (stakeholders and key project contacts)

Task 8.2: Enhance and optimise collaboration within the consortium (M1-M60) (UMCU, NVS, UCB and all WP leaders)This task will aim to keep partners involved in the project by stimulating collaboration and information sharing in a systematic manner. The project management team will: Design and maintain of partner-specific templates for collecting input for required EU documents; Coordinate internal and periodic technical reporting; Support timely production of deliverables and reports, and maintain project archive; Guide partners in project administration by providing a guides and FAQs, as well as a webinar if needed; and Coordinate financial and administrative issues: establish and maintain financial records, co-ordinate financial statements submission by all project partners, calculate partner shares according to rules agreed in the Consortium Agreement. In addition, collaboration will be stimulated by newsletters, and periodic team climate assessments (survey). Impact assessment will be conducted annually.

Report with publications on the results of the demonstration studies & cross validation with WP3 plus recommendations

Task 4.6: Recommendations to health authorities to adopt the methods developed in WP3 and W4 for evidence generation to include in product labelling (M44-M69) (UPPS, CHUT, UOSL, NVS, UCB, CHUV)To impact a change to the current paradigm regarding the lack of available high quality scientific data on drug transfer to infants through breast milk, we will seek advice and make recommendations to regulatory agencies regarding acceptability of utilizing the human breast milk biobank sampling, protocols and procedures to conduct adequate studies for product labelling (SmPC), as well as in vivo and in vitro lactation models as major elements in a risk assessment evidence strategy (in collaboration with WP3 and WP6). To the extent possible, the interactions with regulatory agencies will be approached holistically as a continuum of evidence from the entire package of methodologies arising from both WP3 and 4, owing to the considerable inter dependencies of these WPs.The report in D4.9 will detail the results of the demonstration studies (+ published/publishable manuscripts) and a synthesis of the main recommendations that follow from these studies.

Minutes of annual general assembly meetings 1

Report on lessons learned from the conduct of the PoC feasibility assessments and implications for the sustainability plan

Task 8.9: Task 8.9 (M20 - M69) (TTOP, UMCU, SYNERGIST, EIWH)As part of the sustainability activities, proof-of-concept feasibility assessments will be conducted within the ConcePTION consortium. The objective of this exercise is to ‘test’ the process of formulating study requests and collecting input from partners. This will provide important knowledge for the sustainability activities beyond the life span of the project (Task 8.7).Based on specific requests in the form of a questionnaire from the requestor, public beneficiaries and third parties are requested to indicate to what extent they are able to fulfil the feasibility assessment requirements. The Sustainability Task Force, in collaboration with the assessment requestor will determine which of the requests received is most viable. Based on this, a direct financial contribution will be made to the beneficiary/third party to support the work.

Roadmap of planned project outputs, including qualification advice submissions, mapped to stakeholder needs and planned stakeholder interactions

Task 6.1: Understand stakeholder needs and perceptions and align with project outcomes (M1 – M12) (i~HD, EMA, MHRA, EFGCP, Synergist, KUL, EIWH, FERR, NVS, Takeda, JAN). In this task WP6 will act as a facilitator and coordinator, working with Work Package leaders to gather insights from key stakeholders (regulatory, HCPs, women and patients, maternal health foundations, charities, etc.) on their needs and perceptions, to help achieve project goals and deliver maximum possible value and impact to target audiences. The outputs from task 6.1 will feed into all other work packages.The first step is to determine what input is needed from stakeholders. A stakeholder landscape analysis will be conducted as a resource to the consortium. A variety of tools will be used to gather input from stakeholders, including literature reviews, surveys, interviews, focus groups, and digital tools (e.g. social media outreach, digital listening tools), and to build ongoing dialogue with stakeholders. This task will seek to understand current perceptions on medication use during pregnancy and breastfeeding, barriers to confidently utilising medicines during pregnancy and breastfeeding, the guidance currently available to mothers and professionals, their unmet needs and the potential contributions of new project evidence. The investigation will also elucidate barriers to research participation on the part of mothers.This task will help the WPs to design outputs that align to stakeholder needs. A roadmap of project outputs aligned to stakeholder needs and recommended stakeholder interactions will be provided. It will identify appropriate timeframes to iteratively re-engage with stakeholders at the consortium level to reassess their needs, and to help avoid duplication across the WPs. Any needs identified that are beyond the scope of project will be curated and communicated to other funding bodies as possible future call topics (e.g.FP9, charities).

Final study protocols for demonstration projects submitted to EU PAS register

Task 1.5: Execute five demonstration projects for established and newly marketed products to tackle methodological/data source issues where progress and innovation is needed (M12-M54): (UOSLO, JAN, Lilly, ULST, SGUL, CHUT, THL, USWAN, UMCG, CNR-IFC, FISABIO, FERR, INSERM, UMAN, EMA and Third Parties (institutions providing data, data expertise and clinical expertise), Sanofi, NVS, Pfizer, GSK, Merck) in collaboration with WP7.See also table task 1.5, Part B.The demonstration projects have been chosen according to the following criteria - high public health importance; address known knowledge gaps; together of sufficient variety (including established vs new medications, chronic vs acute condition, rare vs common condition) to innovate in their use of methodological approaches and new data sources. Data sources will be selected according to a combination of cost-effectiveness in terms of size of population and cost, and data quality but in addition priority will be given to use of new data sources.The five demonstration projects will each integrate multiple aspects for each therapeutic area i.e. medication use in pregnancy and in women of childbearing age; the impact of maternal disease on maternal, perinatal and childhood outcomes; and the impact of medications (medication classes) during pregnancy on outcomes. While one therapeutic area will take the lead for each methodological innovation, methods will be shared between demonstration projects. Each demonstration project follows a general process of subsequent steps: [Step1] data characterisation [M0-12] (WP7), [Step 2] protocol writing for each project and approval [M12-16], [Step 3] obtaining data access (WP7), [Step 4] Data validation and assessing variation in prevalence of adverse outcomes – see Task 1.3 - with the addition of validation of exposure and confounder data [M12-36], [Step 5] Statistical analyses starting with detailed Statistical Analysis Plans [M16-48], and [Step 6] Study report or manuscript [M48-54]. WP1 and WP7 will collaborate in the implementation of these demonstration projects according to a detailed process map (Appendix – after Section 5) to align and optimise the various tasks.The WP1 demonstration project teams will be made up of partners and third parties with substantive, methodological, and data source expertise, and will appoint clinical advisors to advise on treatment practice in Europe. Partners will be given the lead on various crosscutting methodological areas e.g. other than the demo project methodological leads already mentioned, UMCG will take the lead for medication utilisation protocols, USWAN will take the lead for integration of breastfeeding data when assessing confounding for long term outcomes, CNR-IFC will take the lead for validating non-prescription exposure data by linkage to prescriptions. A joint statistical method working group will be set up including representation of SGUL, GSK, JAN, Pfizer and WP7 (UMCU, ARS). The demonstration projects will follow the ENCEPP Code of Conduct for Scientific Independence and Transparency. A list of possible conflicts of interest for PP and EFPIA will be agreed before study teams for demonstration projects are finalised.

Summary and review of collected SOPs from project partners and literature

Task 4.4: Developing standard documents for pre-examination processes for breast milk handling and biobanking activities (M1-M60) (BBMRI, UPPS, UNIGE, CHUT, UOSL, Pfizer). Building a ‘Breast Milk Biobank Analysis Center’ requires a comprehensive quality management approach, to secure and control all operations associated with conducting clinical trials, biobanking activities, and downstream analysis procedures at multiple process levels. The partners will develop the basic structure of this quality management system from a set of applicable European and International Standards for biobanking and pre-analytical sample handling (CEN/TS 16835, ISO 20387, ISO 9001, ISO 20186 etc.) and the guideline for good clinical practice E6 (R2), ICH-GCP for the protection of donor rights and safety. SOPs from the project partners and from the literature will be reviewed to verify key processes and methods. The collection, processing steps, processing times, storage temperature, freeze-thaw-cycles and so forth, will be addressed to optimize SOPs to optimal sample quality for subsequent analytical methods. The open structure of the standardization process allows transparency to all involved or interested parties. Building and hosting a BBMRI Technical committee will allow all partners to join guided standardization activities with the aim to develop standardized documents. Regular committee meetings will be initiated and hosted and will take place via web-conferences and/or f2f project meetings. Based upon project partners outcomes, standardization activities will be carried out jointly with the partners within the BBMRI Technical committee, aiming to result in the contribution to, and the preparation of, one or more standard document(s), with the focus on the standardization of the pre-analytical and analytical management of breast milk, based on collection, processing steps, processing times, storage temperature, freeze-thaw-cycles and analytical method for defined intended use. The transformation of research findings into application/product ideas transferred to the market afterwards is also assisted by such standardization activities, as they support the dissemination and implementation of innovative knowledge. With the aim to spread the awareness concerning standardization activities of the project, information about standards and standardization will be provided, e.g. via presentations at conferences and workshops, contribution to journals and scientific publications. The results may also be published in guidelines for the handling of human breast milk. Standardization activities will be provided on the website of Uppsala Biobank.

EMA Qualification Advice: Making the best use of the new non-clinical and in silico predictive tools generated in this WP3 to inform risk assessment on medication use during lactation

Task 3.8: Request EMA ITV meeting and QA regarding the use of these new predictive tools as best practices for informing risk assessment on medication use during lactation (M37-M69) (CHUV, UOSL, CHUT, KUL, NVS). Based on quantitative insights regarding drug milk excretion rates as well as predicted infant drug exposure generated in this WP, activities in this task will focus on seamless integration of insights from non-clinical and in silico evidence to inform best practices on risk assessment for medications used during breast feeding. Methodologies generated in this WP will be proposed to EMA for consideration to adopt into regulatory guidelines for assessment of drugs used during lactation. WP3 will collaborate with WP6 to ask EMA for an Innovation Task Force meeting and to submit our proposals for EMA Qualification Advice.

Report with Standardised procedures for biobank sample analytics

"Task 4.2: Setting up and demonstrating protocols and operating procedures for determination of concentrations of selected drugs and their metabolites in breast milk and plasma (M6-M69) (UPPS, CHUT, UOSL, UCB, Pfizer, CHUV)The objectives of the task 4.2 are: 1) to set up and validate reliable and reproducible analytical methods for determination of drugs in biological matrices; 2) to use the methods to determine concentrations of medications in plasma and breast milk samples. The analytical methods will be performed using mass spectrometry (MS) technique for small molecule drugs and the ligand-based assays, e.g., ELISA, DELFIA and/or MS method with immuno-capture for biologic drugs. The methods will be used for quantitative and qualitative analysis of test compounds in biological matrices like human plasma and breast milk. The methods shall fulfil regulatory requirements for bioanalytical method validation (FDA ""Bioanalytical Method Validation"" Guidance 2018; EMA ""Guideline on bioanalytical method validation"" 2011). The validation process of the analytical methods shall reflect the study sample analysis and cover critical aspects:1) stability and solubility properties of test compound(s); 2) dilution integrity; 3) estimation of matrices effect, i.e. plasma, breast milk; 4) selection of appropriate range of standard curve and used quality control (QC) samples for precision and accuracy; 5) selection of appropriate internal standards; 6) estimation of selectivity and specificity with regard to endogenous compounds and/or metabolites; and 7) determination and evaluation of lower limit of quantification (LLOQ).To ensure and demonstrate reproducibility of the analytical methods, repeated measurement of an analyte's concentration from study samples (incurred sample reanalysis, ISR) will be performed. If needed, metabolites of the test compound will be also quantified, using an adequate analytical method that will be developed and validated. The bioanalysis results will be used to optimise and standardise conditions for breast milk samples collection, storage, handling and analysis. The conditions may differ between test compounds. The analytical method development and validation process will be coordinated and consulted with the EFPIA partners and shared with WP3.The results of bioanalysis will be crucial to estimate pharmacokinetic (PK) parameters, compare with available PK data (literature and product label) and to perform popPK modelling. The popPK modelling will help to understand the relationship between drug treatment, patient features, external factors and drug disposition. The demographic, pathophysiological, environmental and influence will be addressed by collection of respective information from the patients. Common PK and safety assessment routines will be prepared together with the EFPIA partners. Results obtained from bioanalysis of human plasma and breast milk samples will be used for verification of a PBPK model (see WP3). The best practice for analysis and concentration determination in the breast milk samples will be proposed.Additionally, UCB will contribute prospective data from a potential lactation study, contributing toward best practices and use in validation of predictive models."

Minutes of annual general assembly meetings 2

Best practice guidance for evaluation of case reports on pregnancy and signal detection

Task 2.6: Propose a secure and trusted (safe) environment for reporting medication exposed pregnancy cases (M36-M69) (NUTH, LAREB, ENTIS, MHRA). Based on the characteristics of a ‘safe’ and trusted system defined during the stakeholder workshop in task 2.1, findings from the demo projects and remaining tasks, recommendations on how to instil and operate an environment where HCP and women can report pregnancies will be described The process for the reporting of pregnancy exposures by HCPs to the system developed in this project will be formalised, key requirement is that HCP will feel comfortable to report where label discourages use in pregnancy. The system may then be used to collect, share and analyse (using automated data mining algorithms, database flagging / counting) enhanced pregnancy pharmacovigilance data. Task 2.7: Guidelines, recommendations and training materials (M48-M69) (UNEW, ENTIS, NVS, and Pfizer) Guidelines for the generation of evidence on drug safety assessment in pregnancy and breastfeeding based on spontaneously reported pregnancies will be drafted using existing methods and experience of the demonstration projects. These will include guidance on the standards for the reporting and assessment of PV pregnancy case reports in peer review journal(s). All draft guidelines will go out for stakeholder consultation in WP6.

Annual reports on external communication results for impact assessment -5

Task 5.3: Engage HCPs, pregnant and breastfeeding women and general public and to stimulate pregnancy reporting through PV system and participation in research; (with WP2, WP6 and WP7) (M6-M69) (NUTH, ENTIS, LAREB, Synergist, UPPS, EIWH, (third parties such as EU organisation for GPs/ gynaecologist /midwives/pharmacists) Pfizer, Sanofi, NVS, AbbVie, UCB)Rationale: Based on the ethical discussions in WP7 (task 7.3) about the idea of a learning healthcare system where we have a moral duty to generate evidence on the use of medicines in pregnancy, we will translate the learnings from the ethical research into communication programs to stimulate HCPs and pregnant women awareness that they have can play an active role in increasing general knowledge about the safety of drug use during pregnancy and breastfeeding in the post-marketing phase of a drug by contributing to WP2 as well as WP4. Aim: To build awareness and stimulate actual participation from the targeted audience Method: Communications directed to relevant stakeholders will be developed using push-pull strategies and developing value propositions. A combination of very targeted communication on social media and other digital channels together with point of care material will disseminate the message and capture the audiences utilising health literacy methods and tailored messages to stimulate their participation. The campaign overarching messages will build on various awareness messages and value propositions for pregnant women and HCPs. Each exposure will be the opportunity to engage and offer participatory mechanisms. Messages and value propositions will be tested ahead and then will be assessed in terms of participatory rate and ultimately behaviours changes, partly measured through the channels we will deliver (online, apps, etc.) In the same countries as the information materials are tested, communication strategies (including through social media, promotion through pharmaceutical companies, national healthcare systems and international/national regulatory organisations) will implemented to inform the general population, pregnant women/women of reproductive age and healthcare professionals about the importance of reporting to the pregnancy pharmacovigilance system. The effects of the campaign will be measured, both in terms of increased reporting, but also in terms of increased awareness about the importance of reporting among HCPs.

Reports from Advisory Board and Ethic Report 3

Generic PBPK template for predicting drug concentration time profiles in human breast milk

Task 3.4: Development of a robust PBPK framework to predict drug concentration profiles in human breast milk (M13-M37) (KUL, GSK, BioNotus, UNIBO, CHUT, NVS, Teva, CHUV).Drug-specific clearance values for excretion into milk will be generated with the in vitro and in vivo models developed in Tasks 3.2 and 3.3, along with previously generated in vitro/in vivo data11,12,16; and eventually coming from EFPIA partners) will be used to feed drug-specific PBPK models. Based on these models, a generic PBPK template will be developed that encompasses milk excretion of drugs. The PBPK models will be developed in an industry-supported platform (e.g. Simcyp from Certara), while the utility and added value of alternative platforms will be explored. Using the results of a second set of in vitro experiments (see Task 3.2) as input data, the predictive performance of the developed PBPK modelling strategy will be thoroughly evaluated. This will be achieved by comparing PBPK-based predictions with clinical observations. In case adequate in vivo data are available (e.g. regarding systemic maternal exposure for existing drugs), a retrograde approach will be used. Possible covariates identified with population PK approaches in WP4 will be used to further improve the developed PBPK models.

Report on data sources for reported pregnancies and handling processes & survey results

Task 2.2: Catalogue structure of industry and publicly held data sources and handling processes (M1-M69) (LAREB, ENTIS, NVS, Novo Nordisk, Pfizer, Sanofi, NUTH, UKZN, UMAN, AbbVie) in collaboration with WP7. Regulators, industry and teratology information databases and clinical disease-based registries contain a mixture of prospectively reported pregnancy exposures, retrospective case reports and paternal exposures (industry pregnancy registries and PV databases, UK Epilepsy Pregnancy Registry, adverse event reporting systems, Teratology Information Service registries or databases, non-pregnancy disease registries). In addition, case reports of exposed pregnancies data are collected incidentally as secondary outcomes through various other sources or reported in the published literature (randomised controlled trials, research cohorts and case series, other). Using the WP1 literature mining tool, and through the partner and stakeholder network we will identify data sources with reports of pregnancies. We will create a meta data model (the structure of the survey) of variables to be captured in the survey and catalogue, which will be built into the ConcePTION data source catalogue (see WP7). We will survey data sources and enter into the ConcePTION data source catalogue the nature and current handling procedures of these pregnancy data and describe their characteristics.

Report and machine learning tools to integrate reprotox data with clinical data (WP2)

Individual PBPK model for predicting exposure of infants to selected drugs

Task 3.4: Development of a robust PBPK framework to predict drug concentration profiles in human breast milk (M13-M63) (KUL, BioNotus, UNIBO, CHUT, NVS, Teva, CHUV).Drug-specific clearance values for excretion into milk will be generated with the in vitro and in vivo models developed in Tasks 3.2 and 3.3, along with previously generated in vitro/in vivo data11,12,16; and eventually coming from EFPIA partners) will be used to feed drug-specific PBPK models. Based on these models, a generic PBPK template will be developed that encompasses milk excretion of drugs. The PBPK models will be developed in an industry-supported platform (e.g. Simcyp from Certara), while the utility and added value of alternative platforms will be explored. Using the results of a second set of in vitro experiments (see Task 3.2) as input data, the predictive performance of the developed PBPK modelling strategy will be thoroughly evaluated. This will be achieved by comparing PBPK-based predictions with clinical observations. In case adequate in vivo data are available (e.g. regarding systemic maternal exposure for existing drugs), a retrograde approach will be used. Possible covariates identified with population PK approaches in WP4 will be used to further improve the developed PBPK models.

Interoperability and knowledge bank access description System which allows content from the knowledge databank to be adapted in national settings

Task 5.2 Developing an EU centralised open access digital knowledge bank (M6-M69) (LAREB, Sanofi SCC, ENTIS, ORC, the Synergist, EIWH, NVS, AbbVie, UCB, Pfizer) Rationale: By creating an EU centralised digital knowledge bank providing timely and high-quality general information and summary and interpretation of scientific research in literature and of data collected (from WP1 and WP2) this task will contribute to more harmonised and reliable evidence dissemination for the general public, pregnant or breastfeeding women and HCPs. Official labelling information will also be available in the knowledge bank.Members of ENTIS already have their own systems for keeping up to date knowledge of high quality. Some centres have a national knowledge bank, and some also available on their website. A common model to share the safety information they have collected is not yet in place. At this moment each country collects and interprets the scientific data themselves. By joining forces and introducing work-sharing between the members in a network, timely, uniform and high-quality information will be available to all European countries. Objective: The aim of this task is to develop an EU centralised digital knowledge bank for up to date information of drug use before and during pregnancy and breastfeeding and the risks of untreated disease (in English) for a selection of diseases and drugs that are common in pregnancy by combining information from different sources and providing common knowledge. The knowledge bank will start with information on drugs mostly used by women 15-45 years; drugs on which most often advise has been asked for. After the start the repository can be expanded and continuously be updated. General system requirements: The information in the digital knowledge database will be publicly available. The content of the database will be available (in English) through a website and interfaces will be built so that national translations will be accessible to share with 3rd parties such as other apps and websites in the country. A prerequisite for the digital knowledge databank is that all stakeholders have confidence in the quality and reliability of the information. ENTIS will be responsible for quality control. A peer reviewed system and protocol for screening and interpretation scientific research will be developed to add or change information into the knowledge bank to ensure reliability and that the information is up to date. This task is further sub-divided into the following sub-tasks:Sub-task 5.2.1: Agree upon the functionality of the databaseAim: To define the functionalities of the database. This includes; but is not limited to indexing of information, searching information, presenting information and presenting references for the information given. Method: Designing meeting with contributors and partners developing the tool will be organised to agree on the functionality of the database. Stakeholder feedback will be organised in collaboration with WP6.Sub-task 5.2.2: Build a knowledge management database Aim: To build the knowledge bankMethod: the knowledge bank will be built by ORCION in an agile way with the possibility to change things if deemed necessary, so that the final product will fit the needs of the end-users. To ensure usability the knowledge bank will be tested in cycles by WP5 members and stakeholders, to make sure that it fits with their needs. Sub-task 5.2.3: Interconnectivity Rationale: Making Translation of information possible to local language /national adaptations of the content is important. In local settings, it is possible that the safety information will need to be accessed at other points in the healthcare system than the central EU webpage, for example in apps or as part of other websites. A system to ensure the quality and reliability of the translation will be developed.Aim: to build Application programming interfaces (API) to allow for interconnectivity with local websites an

Annual reports on external communication results for impact assessment -1

Description of the operational platform for data sharing and task management plus instructions

Report providing the details on the informed consent procedures, informed consent sheets and information sheets for demonstration studies in WP2 & 5 . IRB approval procedures and confirmation for WP2 demonstration studies and WP5 outreach

Optimised protocol for non-clinical data generation regarding drug milk excretion and breastfed infant drug exposure

Task 3.7: Non-clinical data generation methods for drug milk excretion and breastfed infant exposure (M37-M69) (UNIBO, Covance, CHUT, CHUV, KUL, Lilly, NVS, Teva, Ellegaard).Optimised protocol for conducting non-clinical in vivo studies on drug milk transfer will be proposed. The same will be done for the generic PBPK templates developed to predict drug milk excretion and infant drug exposure. Availability of these optimised protocols will support: (i) risk assessment on medication use during breast feeding; and (ii) possible identification of drug milk excretion mechanisms.

Report on information, privacy and research governance for WP1-5

Task 7.2: Definition governance framework for responsible re-use of data (M3-M12) (i~HD, UMCU, UPPS, EFCGP, EIWH, KI, GSK, JAN, SANOFI). The objective of this task is to ensure, and assure, data access providers and research users that data and samples are treated in full compliance to the GDPR (for personal data), the IMI Secondary Use Code and other codes of practice that protect the privacy of data subjects (especially EHR4CR, EMIF, i~HD and BBMRI-ERIC), that research is conducted in ways that accord with codes of conduct from ENCePP and the ethics policies of ELIXIR, as well as other relevant standards. In achieving this, the partners involved in this task will reuse these existing instruments – some of which they have themselves developed in other initiatives – and carefully combine these and fill any gaps that are relevant to the project, while including the results from task 7.1. We will describe the procedures for a common trusted data management and research ecosystem. The main elements of such trusted ecosystem, and the areas of coverage of some of the instruments we will combine and reuse. After the initial development of instruments and mapping to data access providers, this task will monitor their adoption and maintain the instruments in the light of new policies and legislation (such as national GDPR implementation laws). For instance, it will be important to consider how each EFPIA company is interpreting the grey areas of GDPR in the scope of real world data use for evidence generation. Conception will (re)-use human health/specimen data from various sources (WP1, 2, 3 & 4), that has been consented for research purposes (i.e. biobank, cohorts, some registries, reports) or was collected for routine healthcare (e.g. healthcare data, national statistic registries). The GDPR requires data privacy impact assessments prior to conducting any research on the data. In this task we will provide clear guidance documents to adhere to GDPR and provide templates for data privacy impact assessments and will provide guidance and support for DPIA locally as well as for the central data platform. It will collect and monitor the results of the DPIAS and be the reference for the local data privacy officers. This task will liaise with Ethics and Governance specialists in the Independent Scientific Advisory Board. In this task we will develop information and consent procedures and templates for biobanking. Development and implementation of information and consent procedures and templates for collection, storage, analysis of samples in different European countries and transfer of data across borders will be based on: i) the legal premises of the GDPR; ii) the National laws of participating countries; iii) The Article 29 Working Party Guidelines on consent; iv) The BBMRI-Code of Conduct; v) The Recommendation of the OECD Council of Health Data Governance (of 17 January 2017); vi) The CIOMS International Ethical Guidelines for Health-Related research involving Humans (2016) and; vii) 20 years of published research on information and consent procedures by the Uppsala partner Centre for Research Ethics & Bioethics. The purpose of sampling will be described in general terms while the processes will be described in more detail, e.g. that samples and data will be sent across borders for research that may include both academic and commercial partners; means for privacy protection; how to withdraw consent; kind of analyses to be made; linkage to other data sources; re-consent of children when they reach age of maturity; and how to access to information about projects. Templates will be formulated in the relevant language and ethics approval will be obtained by legitimate ethics committees in each country.

Reports from Advisory Board and Ethic Report 1

User requirements and meta-data model for the FAIR data catalogue from WP1&2

Report with methods and Analytical results of demonstration projects

Report describing the metadata model (variables) for data collection on pregnancy data sources, as basis for the catalogue collection of exposed pregnancies

Task 2.2: Catalogue of industry and publicly held data sources and handling processes (M1-16) (LAREB, ENTIS, NVS, Novo Nordisk, Pfizer, Sanofi, NUTH, UKZN, UMAN, AbbVie) in collaboration with WP7. Regulators, industry and teratology information databases and clinical disease-based registries contain a mixture of prospectively reported pregnancy exposures, retrospective case reports and paternal exposures (industry pregnancy registries and PV databases, UK Epilepsy Pregnancy Registry, adverse event reporting systems, Teratology Information Service registries or databases, non-pregnancy disease registries). In addition, case reports of exposed pregnancies data are collected incidentally as secondary outcomes through various other sources or reported in the published literature (randomised controlled trials, research cohorts and case series, other). Using the WP1 literature mining tool, and through the partner and stakeholder network we will identify data sources with reports of pregnancies. We will create a meta data model (the structure of the survey) of variables to be captured in the survey and catalogue, which will be built into the ConcePTION data source catalogue (see WP7). We will survey data sources and enter into the ConcePTION data source catalogue the nature and current handling procedures of these pregnancy data and describe their characteristics.

Spreadsheet containing all additional data sources for the ConcePTION Data Source Catalogue

Task 1.1: Identifying new data sources to update the ConcePTION data source catalogue and assess its functionality for use in demonstration projects (M1-M60) (ULST, Sanofi, SGUL, USWAN, NUTH, CNR-IFC, INSERM, JAN, NVS). In this task we will update and expand the information in the EMA-funded EUROmediSAFE “Inventory of data sources for evaluating the long-term risks for children” which covers perinatal and childhood outcomes, including neuro- and immuno-developmental outcomes, etc., that are linked, or can be linked, to maternal medication exposure. Expansion will include newly identified EU data sources to study a spectrum of pregnancy outcomes, perinatal, neonatal and long-term childhood outcomes (e.g. cancer), databases for medication utilisation studies, hospital inpatient prescription data, breastfeeding data, additional primary care sources (e.g. in UK), rare disease and other disease registries for maternal disease, and additional contextual information (e.g. medication coverage, reimbursement) where relevant. Non-EU data will also be considered, as available. The focus of activity for this task will be data sources potentially relevant to the Demonstration Projects (see Task 1.5). WP7 will transform the EUROmediSAFE inventory and the updates above to a FAIR data source catalogue with specific search features and quality indicators which will be designed and tested in collaboration with WP1. Further updating throughout the project will be done directly by WP1 into the catalogue database designed by WP7.

Report describing communication plan and governance

Description of basic quality management structure for biobanking and pre-analytical handling of human breastmilk specimens

Task 4.4: Developing standard documents for pre-examination processes for breast milk handling and biobanking activities (M1-M60) (BBMRI, UPPS, CHUT, UOSL, Pfizer, CHUV). Building a ‘Breast Milk Biobank Analysis Center’ requires a comprehensive quality management approach, to secure and control all operations associated with conducting clinical trials, biobanking activities, and downstream analysis procedures at multiple process levels. The partners will develop the basic structure of this quality management system from a set of applicable European and International Standards for biobanking and pre-analytical sample handling (CEN/TS 16835, ISO 20387, ISO 9001, ISO 20186 etc.) and the guideline for good clinical practice E6 (R2), ICH-GCP for the protection of donor rights and safety. SOPs from the project partners and from the literature will be reviewed to verify key processes and methods. The collection, processing steps, processing times, storage temperature, freeze-thaw-cycles and so forth, will be addressed to optimize SOPs to optimal sample quality for subsequent analytical methods. The open structure of the standardization process allows transparency to all involved or interested parties. Building and hosting a BBMRI Technical committee will allow all partners to join guided standardization activities with the aim to develop standardized documents. Regular committee meetings will be initiated and hosted and will take place via web-conferences and/or f2f project meetings. Based upon project partners outcomes, standardization activities will be carried out jointly with the partners within the BBMRI Technical committee, aiming to result in the contribution to, and the preparation of, one or more standard document(s), with the focus on the standardization of the pre-analytical and analytical management of breast milk, based on collection, processing steps, processing times, storage temperature, freeze-thaw-cycles and analytical method for defined intended use. The transformation of research findings into application/product ideas transferred to the market afterwards is also assisted by such standardization activities, as they support the dissemination and implementation of innovative knowledge. With the aim to spread the awareness concerning standardization activities of the project, information about standards and standardization will be provided, e.g. via presentations at conferences and workshops, contribution to journals and scientific publications. The results may also be published in guidelines for the handling of human breast milk. Standardization activities will be provided on the website of Uppsala Biobank.

Report describing synthesis of evidence and testing the knowledge databank and recommendations for sustainability

Annual reports on external communication results for impact assessment-4

Report describing toolbox of methodologies and approaches for WPs to engage stakeholders regarding new evidence on the use of medicines in pregnancy and lactation

Task 6.3: Methodologies and tools for stakeholder engagement and consensus building (M1 – M24) (KUL, i~HD, EMA, EFGCP, Takeda, NVS, Lilly, JAN, Teva). This task will assemble a toolbox of resources (methodologies, instruments, tools, guidelines and training materials) to enable positive and successful engagement across stakeholder groups and to support patient engagement & healthcare professional and public health consensus building, for example about communicating the strength of evidence about safety, how it has been derived, the level of confidence provided by the experimental data. This activity will primarily guide the consortium on which well-established methods may be most suitable for each of the various kinds of engagement, attitude sampling and consensus building. In collaboration with WP5, this task will advise internally on the uses of individual expert interviews, focus group discussions, Delphi study methods, online surveys, webinars and training materials. The toolbox will progressively grow tools in a prioritised way from early in the project and be complete by M24.

Report on data characterisation

Task 7.6: Data characterisation of DAPs (M1-M58) (UMCU, ARS, GSK, ULST, USWAN, CNR-IFC, FISABIO, UOSL, ULST, CHUT, UMCG, LAREB and all other data access providers (third parties or subcontractors). In this task we will start with defining the data characterisation indicators in close collaboration with WP1&2, this will include describing the population, drug use in the population, incidence rates and counts of specific events and diagnosis codes and distributions of measurements. Common scripts will be written in R for the data characterization. Data will be benchmarked externally against published data as well as between data sources. Many third parties have agreed to this early data characterization which should inform the algorithm development in WP1 and 2. A workflow to assess ‘fitness of use’ for certain purposes of a data source will be developed and agreed with WP1 &2.

Report on recommendations on generating evidence at a level considered suitable for meaningfully informing product information on drug safety in pregnancy and lactation. These will include recommendations on methods of de novo evidence generation as well

Task 6.4: Engaging with regulators on the use of new evidence in decision making (M1 – M69) (EMA, i~HD, KUL, EMA, MHRA, EIWH, NVS, Takeda, UCB, JAN, Teva). This task will identify the present-day hurdles for regulatory authority decision making on the safety and use of medicines during pregnancy and breast feeding. It will work (through workshops, round tables and focus groups) with other consortium partners, members of its advisory boards, external academics and regulatory authorities on how relevant new evidence from secondary and primary sources might best be used by regulators. WP6 will facilitate the dialog between project participants across WPs and Health Authorities on the merits and use of innovative methods developed by the project. Specifically, the aim will be to make recommendations and solicit health authority feedback on the use of these methods to provide evidence for inclusion in product label, as well as for use in other regulated activities, e.g., pharmacovigilance systems. This activity will engage with ongoing initiatives by regulators looking into the value of new evidence (including a Head of Agencies Task Force).The task will then guide the other WPs on how to present their evidence for regulatory authority review and assessment. This will include both scientific findings and novel evidence generation methods. It will act as a peer review resource on the formulation of other work package proposals for EMA Qualification Advice.As the project develops, the best 5 or 6 candidates for qualification advice in terms of impact and benefit to EU public health and the ConcePTION consortium will be agreed upon and submitted.

Reports from Advisory Board and Ethic Report 2

Submitted manuscript of a guidance document outlining lessons learned for conducting drug utilization and medication safety studies based on secondary data sources in pregnancy using the ConcePTION pipeline

Task 1.6: Prepare guidance documents and bring to external stakeholder for consultation (M22-M69): (FERR, JAN, ULST, SGUL, UOSLO, CHUT, THL, KI, USWAN, UMAN, Merck, GSK, Lilly, NVS, Pfizer). The task is to prepare guidance documents outlining standards for conducting medication safety studies in pregnancy (data and analytic standards) using secondary population-based data approaches based on the knowledge gained through demonstration projects and other WP1 tasks; to bring recommendations on core evidence elements (Task 1.2) for discussion to EMA Innovation Task Force; to validate the guidance documents through EMA qualification advice; and to publish overall guidance based on the knowledge use and gained through both WP1 and WP2 (i.e. primary vs secondary data approaches) on the application of different data and analytic approaches to study medication safety in pregnancy. Data access and data protection aspects will be provided by WP7. Stakeholder consultation on how to provide evidence on medication use during pregnancy for HCPs, patients and general public that are acceptable to all stakeholders; EMA Innovation Task Force meeting and EMA Qualification Advice will be facilitated by WP6.

Final FAIR data catalogue including negotiation services and authenticated space for simple analytics on data characterization output

Task 7.4: Creation and filling of a FAIR data source catalogue(s) (M3-M58) (BBMRI, UMCG, GSK, JAN, Sanofi, SGUL). A FAIR data source catalogue will be created with specific search features that will be defined based on user requirements. We will use standard metadata models to make data resources findable, understandable, and provide fine-grained access control for researchers (FAIR implies access ‘under well-defined conditions’). Computer-readable terms that minimally describe the data resource (e.g. an ontology term or a (bio)schema.org term) are added for a searchable index of sources. The metadata defines the resource as a whole, the data sets, formats in which the data sets are, variables and provenance. The catalogue will also contain a private negotiation service to arrange data access, and a separate private site for simple analysis of data characterisation tables, which can be used in feasibility services following authentication. The catalogue will be filled by UMCG using the WP1 and 2 data. Task 7.6: Data characterisation of DAPs (M1-M58) (UMCU, ARS, GSK, ULST, USWAN, CNR-IFC, FISABIO, UOSL, ULST, CHUT, UMCG, LAREB and all other data access providers (third parties or subcontractors). In this task we will start with defining the data characterisation indicators in close collaboration with WP1&2, this will include describing the population, drug use in the population, incidence rates and counts of specific events and diagnosis codes and distributions of measurements. Common scripts will be written in R for the data characterization. Data will be benchmarked externally against published data as well as between data sources. Many third parties have agreed to this early data characterization which should inform the algorithm development in WP1 and 2. A workflow to assess ‘fitness of use’ for certain purposes of a data source will be developed and agreed with WP1 &2.

Protocols for 5 approved demonstration studies uploaded on EU-PAS register

Task 4.3: Demonstration studies (M12-M66) (UOSL, UPPS, CHUT, CHUV)At least 5 demonstration projects measuring selected medications in breast milk and maternal blood/plasma and assessing exposure of breastfed infants will be performed, which will provide evidence for appropriate methodology for different chemical classes (see example demonstration project description in Appendix (after Section 5). The same drugs will be used in WP 3 for development and validation of non-clinical models. Drug selection will be based on several feasibility factors and targeted disease areas according to the following criteria: Available human data, Diversity of physicochemical properties; Societal impact of the data generation (e.g., prevalence of the disease in women of child-bearing age, seriousness of the condition); Ability to assess PK; Existing networks to raise awareness for patients to participate in research and for developing ethical standards via empirical qualitative studies, i.e., patient groups; Patient compliance, e.g., epilepsy prioritised over bipolar disorder; Feasibility to recruit a sufficient sample size for analysis at appropriate population levels for popPK.Principal investigators will be distributed over CHUV, CHUT, UOSL and UPPS. Prospective samples will be collected from clinical care or research across the consortium (in collaboration with WP2 and 5). Participants will be recruited through partners' networks and pregnancy exposure registries as available by the partners in the project. Two disease areas where large networks are already established and that have been identified as fulfilling the criteria above are rheumatoid arthritis and epilepsy. Protocols for human sampling will be made based on established formats of the principal investigators, EFPIA partners, Codes of Conduct and access policies of BBMRI-ERIC. Consent forms will be harmonised in collaboration with task 7.2. Patients’ PK profiles in plasma and breast milk will be compared. The results will be analysed by popPK modelling to identify possible covariates explaining variability in drug concentrations in breast milk. These covariates will be implemented in the development and validation of PBPK models (WP 3, Task 3.6).Based on the experiences with the demonstration studies, an outreach program will be developed that will facilitate future breastmilk drug transfer studies and will include outreach to patients and clinicians, including information on how to participate in research. Social media specifically targeted to young women will be used for broad outreach, in collaboration with WP 5. Information and communication resources for carrying out this task will include BBMR whose information network involves 19 EU-member countries. Special sessions on breast milk biobanking and Conception will be arranged at the yearly European and Global Biobank weeks.

Common data model and data elements required for retrospective case reports and primary prospective data collection on exposure and outcomes during pregnancy

Task 2.4: Develop a common data model and analytical methods to enable analysis of existing surveillance data from different sources and centres across Europe (M6-M69) (LAREB, NVS, NUTH, UKZN, ENTIS, EMA, Teva, Novo, Pfizer, BMS. In collaboration with WP7: UMCU, ARS). In collaboration with WP7, will create a common data model for a standardised method for data analysis of pregnancy reports (passive and active surveillance) and novel methods for qualitative and quantitative signal detection and risk estimation to allow for distributed analysis (data stay local, but results are pooled) of reported medication exposed pregnancy cases from different existing data sources (e.g. retrospective, registries, prospective data collection, see data sources specified in task 2.2). The model will be used to convert existing data towards, as well as to analyse these data (including publicly and privately maintained PV systems) and risk estimation techniques (see demonstration projects) using qualitative review, disproportionality analyses, machine learning and epidemiological methods.

Report explaining the regulatory procedures, their scientific requirements, priorities and decision-making pathways regarding the use of medicines in pregnancy and lactation

Task 6.2: Promote a common understanding of regulatory authorities and their use of evidence (M1 – M18) (i~HD, KUL, EMA, MHRA, NVS, Lilly, Takeda, UCB, JAN, Teva). This task will help all consortium partners and external stakeholders to share a common understanding of the scope, roles and responsibilities of different regulatory agencies at European and national levels, how they work, their statutory powers and in particular their decision-making pathways when assessing new evidence on the use of medicines in pregnancy and lactation. A review and synthesis of regulatory publications and relevant EFPIA partner internal guidelines, supplemented by stakeholder consultations (e.g. interviews, surveys, current FDA and EMA work on patient-focused drug development) will be undertaken with the goal to ensure consortium partners, advisory board members and external stakeholders have a common understanding of the current regulatory frameworks that govern evidence assessment to understand impact of medicines used by pregnant and lactating women.This task will establish glossaries and other explanatory tools for internal and external use and shared with the public. The glossary will specify a standardised nomenclature and terminologies related to use of medicines during pregnancy and lactation that will be used consistently within the project for scientific communication. In collaboration with maternal/patient experts the glossary will include lay terms that can also be used when developing dissemination materials intended for the public.

Report on data access models and rules

Task 7.1: Defining the rules and collaboration models for data reuse (M1-M12) (UMCU, SGUL, KI, i~HD, EIWH, GSK)This task will inquire from relevant data sources identified by WP1 and 2 the access rules, in terms of data sharing policies (privacy and ethics) and governance rules, as well as possibilities to speed this up (public health access vs. research access). In addition, we will inquire about recognition rules. Both monetary and non-monetary recognition examples will be collected and compiled into a set of reward models that will be offered during the project. Data will be collected by interview. Based on collected data, we will convene a focus group with different types and geographies of data access providers to further define the access and reward models. A readable summary of these rules will be added to each data source in the ConcePTION FAIR data catalogue (Task 7.3).

Report on the methods and results of the communication campaign to stimulate reporting and participation in studies/registries and publication of analysis of communication methods

Task 5.4 Develop a training programme for continuous education for HCPs (M12-M48) (ENTIS, UOSL, UMCU, Elevate and WP leads, Sanofi)Rationale: Studies show that HCP have challenges to explain possible risks of drug use/exposure during pregnancy and lactation. Aim: To train HCPs about teratology, and long-term outcome and methods of evidence generation in Conception and how they can translate this in effective messages for women and their families. Method: With content input from WP1, 2, 3, 4, 7, this task will develop a e-learning training programme which can be used for continuous education of HCPs in English language. We will also apply for EU wide continuous medical accreditation. The focus will be on the basic principles of teratology, knowing where to find the right information and how to interpret it for a patient centred and evidence-based decision. Case discussions regarding the teratological risk assessment following an inadvertent exposure during pregnancy or approach to a pregnant patient in whom pharmacotherapy is necessary or the management of pharmacotherapy in a breastfeeding mother.

Annual reports on external communication results for impact assessment -6

Task 5.3: Engage HCPs, pregnant and breastfeeding women and general public and to stimulate pregnancy reporting through PV system and participation in research; (with WP2, WP6 and WP7) (M6-M69) (NUTH, ENTIS, LAREB, Synergist, UPPS, EIWH, (third parties such as EU organisation for GPs/ gynaecologist /midwives/pharmacists) Pfizer, Sanofi, NVS, AbbVie, UCB)Rationale: Based on the ethical discussions in WP7 (task 7.3) about the idea of a learning healthcare system where we have a moral duty to generate evidence on the use of medicines in pregnancy, we will translate the learnings from the ethical research into communication programs to stimulate HCPs and pregnant women awareness that they have can play an active role in increasing general knowledge about the safety of drug use during pregnancy and breastfeeding in the post-marketing phase of a drug by contributing to WP2 as well as WP4. Aim: To build awareness and stimulate actual participation from the targeted audience Method: Communications directed to relevant stakeholders will be developed using push-pull strategies and developing value propositions. A combination of very targeted communication on social media and other digital channels together with point of care material will disseminate the message and capture the audiences utilising health literacy methods and tailored messages to stimulate their participation. The campaign overarching messages will build on various awareness messages and value propositions for pregnant women and HCPs. Each exposure will be the opportunity to engage and offer participatory mechanisms. Messages and value propositions will be tested ahead and then will be assessed in terms of participatory rate and ultimately behaviours changes, partly measured through the channels we will deliver (online, apps, etc.) In the same countries as the information materials are tested, communication strategies (including through social media, promotion through pharmaceutical companies, national healthcare systems and international/national regulatory organisations) will implemented to inform the general population, pregnant women/women of reproductive age and healthcare professionals about the importance of reporting to the pregnancy pharmacovigilance system. The effects of the campaign will be measured, both in terms of increased reporting, but also in terms of increased awareness about the importance of reporting among HCPs.

Report providing the details on the informed consent procedures, informed consent sheets and information sheets for demonstration studies in WP4. IRB approval procedures and confirmation for WP4 demonstration studies.

Submitted manuscript of a guidance document outlining standards for conducting medication utilisation studies in pregnant women (data collection and analytic standards) for established and newly marketed products

Task 1.4: Establishing medication utilisation for newly approved products (M12-M69) (USWAN, THL, NVS, SGUL, UMCG, FISABIO, Novo Nordisk, Merck, BMS, GSK, Lilly, Pfizer).For newly approved medications, the utilisation pattern among women of childbearing age and pregnant women is important to inform feasibility of safety studies and safety measures, but usually unknown. This task is to establish acceptable methodology in data source identification and data analysis e.g. assessing exposure definition by all stakeholders. NVS, Merck KGaA, BMS and GSK will each share the results of future ongoing studies for newly approved medications. NVS will lead the alignment on exposure definition. This task will closely collaborate with WP2 & 7 in order to establish the best strategy and innovative methodologies to study new products in population databases, which will contribute to the guideline recommendations in Task 1.6.

Landscape analysis & costs analysis

Task 8.7: Sustainability plan and roadshow (M1-M60) (TTOP, UMCU, SYNERGIST, EIWH) A detailed sustainability plan will be created (including a business plan), where the exact plans for the Conception ecosystem and how this will be continued after the end of the project will be detailed. Dedicated sustainability plans will be developed for the community (WP6), the tools and infrastructure (biobank (WP4), the drug information databank (WP5), the data source catalogue (WP7) and the evidence generation workflows and templates. In order to be able to develop the business plan we will make a baseline assessment of the current costs pregnancy registries to comply with regulatory standards. The consortium will employ the following proven phased approach to implement a successful sustainability strategy: (1) Mapping: an environmental assessment will be made, including identification and refinement of the needs of end-users, inventory of possible strategic partners, assessment of organisational needs and investigation of best practices amongst comparable initiatives (2) brainstorming and business case development (3) validating: Together with a selection of key stakeholders and possible funders/payers, the business cases will be validated (including cost-effectiveness modelling). (4) planning: Positive business cases will be further detailed in a sustainability/business plan (5) roadshow: Key project representatives, policy experts will make a roadshow and meet with key funders/decision makers/payers to realise seed funding / initial revenue. The success of a sustainable ecosystem will critically depend upon the multi-stakeholder alignment and support we establish, especially via WP6, in financing, contributing data and new evidence, and in valuing and using this evidence to improve the confident and safe treatment of women. We will also leverage partner expertise in establishing and sustaining new not for profit ecosystems and in delivering scalable and interoperable data and information infrastructures, for example to sustain the knowledge bank. More details provided in section 2.

Updated Data Management Plan

Report confirming all relevant documents for using, producing or collecting human cells or tissues(e.g.ethics approval, import licence, accreditation/designation/authorisation/licensing) prior to start of research raising ethical issues are on file

List with names and expertise of expert delegates group for BBMRI Technical committee

Recommendations for a sustainable information production, dissemination and engagement ecosystem to healthcare systems and women regarding new evidence generation methods to inform on the risks and benefits related to use of medicines in pregnancy and lac

Description of work Task 6.1: Understand stakeholder needs and perceptions and align with project outcomes (M1 – M12) (i~HD, EMA, MHRA, EFGCP, Synergist, KUL, EIWH, FERR, NVS, Takeda, JAN). In this task WP6 will act as a facilitator and coordinator, working with Work Package leaders to gather insights from key stakeholders (regulatory, HCPs, women and patients, maternal health foundations, charities, etc.) on their needs and perceptions, to help achieve project goals and deliver maximum possible value and impact to target audiences. The outputs from task 6.1 will feed into all other work packages.The first step is to determine what input is needed from stakeholders. A stakeholder landscape analysis will be conducted as a resource to the consortium. A variety of tools will be used to gather input from stakeholders, including literature reviews, surveys, interviews, focus groups, and digital tools (e.g. social media outreach, digital listening tools), and to build ongoing dialogue with stakeholders. This task will seek to understand current perceptions on medication use during pregnancy and breastfeeding, barriers to confidently utilising medicines during pregnancy and breastfeeding, the guidance currently available to mothers and professionals, their unmet needs and the potential contributions of new project evidence. The investigation will also elucidate barriers to research participation on the part of mothers.This task will help the WPs to design outputs that align to stakeholder needs. A roadmap of project outputs aligned to stakeholder needs and recommended stakeholder interactions will be provided. It will identify appropriate timeframes to iteratively re-engage with stakeholders at the consortium level to reassess their needs, and to help avoid duplication across the WPs. Any needs identified that are beyond the scope of project will be curated and communicated to other funding bodies as possible future call topics (e.g.FP9, charities).Task 6.2: Promote a common understanding of regulatory authorities and their use of evidence (M1 – M24) (i~HD, KUL, EMA, MHRA, NVS, Lilly, Takeda, UCB, JAN, Teva). This task will help all consortium partners and external stakeholders to share a common understanding of the scope, roles and responsibilities of different regulatory agencies at European and national levels, how they work, their statutory powers and in particular their decision-making pathways when assessing new evidence on the use of medicines in pregnancy and lactation. A review and synthesis of regulatory publications and relevant EFPIA partner internal guidelines, supplemented by stakeholder consultations (e.g. interviews, surveys, current FDA and EMA work on patient-focused drug development) will be undertaken with the goal to ensure consortium partners, advisory board members and external stakeholders have a common understanding of the current regulatory frameworks that govern evidence assessment to understand impact of medicines used by pregnant and lactating women.This task will establish glossaries and other explanatory tools for internal and external use and shared with the public. The glossary will specify a standardised nomenclature and terminologies related to use of medicines during pregnancy and lactation that will be used consistently within the project for scientific communication. In collaboration with maternal/patient experts the glossary will include lay terms that can also be used when developing dissemination materials intended for the public. Task 6.3: Methodologies and tools for stakeholder engagement and consensus building (M1 – M24) (KUL, i~HD, EMA, EFGCP, Takeda, NVS, Lilly, JAN, Teva). This task will assemble a toolbox of resources (methodologies, instruments, tools, guidelines and training materials) to enable positive and successful engagement across stakeholder groups and to support patient engagement & healthcare professional and public health consensus building, for example ab

Sustainability plan

Task 8.7: Sustainability plan and roadshow (M1-M69) (TTOP, UMCU, SYNERGIST, EIWH) A detailed sustainability plan will be created (including a business plan), where the exact plans for the Conception ecosystem and how this will be continued after the end of the project will be detailed. Dedicated sustainability plans will be developed for the community (WP6), the tools and infrastructure (biobank (WP4), the drug information databank (WP5), the data source catalogue (WP7) and the evidence generation workflows and templates. In order to be able to develop the business plan we will make a baseline assessment of the current costs pregnancy registries to comply with regulatory standards. The consortium will employ the following proven phased approach to implement a successful sustainability strategy: (1) Mapping: an environmental assessment will be made, including identification and refinement of the needs of end-users, inventory of possible strategic partners, assessment of organisational needs and investigation of best practices amongst comparable initiatives (2) brainstorming and business case development (3) validating: Together with a selection of key stakeholders and possible funders/payers, the business cases will be validated (including cost-effectiveness modelling). (4) planning: Positive business cases will be further detailed in a sustainability/business plan (5) roadshow: Key project representatives, policy experts will make a roadshow and meet with key funders/decision makers/payers to realise seed funding / initial revenue. The success of a sustainable ecosystem will critically depend upon the multi-stakeholder alignment and support we establish, especially via WP6, in financing, contributing data and new evidence, and in valuing and using this evidence to improve the confident and safe treatment of women. We will also leverage partner expertise in establishing and sustaining new not for profit ecosystems and in delivering scalable and interoperable data and information infrastructures, for example to sustain the knowledge bank. More details provided in section 2.

Report on E-learning training programme and accreditation plus sustainability plan

Report on characterisation In vitro human/animal mammary epithelial cell culture models, including comparison between in vitro models

Task 3.2: Development of an improved in vitro model to identify parameters determining the rate and extent of blood-milk excretion (M4-M48) (KUL, NVS, UNIBO, Bionotus, Covance). The aim is to develop and characterise an improved in vitro model for drug passage from maternal blood to human breast milk. The model will be based on cultured human mammary epithelial cells11,12. In parallel, a mammary epithelial cell model corresponding to the species selected for Task 3.3 will be established. Primary cultures of mammary epithelial cells, grown as monolayers or on inserts, will be utilised to determine transfer rate data for the model drugs across mammary epithelial cells13. The literature search performed in Task 3.1 will be used to inform the development of the in vitro models. At least 10 model compounds selected in Task 3.1 will be used in a first wave of in vitro experiments. High-throughput and sensitive LC-MSMS methods will be developed and validated according to EMA/FDA guidelines and EBF recommendations. These methods will be applied for accurate and precise measurement of drugs in in vitro samples.As a secondary objective, the data obtained in Task 3.2 will be compared to data generated on existing models of trans-epithelial transport (e.g., Caco-2 / MDCK / PAMPA) to investigate whether those existing models could predict the mammary cell culture data and could be used as replacement. This would allow utilisation of a large amount of existing data from easy-to-access assays that are commonly found in discovery programs across industry.

Integrated mother-infant PBPK models verified against human lactation data

Task 3.5: Neonatal physiological factors determining drug exposure in breastfed infants based on PBPK modelling (M4-M63) (KUL, UNIBO, Bionotus, NVS, CHUV).A systematic literature search will be performed to collect all available information on (i) gastro-Intestinal maturation, with the specific emphasis on the settings during breast feeding that are different when compared to formula feeding; (ii) milk composition; (iii) physicochemical properties of drugs; (iv) ontogeny of relevant drug elimination pathways (renal/hepatic); and (v) bioavailability14. The available PBPK models for systemic drug exposure in term neonates after oral administration17,18 will be explored on their performance for the selected model compounds. For feasibility reasons (i.e. due to very sparse PK and ontogeny data in preterm neonates), development and validation of PBPK models for preterm neonates will not be pursued. However, successful validation of PBPK models for term neonates in the present project may serve as relevant starting point and provide useful expertise for the development of PBPK models in preterm neonates in a follow-up project.Role and expertise of public partners: (i) selection of neonatal physiological parameters to be implemented in PBPK models for drug exposure in term neonates [ALL]. In addition, as K. Allegaert is the co-chair for clinical pharmacology in the International Neonatal Consortium (INC), expertise present among INC members in the field of neonatal physiology will be implemented in these neonatal PBPK models;for neonatal drug exposure [ALL]; (ii) PBPK model development [KUL, Bionotus]; (iii) input from WP4 regarding clinical PK observations in term infants (CHUV); (iv) implementation of ontogeny profiles that are currently being compiled as part of a HESI working group on neonatal models (KU Leuven in collaboration with others).Role of EFPIA partners: Expertise in general and reproductive toxicology, physiologically-based modelling and simulation, capabilities to develop animal lactation models.

Report with planned training programmes, learning goals, target audience, teachers

Interim Report on ethical issues

Task 7.3: Ethical issues (M1-24) (UMCU, EFGCP, EIWH, UPPS, GSK, Sanofi). The approach of ConcePTION to collect data on safety of medicines during pregnancy and breastfeeding is similar to what is increasingly being called a Learning Healthcare System (LHS). In an LHS, care and research are aligned to accelerate research and outcomes for patients and to overcome current problems, such as low inclusion rates and complex informed consent procedures. Taking an LHS approach to knowledge generation in the field of pregnancy and breastfeeding may broaden the opportunities to strengthen the evidence base, among others by learning from routinely collected data. However, applying an LHS approach to the field of pregnancy and breastfeeding comes with at least three open ethical issues:1.How should we weigh the risks of the current status quo (where women hardly participate in research and we do not learn) versus the benefits and risks of participating in a system where pregnant and breastfeeding women will continuously be studied to improve the evidence base? Currently, pregnant and breastfeeding women are typically excluded from research for reasons of risks to the foetus/child and potential liability. At the same time, the practice of prescription of off-label medication exposes pregnant and breastfeeding women and their children to risks without learning for future patients;2.Is there a moral duty around continuous learning in healthcare for pregnant and breastfeeding women and the healthcare professionals involved in their care? If so, how could such a moral duty be implemented in practice? If care and research become integrated in drug use in pregnancy and breastfeeding, it will be virtually impossible to escape from this learning environment. Ethical evaluation of a moral duty to participate in such a system is essential when regular care becomes inherently intertwined with learning components; and3.What are the features of a responsible and sustainable LHS for pregnant and breastfeeding women? A radical turn to continuous learning from routinely collected data in the field of pregnancy and breastfeeding also requires as set of ethical criteria to render this learning environment responsible and sustainable. At least ethical criteria of review, informed consent, fair inclusion and benefit-sharing need rethinking in light of an LHS in this field; To address these questions, we will take an approach in which the stakeholder’s perspectives as well as ethical theory on principles such as responsibility, solidarity, equity and fairness will be translated to the context of the project. We will use the method of Reflective Equilibrium. Originally, the Reflective Equilibrium has its roots in the ideas of the political philosopher John Rawls. We will use a version of this method that has been developed by members of the project team and the Department of Medical Humanities of the Julius Centre (Van Delden and Van Thiel): the normative empirical reflective equilibrium. It has proven to be successful in giving guidance to ethical thinking in practical contexts. The aim of the Reflective Equilibrium is to produce coherence between empirical, conceptual and normative data. The empirical and conceptual elements will be brought into Reflective Equilibrium in order to be able to develop a framework for fair inclusion of pregnant women in a Learning Healthcare System. To answer the empirical part of the questions we will conduct systematic literature studies and conduct qualitative research (structured interviews) with relevant stakeholders. Maximum variation in context, experience, and views are essential in order to reach saturation in qualitative research. Therefore, we will interview the following group of stakeholders which will be drawn from the hospital/catchment area: a) Sick pregnant women pre-existing (e.g. depression) + new diseases (pre-eclampsia); b) Fertile sick women who want to become pregnant; c) Healthy pregnant women;

Test report of FAIR data catalogue 1st

Data Management Plan

Task 8.3: Development and updating of data management plan (M1-M60) (UMCU, i~HD, BBMRI)In order to ensure the implementation of FAIR principles on all levels, ACRONYM will develop and further update a data management plan (DMP; in collaboration with WP7). A DMP describes the data management life cycle for all data sets that will be collected, processed or generated by the research project. ACRONYM’s DMP will detail: The handling of research data during and after the end of the project; What data will be collected, processed and/or generated; Which methodology and standards will be applied; Whether data will be shared/made open access, accessible for verification and re-use; How data will be curated and preserved.

Final Report on ethical issues

Collaborative website (intranet)

Task 8.5: Website, internal document repository and social media (M1-M60) (UMCU)Implementing and maintaining the project infrastructure and the collaborative website (public and closed) as a platform for secured internal information exchange and project documents archive. The public website will include items such as general project information, news and newsletters, events and event outputs, tool information and the key results of the project. The website needs to be a functional, user friendly website. A social media strategy will be developed with WP5 (focus on Twitter and LinkedIn), aiming to promote the project image, inform stakeholders and the general public and to share key results of the project. It will also reinforce the communication activities as described in the communication.The social media strategy will include measurable objectives. The social media strategy will be included in the communication plan and social media activities will be aligned with information on the project’s public website.

Public website and social media plan

Task 8.5: Website, internal document repository and social media (M1-M60) (UU, UMCU)Implementing and maintaining the project infrastructure and the collaborative website (public and closed) as a platform for secured internal information exchange and project documents archive. A communications manager will lead the development and operational implementation of communications strategy and plan, with the aim to launch and maintain channels (website, newsletter and Twitter), build audiences and disseminate project activities & results to the wider stakeholder community. This includes developing social media strategy, monitoring and reporting KPIs for all channels, liaison with WP leads to ensure timely communication of results, and task 5.3 to ensure communications activities are aligned in terms of project overall messaging, visual identity, and timing. A communications strategy and plan will be developed, listing project overall communication objectives, audiences, key messages, tools and tactics.

Wiki page with description of tools and GITHUB repository 1st

Task 7.8: Creation & posting of double coded scripts (M12-M48) (UMCU, ARS, USWAN)In this task we will provide a service to double code WP1 study-specific scripts in R, and to document, version and store them. Scripts will be parameterised and documented for reuse. Compatibility with the infrastructure developed by the EHDEN Project will be sought.

Wiki page with description of tools and GITHUB repository 2nd

Task 7.8: Creation & posting of double coded scripts (M12-M58) (UMCU, ARS, USWAN)In this task we will provide a service to double code WP1 study-specific scripts in R, and to document, version and store them. Scripts will be parameterised and documented for reuse. Compatibility with the infrastructure developed by the EHDEN Project will be sought.

Veröffentlichungen

Infant exposure to Fluvoxamine through placenta and human milk: a case series - A contribution from the ConcePTION project

Autoren: Anaëlle Monfort, Evelina Cardoso, Chin B Eap, Céline J Fischer Fumeaux, Myriam Bickle Graz, Mathilde Morisod Harari, Etienne Weisskopf, Peggy Gandia, Karel Allegaert, Hedvig Nordeng, Jean-Michel Hascoët, Olivier Claris, Manuella Epiney, Chantal Csajka, Monia Guidi, Ema Ferreira, Alice Panchaud
Veröffentlicht in: Frontiers in Psychiatry, Ausgabe 14, 2023, ISSN 1664-0640
Herausgeber: Frontiers Research Foundation
DOI: 10.3389/fpsyt.2023.1167870

Development and Characterization of a Human Mammary Epithelial Cell Culture Model for the Blood–Milk Barrier—A Contribution from the ConcePTION Project

Autoren: Debora La Mantia, Nina Nauwelaerts, Chiara Bernardini, Augusta Zannoni, Roberta Salaroli, Qi Lin, Isabelle Huys, Pieter Annaert, Monica Forni
Veröffentlicht in: International Journal of Molecular Sciences, Ausgabe 25, 2024, Seite(n) 11454, ISSN 1422-0067
Herausgeber: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/ijms252111454

From Inception to ConcePTION: Genesis of a Network to Support Better Monitoring and Communication of Medication Safety During Pregnancy and Breastfeeding

Autoren: Nicolas H. Thurin,Romin Pajouheshnia,Giuseppe Roberto,Caitlin Dodd,Giulia Hyeraci,Claudia Bartolini,Olga Paoletti,Hedvig Nordeng,Helle Wallach-Kildemoes,Vera Ehrenstein,Elena Dudukina,Thomas MacDonald,Giorgia De Paoli,Maria Loane,Christine Damase-Michel,Anna-Belle Beau,Cécile Droz-Perroteau,Régis Lassalle,Jorieke Bergman,Karin Swart,Tania Schink,Clara Cavero-Carbonell,Laia Barrachina-Bonet,Ainho
Veröffentlicht in: Clinical Pharmacology & Therapeutics, 2021, ISSN 0000-0000
Herausgeber: Wiley
DOI: 10.1002/cpt.2476

Where are the data linking infant outcomes, breastfeeding and medicine exposure? A systematic scoping review

Autoren: Jordan S, Komninou S, Lopez Leon S
Veröffentlicht in: PLOS ONE, 2023, ISSN 1932-6203
Herausgeber: Public Library of Science
DOI: 10.1371/journal.pone.0284128

Improving data harmonization in pregnancy safety studies: Demonstrating the feasibility of standardized data analysis of pregnancy reports–A contribution from the conception project

Autoren: Ursula Winterfeld, Guillaume Favre, Jonathan Luke Richardson, Alan Moore, Yvonne Geissbühler, Valentine Jehl, Alison Oliver, Svetlana Shechtman, Orna Diav-Citrin, Maya Berlin, Tal De Haan, David Baud, Alice Panchaud, Anil Mor, Meritxell Sabido, Sabrina de Souza, Christina Chambers, Eugène P van Puijenbroek, Laura M Yates, François R Girardin, Michael Stellfeld
Veröffentlicht in: Journal of Clinical and Experimental Reproductive Medicine, Ausgabe 2, 2025, Seite(n) 6-12, ISSN 3067-7904
Herausgeber: Probiologists Limited
DOI: 10.46439/reproductivemed.2.007

Delphi Method Consensus on Statistical Analysis and Reporting Recommendations for Single-Arm Pregnancy Medication Safety Studies Investigating Pregnancy, Birth and Neonatal Health Outcomes: A Contribution from IMI-ConcePTION

Autoren: Jonathan L. Richardson, Alan Moore, Michael Stellfeld, Yvonne Geissbühler, Ursula Winterfeld, Guillaume Favre, Christina Chambers, Evelin Beck, Marlies Onken, Katarina Dathe, Michael Ceulemans, Orna Diav-Citrin, Svetlana Shechtman, Alison M. Oliver, Kenneth K. Hodson, Dee-Dee Shiller, Amalia Alexe, Eugène P. van Puijenbroek, David J. Lewis, Laura M. Yates
Veröffentlicht in: Drug Safety, 2025, ISSN 0114-5916
Herausgeber: Adis International Ltd.
DOI: 10.1007/s40264-025-01521-0

Families need support to reduce the risk of adverse drug reactions from breastfeeding

Autoren: Sue Jordan, Emyr Jones, Sophia Komninou, Maria Loane, Christine Damase-Michel
Veröffentlicht in: The Pharmaceutical Journal, 2022, ISSN 0031-6873
Herausgeber: Pharmaceutical Society of Great Britain

Clopidogrel transfer into human milk: case series – a contribution from the ConcePTION project

Autoren: Martje Van Neste, Nina Nauwelaerts, Raf Mols, Kaytlin Krutsch, Michael Ceulemans, Anneke Passier, Anne Smits, Pieter Annaert, Karel Allegaert
Veröffentlicht in: Frontiers in Pharmacology, Ausgabe 16, 2025, ISSN 1663-9812
Herausgeber: Frontiers Media S.A.
DOI: 10.3389/fphar.2025.1499243

Maternal drugs and breastfeeding: risk assessment from pharmacokinetics to safety evidence - A contribution from the ConcePTION project

Autoren: Evelina Cardoso, Anaëlle Monfort, Ema Ferreira, Hedvig Nordeng, Ursula Winterfeld, Karel Allegaert, Peggy Gandia, Monia Guidi, Alice Panchaud
Veröffentlicht in: Therapie, Ausgabe 78(2), 2023, Seite(n) 149-156, ISSN 0040-5957
Herausgeber: John Libbey & Co. Ltd.
DOI: 10.1016/j.therap.2023.01.008

Drug Utilization Studies in Pregnant Women for Newly Licensed Medicinal Products: A Contribution from IMI ConcePTION

Autoren: Sandra Lopez Leon, Anja Geldhof, Julie Scotto, Keele Wurst, Meritxell Sabidó, Jingping Mo, Ditte Molgaard-Nielsen, Jorieke EH Bergman, Xuan Anh Phi, Sue Jordan
Veröffentlicht in: Journal of Pregnancy, 2024, Seite(n) 1-13, ISSN 2090-2727
Herausgeber: Hindawi Publishing Corporation
DOI: 10.1155/2024/8862801

Transfer of cetirizine/levocetirizine into human breast milk and estimation of drug exposure to infants through breastfeeding: A human lactation study from the ConcePTION project

Autoren: Hedvig Nordeng; Christine Wegler; Annika Lindqvist Erik Melander, Mikaela Magnusson, Peggy Gandia, Alice Panchaud, Pawel Baranczewski and Olav Spigset
Veröffentlicht in: Basic & clinical pharmacology & toxicology, Ausgabe 134(1), 2023, Seite(n) 153-164, ISSN 1742-7843
Herausgeber: Wiley-Blackwell
DOI: 10.1111/bcpt.13948

Stimulating solidarity to improve knowledge on medications used during pregnancy

Autoren: Marieke Hollestelle, Rieke van der Graaf, Miriam Sturkenboom and Hans van Delden
Veröffentlicht in: BMC Medical Ethics, Ausgabe 24(1):44, 2023, ISSN 1472-6939
Herausgeber: BioMed Central
DOI: 10.1186/s12910-023-00924-x

Simple and rapid quantification of cetirizine, venlafaxine, and O-desmethylvenlafaxine in human breast milk, and metformin in human milk and plasma with UHPLC-MS/MS

Autoren: Christine Wegler, Aljona Saleh, Annika Lindqvist, Hedvig Nordeng, John Smeraglia, Pawel Baranczewski
Veröffentlicht in: Journal of Chromatography B, 2022, ISSN 0000-0000
Herausgeber: Elsevier B.V
DOI: 10.1016/j.jchromb.2022.123340

Improving data collection in pregnancy safety studies: Towards standardisation of data elements in pregnancy reports from public and private partners, a contribution from the ConcePTION project

Autoren: Favre G., Richardson J.L., Moore A., Geissbühler Y., Jehl V., Oliver A., Shechtman S., Diav-Citrin O., Berlin M., De Haan T., Baud D, Panchaud A, Mor A., Sabidó M., de Souza S., Chambers C., van Rijt-Weetink, Y.R.J., van Puijenbroek E.P., Yates L.M., Stellfeld M., Winterfeld U
Veröffentlicht in: Drug Safety, Ausgabe 47(3), 2023, Seite(n) 227-236, ISSN 0114-5916
Herausgeber: Adis International Ltd.
DOI: 10.1007/s40264-023-01384-3

Very low monomethyl fumarate exposure via human milk: a case report—a contribution from the ConcePTION project

Autoren: Martje Van Neste, Nina Nauwelaerts, Michael Ceulemans, Benedikte Cuppers, Pieter Annaert, Anne Smits, Karel Allegaert
Veröffentlicht in: Frontiers in Public Health, Ausgabe 12, 2024, ISSN 2296-2565
Herausgeber: Frontiers Media S.A.
DOI: 10.3389/fpubh.2024.1393752

Safety of medicines during breastfeeding – from case report to modeling: a contribution from the ConcePTION project

Autoren: Evelina Cardoso, Monia Guidi, Nina Nauwelaerts, Hedvig Nordeng, Marie Teil, Karel Allegaert, Anne Smits, Peggy Gandia, Andrea Edginton, Shinya Ito, Pieter Anaert, Alice Panchaud
Veröffentlicht in: Expert Opinion on Drug Metabolism & Toxicology, 2023, Seite(n) 269-283, ISSN 1742-5255
Herausgeber: Ashley Publications Ltd.
DOI: 10.1080/17425255.2023.2221847

Pragmatic and contextualized methods selection for safety assessment of infant systemic exposure through human milk: the Milk4baby decision tree approach - a contribution from the concePTION project

Autoren: Anaëlle Monfort, Julia Macente, Martje Van Neste, Miao-Chan Huang, Nina Nauwelaerts, Getahun Befirdu Abza, Ursula Winterfeld, Anne Smits, Karel Allegaert, Pieter Annaert, Monia Guidi, Alice Panchaud
Veröffentlicht in: Frontiers in Pharmacology, Ausgabe 16, 2025, ISSN 1663-9812
Herausgeber: Frontiers Media S.A.
DOI: 10.3389/fphar.2025.1602018

Identifying multiple sclerosis in women of childbearing age in six European countries: a contribution from the ConcePTION project

Autoren: Marie Beslay, Yvonne Geissbühler, Anna-Belle Beau, Davide Messina, Justine Benevent, Elisa Ballardini, Laia Barrachina-Bonet, Clara Cavero-Carbonell, Alex Coldea, Laura García-Villodre, Anja Geldhof, Rosa Gini, Kerstin Hellwig, Sue Jordan, Maarit K. Leinonen, Sandra Lopez-Leon, Marco Manfrini, Visa Martikainen, Vera R. Mitter, Amanda J. Neville, Hedvig Nordeng, Aurora Puccini, Sandra Vukusic, Jo
Veröffentlicht in: European Journal of Epidemiology, Ausgabe 40, 2025, Seite(n) 891-904, ISSN 0393-2990
Herausgeber: Kluwer Academic Publishers
DOI: 10.1007/s10654-025-01264-3

An inventory of European data sources to support pharmacoepidemiologic research on neurodevelopmental outcomes in children following medication exposure in pregnancy: A contribution from the ConcePTION project

Autoren: Joanne Given, Rebecca L Bromley, Florence Coste, Sandra Lopez, Maria Loane
Veröffentlicht in: PLOS ONE, 2022, ISSN 1932-6203
Herausgeber: Public Library of Science
DOI: 10.1371/journal.pone.0275979

Determining the exposure of maternal medicines through breastfeeding: the UmbrelLACT study protocol - A contribution from the ConcePTION project

Autoren: Martje Van Neste, Nina Nauwelaerts, Michael Ceulemans, Kristel Van Calsteren, An Eerdekens, Pieter Annaert, Karel Allegaert, Anne Smits
Veröffentlicht in: BMJ Paediatrics Open, Ausgabe 8(1), 2024, Seite(n) e002385, ISSN 2399-9772
Herausgeber: BMJ Publishing Group
DOI: 10.1136/bmjpo-2023-002385

Case Report: Bosentan and Sildenafil Exposure in Human Milk - A Contribution From the ConcePTION Project

Autoren: Nina Nauwelaerts, Michael Ceulemans, Neel Deferm, An Eerdekens, Bart Lammens, Yeghig Armoudjian, Kristel Van Calsteren, Karel Allegaert, Loes de Vries, Pieter Annaert and Anne Smits
Veröffentlicht in: Frontiers in Pharmacology, 2022, ISSN 0000-0000
Herausgeber: Frontiers
DOI: 10.3389/fphar.2022.881084

An ethics framework for the transition to an operational learning healthcare system

Autoren: Marieke J Hollestelle, Rieke van der Graaf, Miriam CJM Sturkenboom, Johannes JM van Delden
Veröffentlicht in: Learning Health Systems, 2024, ISSN 2379-6146
Herausgeber: Wiley Periodicals LLC
DOI: 10.1002/lrh2.10414

Maternal Socioeconomic Status and the Initiation and Duration of Breastfeeding in Western Europe Versus Southern Africa: A Systematic Review—A Contribution from the ConcePTION Project

Autoren: Martje Van Neste, Katoo Verschoren, Rani Kempenaers, An Eerdekens, Danine Kitshoff, Karel Allegaert, Annick Bogaerts
Veröffentlicht in: Nutrients, Ausgabe 17, 2025, Seite(n) 946, ISSN 2072-6643
Herausgeber: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/nu17060946

Breastfeeding, pregnancy, medicines, neurodevelopment, and population databases: the information desert.

Autoren: Sue Jordan, Rebecca Bromley, Christine Damase‐Michel, Joanne Given, Sophia Komninou, Maria Loane, Naomi Marfell, Helen Dolk.
Veröffentlicht in: International Breastfeeding Journal, Ausgabe 17, 2022, Seite(n) 55, ISSN 1746-4358
Herausgeber: BioMed Central
DOI: 10.1186/s13006-022-00494-5

Population pharmacokinetic modelling of cetirizine concentrations in human breast milk—A contribution from the ConcePTION project

Autoren: Erik Melander, Elisabet I. Nielsen, Annika Lindqvist, Markus Hovd, Peggy Gandia, Alice Panchaud, Monia Guidi, Pieter Annaert, Pawel Baranczewski, Olav Spigset, Hedvig Nordeng
Veröffentlicht in: Basic & Clinical Pharmacology & Toxicology, 2024, ISSN 1742-7835
Herausgeber: Nordic Pharmacological Society
DOI: 10.1111/bcpt.14100

Addressing bias due to measurement error of an outcome with unknown sensitivity in database epidemiological studies

Autoren: Giorgio Limoncella, Leonardo Grilli, Emanuela Dreassi, Carla Rampichini, Robert Platt, Rosa Gini
Veröffentlicht in: American Journal of Epidemiology, 2024, ISSN 0002-9262
Herausgeber: Oxford University Press
DOI: 10.1093/aje/kwae423

Building a Sustainable Learning Health Care System for Pregnant and Lactating People: Interview Study Among Data Access Providers

Autoren: Marieke J Hollestelle; Rieke van der Graaf; Miriam C J M Sturkenboom; Marianne Cunnington; Johannes J M van Delden
Veröffentlicht in: JMIR Pediatrics and Parenting, Ausgabe 7, 2024, Seite(n) e47092, ISSN 2561-6722
Herausgeber: JMIR Publications Inc
DOI: 10.2196/47092

Online information discrepancies regarding safety of medicine use during pregnancy and lactation: an IMI ConcePTION study

Autoren: Ulrika Nörby, Benedikte Noël-Cuppers, Sashka Hristoskova, Monali Desai, Linda Härmark, Michael Steel, Chantal El-Haddad, Ludivine Douarin
Veröffentlicht in: Expert Opinion on Drug Safety, 2021, Seite(n) 1-8, ISSN 1474-0338
Herausgeber: Ashley Publications Ltd.
DOI: 10.1080/14740338.2021.1935865

Methods of estimating prevalence of multiple sclerosis in six European healthcare data sources: a contribution from the ConcePTION project

Autoren: Marie Beslay, Anna-Belle Beau, Davide Messina, Justine Benevent, Elisa Ballardini, Laia Barrachina-Bonet, Clara Cavero-Carbonell, Alex Coldea, Laura García-Villodre, Anja Geldhof, Rosa Gini, Kerstin Hellwig, Sue Jordan, Maarit K. Leinonen, Sandra Lopez-Leon, Marco Manfrini, Visa Martikainen, Vera R. Mitter, Amanda J. Neville, Hedvig Nordeng, Aurora Puccini, Sandra Vukusic, Christine Damase-Michel
Veröffentlicht in: European Journal of Epidemiology, 2025, ISSN 0393-2990
Herausgeber: Kluwer Academic Publishers
DOI: 10.1007/s10654-025-01243-8

Isolation and characterization of mammary epithelial cells derived from Göttingen Minipigs: A comparative study versus hybrid pig cells from the IMI-ConcePTION Project

Autoren: Chiara Bernardini, Salvatore Nesci, Debora La Mantia, Roberta Salaroli, Nina Nauwelaerts, Domenico Ventrella, Alberto Elmi, Fabiana Trombetti, Augusta Zannoni, and Monica Forni
Veröffentlicht in: Research in Veterinary Science, Ausgabe 172, 2024, Seite(n) 105, 244, ISSN 0034-5288
Herausgeber: W. B. Saunders Co., Ltd.
DOI: 10.1016/j.rvsc.2024.105244

Sensitive and rapid method for the quantitation of amoxicillin in minipig plasma and milk by LC-MS/MS: A contribution from the IMI ConcePTION project

Autoren: Yeghig Armoudjian, Yeghig Armoudjian, Qi Lin, Bart Lammens, Johan Van Daele, Pieter Annaert
Veröffentlicht in: Journal of Pharmacological and Toxicological Methods, 2023, ISSN 1056-8719
Herausgeber: Elsevier BV
DOI: 10.1016/j.vascn.2023.107264

A Learning Healthcare System for pregnant and breastfeeding women: what do women during preconception, pregnancy, and nursing think? – A qualitative study

Autoren: Marieke J. Hollestelle, Rieke van der Graaf, Sarah Dewi Hartman, Miriam C. J. M. Sturkenboom & Johannes J. M. van Delden
Veröffentlicht in: BMC Pregnancy and Childbirth, 2022, ISSN 1471-2393
Herausgeber: BioMed Central
DOI: 10.1186/s12884-022-04675-2

Generic Workflow to Predict Medicine Concentrations in Human Milk Using Physiologically-Based Pharmacokinetic (PBPK) Modelling—A Contribution from the ConcePTION Project

Autoren: Nina Nauwelaerts, Julia Macente, Neel Deferm, Rodolfo Hernandes Bonan, Miao-Chan Huang, Martje Van Neste, David Bibi, Justine Badee, Frederico S. Martins, Anne Smits, Karel Allegaert, Thomas Bouillon, Pieter Annaert
Veröffentlicht in: Pharmaceutics, 2023, ISSN 1999-4923
Herausgeber: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/pharmaceutics15051469

A Landscape Analysis of Post-Marketing Studies Registered in the EU PAS Register and ClinicalTrials.gov Focusing on Pregnancy Outcomes or Breastfeeding Effects: A Contribution from the ConcePTION Project

Autoren: Leonardo Roque Pereira, Carlos E. Durán, Deborah Layton, Georgios Poulentzas, Panagiotis-Nikolaos Lalagkas, Christos Kontogiorgis and Miriam Sturkenboom
Veröffentlicht in: Drug Safety, 2022, ISSN 0000-0000
Herausgeber: Springer Nature
DOI: 10.1007/s40264-022-01154-7

Where are the data to assess the safety of paternal drug exposure? A systematic review of secondary databases: A contribution from IMI concePTION

Autoren: Sneha Gaitonde, Yola Moride, Elizabeth Suarez, Sandra Lopez-Leon
Veröffentlicht in: Pharmacoepidemiology & Drug Safety, Ausgabe 33, 2024, ISSN 1099-1557
Herausgeber: John Wiley & Sons Ltd
DOI: 10.1002/pds.5764

A systematic review and meta-analyses on the prevalence of pregnancy outcomes in migraine treated patients: a contribution from the IMI2 ConcePTION project

Autoren: Daniel C. Dudman, Fatima Tauqeer, Moninder Kaur, Mary E. Ritchey, Hu Li, Sandra Lopez-Leon
Veröffentlicht in: Journal of Neurology, 2021, ISSN 0340-5354
Herausgeber: Dr. Dietrich Steinkopff Verlag
DOI: 10.1007/s00415-021-10534-5

Autoren: Martje Van Neste, Annick Bogaerts, Nina Nauwelaerts, Julia Macente, Anne Smits, Pieter Annaert, Karel Allegaert
Veröffentlicht in: Pharmaceutics, Ausgabe 15(11), 2618, 2023, ISSN 1999-4923
Herausgeber: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/pharmaceutics15112618

IMI ConcePTION core data elements for pregnancy pharmacovigilance studies using primary source data collection methods

Autoren: Jonathan Richardson, Alan Moore, Rebecca Bromley, Michael Stellfeld, Yvonne Geissbühler, Matthew Bluett-Duncan, Ursula Winterfeld, Guillaume Favre, Kenneth Hodson, Alison Oliver, Amalia Alexe, Yrea van Rijt-Weetink, Bita Rezaallah, Eugene van Puijenbroek, David Lewis, Laura Yates
Veröffentlicht in: Neurotoxicology and Teratology, Ausgabe 98, 2023, Seite(n) 107, 198, ISSN 0892-0362
Herausgeber: Elsevier BV
DOI: 10.1016/j.ntt.2023.107198

Development of a pig mammary epithelial cell culture model as a non‐clinical tool for studying epithelial barrier— a contribution from the imi‐conception project

Autoren: Chiara Bernardini; Debora La Mantia; Roberta Salaroli; Augusta Zannoni; Nina Nauwelaerts; Neel Deferm; Domenico Ventrella; Maria Laura Bacci; Giuseppe Sarli; Michele Bouisset-Leonard; Pieter Annaert; Monica Forni
Veröffentlicht in: Animals, Vol 11, Iss 2012, p 2012 (2021), 2021, ISSN 2076-2615
Herausgeber: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/ani11072012

Validation of a Novel Method to Assess the Clinical Quality of Information in pregnancy-related pharmacovigilance case reports: a ConcePTION project

Autoren: Yrea R. J. van Rijt-Weetink, Toine C. G. Egberts, Florence P. A. M. van Hunsel, David J. Lewis, Laura M. Yates, Ursula Winterfeld, Eugène P. van Puijenbroek
Veröffentlicht in: Drug Safety, Ausgabe 47, 2024, Seite(n) 261-270, ISSN 0114-5916
Herausgeber: Adis International Ltd.
DOI: 10.1007/s40264-023-01389-y

A systematic review and meta-analyses of pregnancy and fetal outcomes in women with multiple sclerosis: a contribution from the IMI2 ConcePTION project

Autoren: Sandra Lopez-Leon, Yvonne Geissbühler, Meritxell Sabidó, Moise Turkson, Charlotte Wahlich, Joan K. Morris
Veröffentlicht in: Journal of Neurology, 2020, ISSN 0340-5354
Herausgeber: Dr. Dietrich Steinkopff Verlag
DOI: 10.1007/s00415-020-09913-1

An innovative mobile app for the provision of medical information and collection of safety data on exposure to medicines during pregnancy or breastfeeding: An IHI ConcePTION contribution

Autoren: Amalia Alexe, David Lewis, Kendal Harrison
Veröffentlicht in: Reproductive, Female and Child Health, Ausgabe 3, 2024, ISSN 2768-7228
Herausgeber: Wiley
DOI: 10.1002/rfc2.74

A population pharmacokinetic model for sertraline in women during the perinatal period—A contribution from the ConcePTION project

Autoren: Anaëlle Monfort, Evelina Cardoso, Chin B. Eap, Nicolas Ansermot, Severine Crettol, Céline J. Fischer Fumeaux, Myriam Bickle Graz, Mathilde Morisod Harari, Etienne Weisskopf, Peggy Gandia, Karel Allegaert, Pieter Annaert, Hedvig Nordeng, Jean‐Michel Hascoët, Olivier Claris, Manuella Epiney, Ema Ferreira, Grégoire Leclair, Chantal Csajka, Alice Panchaud, Monia Guidi, null null
Veröffentlicht in: British Journal of Clinical Pharmacology, 2024, ISSN 0306-5251
Herausgeber: Blackwell Publishing Inc.
DOI: 10.1111/bcp.16177

Systematic review of gabapentinoid use during pregnancy and its impact on pregnancy and childhood outcomes: A ConcePTION study

Autoren: Anna-Belle Beau, Jingping Mo, Xavier Moisset, Justine Bénévent, Christine Damase-Michel
Veröffentlicht in: Therapies, 2024, ISSN 0040-5957
Herausgeber: John Libbey & Co. Ltd.
DOI: 10.1016/j.therap.2024.10.049

Systematic Search of Height and Weight Changes of Exclusively Breastfed Infants Until 1 Year of age: A Contribution from the ConcePTION Project

Autoren: Martje Van Neste, Julia Macente, Nina Nauwelaerts, Lieveke Ameye, Annick Bogaerts, Anne Smits, Pieter Annaert, Karel Allegaert
Veröffentlicht in: Clinical Pharmacokinetics, 2025, ISSN 0312-5963
Herausgeber: Adis International Ltd.
DOI: 10.1007/s40262-025-01583-4

Neurodevelopmental outcomes in children and adults with Fetal Valproate Spectrum Disorder: a contribution from the ConcePTION project

Autoren: Bluett-Duncan M., Astill D., Charbak R., Clayton-Smith J., Cole S., Cook P. A., Cozens J., Keely K., Morris J., Mukherjee R., Murphy E., Turnpenny P., Williams J., Wood A. G., Yates L., Bromley R. L.
Veröffentlicht in: Neurotoxicology and Teratology, Ausgabe 98, 2023, Seite(n) 107, 201, ISSN 0892-0362
Herausgeber: Elsevier BV
DOI: 10.1016/j.ntt.2023.107292

Elements to assess the quality of information of case reports in pregnancy pharmacovigilance data - a ConcePTIONproject

Autoren: Yrea R.J. van Rijt-Weetink, Khoezik Chamani, Toine C.G. Egberts, Florence P.A.M. van Hunsel, David J. Lewis, Laura M. Yates, Ursula Winterfeld, Eugène P. van Puijenbroek
Veröffentlicht in: Frontiers in Drug Safety and Regulation, Ausgabe 3, 2023, ISSN 2674-0869
Herausgeber: Frontiers Media S.A.
DOI: 10.3389/fdsfr.2023.1187888

The Deuterium Oxide Dilution Method to Quantify Human Milk Intake Volume of Infants: A Systematic Review—A Contribution from the ConcePTION Project

Autoren: Lucas Cloostermans, Karel Allegaert, Anne Smits, Martje Van Neste
Veröffentlicht in: Nutrients, Ausgabe 16, 2024, Seite(n) 4205, ISSN 2072-6643
Herausgeber: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/nu16234205

Expert consensus on neurodevelopmental outcomes in pregnancy pharmacovigilance studies

Autoren: Bromley R. L., Bickle Graz M., Bluett-Duncan M., Chambers C., Damkier P., Dietrich K., Dolk H., Grant K., Mattson S., Meador K. J., Nordeng H., Oberlander T. F., Ornoy A., Revet A., Richardson J., Rovet J., Schuler-Faccini L., Smearman E., Simms V., Vorhees C., Wide K., Wood A., Yates L., Ystrom E., Supraja T. A., Adams J.
Veröffentlicht in: Frontiers in Pharmacology, 2023, ISSN 1663-9812
Herausgeber: Frontiers Media S.A.
DOI: 10.3389/fphar.2023.1094698

Core Data Elements for Pregnancy Pharmacovigilance Studies Using Primary Source Data Collection Methods: Recommendations from the IMI ConcePTION Project

Autoren: Jonathan L. Richardson, Alan Moore, Rebecca L. Bromley, Michael Stellfeld, Yvonne Geissbühler, Matthew Bluett‑Duncan, Ursula Winterfeld, Guillaume Favre, Amalia Alexe, Alison M. Oliver, Yrea R. J. van Rijt‑Weetink, Kenneth K. Hodson, Bita Rezaallah, Eugene P. van Puijenbroek, David J. Lewis, Laura M. Yates
Veröffentlicht in: Drug Safety, 2023, ISSN 0114-5916
Herausgeber: Adis International Ltd.
DOI: 10.1007/s40264-023-01291-7

A comprehensive review on non-clinical methods to study transfer of medication into breast milk – A contribution from the ConcePTION project

Autoren: Nina Nauwelaerts, Neel Deferm, Anne Smits, Chiara Bernardini, Bart Lammens, Peggy Gandia, Alice Panchaud, Hedvig Nordeng, Maria Laura Bacci, Monica Forni, Domenico Ventrella, Kristel Van Calsteren, Anthony DeLise, Isabelle Huys, Michele Bouisset-Leonard, Karel Allegaert, Pieter Annaert
Veröffentlicht in: Biomedicine & Pharmacotherapy, Ausgabe 136, 2021, Seite(n) 111038, ISSN 0753-3322
Herausgeber: Elsevier Masson
DOI: 10.1016/j.biopha.2020.111038

Animal Models for In Vivo Lactation Studies: Anatomy, Physiology and Milk Compositions in the Most Used Non-Clinical Species: A Contribution from the ConcePTION Project

Autoren: Domenico Ventrella, Nurit Ashkenazi, Alberto Elmi, Karel Allegaert, Camilla Aniballi, Anthony DeLise, Patrick John Devine, Anne Smits, Lilach Steiner, Monica Forni, Michele Bouisset-Leonard, Maria Laura Bacci
Veröffentlicht in: Animals, Ausgabe 11/3, 2021, Seite(n) 714, ISSN 2076-2615
Herausgeber: MDPI
DOI: 10.3390/ani11030714

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