Periodic Reporting for period 2 - PERSIST (Patients-centered SurvivorShIp care plan after Cancer treatments based on Big Data and Artificial Intelligence technologies)
Reporting period: 2021-01-01 to 2021-12-31
Cancer concerns all European citizens. 40% of us are likely to be affected and we all know someone who developed the disease. In 2020, 19.3 million of new cases appeared and there were 9.96 million deaths
For a long time, cancer treatment has been the main focus of research, but the moment has come to pay attention and efforts on 'long-term patients'. Cancer survivors have unmet needs, especially when it comes to improving their independence and quality of life (QoL), in addition to extending the duration of life. These are important aspects to tackle, not only from the patient perspective but also for society acceptance and adaptation of the cancer survivors.
PERSIST goals are very ambitious, pursuing a radical breakthrough in the quality of treatment and follow-up of cancer survivors. PERSIST not only develops innovative applications based on artificial intelligence and big data, but also aims to demonstrate their effectiveness in improving the quality of life of these survivors. In this regard, PERSIST approach is fully patient-centric while taking into account all the necessary elements of the healthcare ecosystem, in order to ensure a rapid uptake of the results in the European context. The complete PERSIST system will incorporate, on the one hand, a Clinical Decision Support System based on new models of health data analysis. On the other hand, a mHealth system for the remote and personalized monitoring of each patient. In addition, the partners will develop a Big Data Platform that integrates the two previous systems and will connect to the Electronic Health Records (EHRs) of the hospitals.
For a long time, cancer treatment has been the main focus of research, but the moment has come to pay attention and efforts on 'long-term patients'. Cancer survivors have unmet needs, especially when it comes to improving their independence and quality of life (QoL), in addition to extending the duration of life. These are important aspects to tackle, not only from the patient perspective but also for society acceptance and adaptation of the cancer survivors.
PERSIST goals are very ambitious, pursuing a radical breakthrough in the quality of treatment and follow-up of cancer survivors. PERSIST not only develops innovative applications based on artificial intelligence and big data, but also aims to demonstrate their effectiveness in improving the quality of life of these survivors. In this regard, PERSIST approach is fully patient-centric while taking into account all the necessary elements of the healthcare ecosystem, in order to ensure a rapid uptake of the results in the European context. The complete PERSIST system will incorporate, on the one hand, a Clinical Decision Support System based on new models of health data analysis. On the other hand, a mHealth system for the remote and personalized monitoring of each patient. In addition, the partners will develop a Big Data Platform that integrates the two previous systems and will connect to the Electronic Health Records (EHRs) of the hospitals.
By the end of 2021 the BIG DATA PLATFORM features were developed, such as the CDS-Hooks component to allow the connection with CDS services. Likewise, new capabilities to execute modules based on AI were deployed, i.e. the AI-Ready adapter which provides an easier way to query the data stored in the Big Data platform.
The MULTIMODAL SENSING NETWORK version alpha is already finished. In addition to the first version of objective sensors and PREM/PROM API as subjective sensors already delivered, also the first version of the embodied conversational agents in the four languages are already finished and they are being finetuning. Likewise, first version of attitude and emotion classication algorithms were developed, being retrained with new samples.
Regarding the scalable hard-plastic chip for CTC isolation, it was succesfully tested using the standard PDMS priming and blood processing protocols. Meanwhile, a CTC web application for manual ingestion was developed and deployed. CTC images were preprocessed and annotated in accordance with COCO standard, being ready for the AI training.
Data extraction ended in 2021, giving the chance to improve the results of the first approach to COHORTS and TRAJECTORIES performed previously. In particular, first models for life expectancy estimation were developed and they can be accessed now through a new designed web-interface. Additionally, ENRICHMENT steps regarding diseases, symptoms, and medication data extraction were addressed. As for the EHR prospective data ingestion, an specific user interface for clinicians, called mClinician, was created. This web app has also been integratd with the Big Data platform.
The last key component of PERSIST is the INFERENCE ENGINE of the clinical decision support system (CDSS). Along with technical details, the development of a knowledge base was addressed. Its core will be rule flows that integreates both clinical guidelines and literature as well as trajectory projections. At this moment, based on the guidelines, a scoring algorithm is developed for assessing risk of breast and colon cancer recurrence according to patient’s retrospective data, questionnaire responses and patient habits and lifestyle.
In 2021, the CLINICAL STUDY with 160 patients in 4 hospitals (Belgium, Latvia, Slovenia, Spain) was successfully launched. To achieve this, every clinical partner involved 20 breast cancer (C50) and 20 colorectal cancer (C18/C19)survivor patients. Also, during this year, clinical partners performed a close follow-up of these patients and held several workshops to not only explain PERSIST in detail, but also to gather feedback from patients (co-creation activities).
PERSIST consortium presented the project on several events, such as conferences (online and in person), public sector and industry events (online and in person), academic and research events (online and in person), and seminars, as well as to organise project-specific events. Besides, relevant materials were produced like the new project presentations, newsletters, press releases, videos etc. Furthermore, several electronic and web dissemination channels kept their dissemination activities, including the project website, its collaboration portal, social media accounts and channels. Lastly, a specific exploitation and sustainability task started where ‘Mission & Vision’ were defined.
The MULTIMODAL SENSING NETWORK version alpha is already finished. In addition to the first version of objective sensors and PREM/PROM API as subjective sensors already delivered, also the first version of the embodied conversational agents in the four languages are already finished and they are being finetuning. Likewise, first version of attitude and emotion classication algorithms were developed, being retrained with new samples.
Regarding the scalable hard-plastic chip for CTC isolation, it was succesfully tested using the standard PDMS priming and blood processing protocols. Meanwhile, a CTC web application for manual ingestion was developed and deployed. CTC images were preprocessed and annotated in accordance with COCO standard, being ready for the AI training.
Data extraction ended in 2021, giving the chance to improve the results of the first approach to COHORTS and TRAJECTORIES performed previously. In particular, first models for life expectancy estimation were developed and they can be accessed now through a new designed web-interface. Additionally, ENRICHMENT steps regarding diseases, symptoms, and medication data extraction were addressed. As for the EHR prospective data ingestion, an specific user interface for clinicians, called mClinician, was created. This web app has also been integratd with the Big Data platform.
The last key component of PERSIST is the INFERENCE ENGINE of the clinical decision support system (CDSS). Along with technical details, the development of a knowledge base was addressed. Its core will be rule flows that integreates both clinical guidelines and literature as well as trajectory projections. At this moment, based on the guidelines, a scoring algorithm is developed for assessing risk of breast and colon cancer recurrence according to patient’s retrospective data, questionnaire responses and patient habits and lifestyle.
In 2021, the CLINICAL STUDY with 160 patients in 4 hospitals (Belgium, Latvia, Slovenia, Spain) was successfully launched. To achieve this, every clinical partner involved 20 breast cancer (C50) and 20 colorectal cancer (C18/C19)survivor patients. Also, during this year, clinical partners performed a close follow-up of these patients and held several workshops to not only explain PERSIST in detail, but also to gather feedback from patients (co-creation activities).
PERSIST consortium presented the project on several events, such as conferences (online and in person), public sector and industry events (online and in person), academic and research events (online and in person), and seminars, as well as to organise project-specific events. Besides, relevant materials were produced like the new project presentations, newsletters, press releases, videos etc. Furthermore, several electronic and web dissemination channels kept their dissemination activities, including the project website, its collaboration portal, social media accounts and channels. Lastly, a specific exploitation and sustainability task started where ‘Mission & Vision’ were defined.
By the end of the project we will get ready a robust, scalable and flexible BIG DATA PLATFORM enabling the flow of complex and fragmented data from disparate applications and heterogeneous sources. This flow will be secured and supported by open interfacing industry standards and the use of FHIR for clinical resource definition. Given that part of the data will be extracted from hospitals with different storing schema, a protocol for the extraction and preparation of EHR data for secondary use will also be designed.
PERSIST will also offer patients the possibility of remote support and monitoring. The combination of patients’ wearables, a mHealth application and an innovative multimodal sensing network will collect objective data (e.g. physical activity frequency, duration, new biomarkers, and intensity), patients’ perceptions (on their health and experience) and complex phenomena such as mood and depression. Since these are new sources of health and wellbeing data, the corresponding standard mechanism for collecting their data in a secure and reliable way will be set.
Additionally, PERSIST will develop a new software for automated CTC counting and new classification models based on image analysis, signal fusion and transfer knowledge concepts for tracking and classification of wellbeing and health parameters of cancer survivors. Artificial Intelligence (AI) will be employed to achieve predictive models based on multiple level cohort analysis and identification of common trajectories of cancer patients that can be used to personalize and optimize treatment, and to prevent adverse events and hospital readmissions. This predictive model will be the base of clinical knowledge modules that provide clinicians accurate recommendations for developing, reviewing and updating Survivor Care Plans (SCP) and highlight alarming states and situations where rapid response is required. This will allow associations between lifestyle and wellbeing factors and the outcomes observed during the follow up of cancer survivors, helping in the prevention and timely addressing of long-term side effects.
During the project, four simultaneous clinical studies (in Latvia, Belgium, Slovenia and Spain) will be carried out to demonstrate the advantages of monitoring lifestyle factors in cancer survivors and draw conclusions on the usability and performance of the ecosystem from patients and professionals perspectives.
PERSIST will also offer patients the possibility of remote support and monitoring. The combination of patients’ wearables, a mHealth application and an innovative multimodal sensing network will collect objective data (e.g. physical activity frequency, duration, new biomarkers, and intensity), patients’ perceptions (on their health and experience) and complex phenomena such as mood and depression. Since these are new sources of health and wellbeing data, the corresponding standard mechanism for collecting their data in a secure and reliable way will be set.
Additionally, PERSIST will develop a new software for automated CTC counting and new classification models based on image analysis, signal fusion and transfer knowledge concepts for tracking and classification of wellbeing and health parameters of cancer survivors. Artificial Intelligence (AI) will be employed to achieve predictive models based on multiple level cohort analysis and identification of common trajectories of cancer patients that can be used to personalize and optimize treatment, and to prevent adverse events and hospital readmissions. This predictive model will be the base of clinical knowledge modules that provide clinicians accurate recommendations for developing, reviewing and updating Survivor Care Plans (SCP) and highlight alarming states and situations where rapid response is required. This will allow associations between lifestyle and wellbeing factors and the outcomes observed during the follow up of cancer survivors, helping in the prevention and timely addressing of long-term side effects.
During the project, four simultaneous clinical studies (in Latvia, Belgium, Slovenia and Spain) will be carried out to demonstrate the advantages of monitoring lifestyle factors in cancer survivors and draw conclusions on the usability and performance of the ecosystem from patients and professionals perspectives.