Periodic Reporting for period 1 - OPTOMICS (Combining optoacoustic imaging phenotypes and multi-omics to advance diabetes healthcare)
Okres sprawozdawczy: 2021-01-01 do 2021-12-31
Diabetes has emerged as a global pandemic affecting more than 420 million people worldwide, a number expected to further rise in the next decades. The disease has very heterogeneous outcomes and accurate patient staging or prediction of subsets of individuals likely to develop disease and/or progress to disease complications are currently unmet clinical challenges in need of urgent attention.
OPTOMICS aims to research methodology that can deliver a paradigm shift in type-2 diabetes healthcare, by integrating 1) molecular phenotyping, 2) a new generation of phenotypic measurements in humans, representative of diabetes onset and progression, allowed by novel portable and non-invasive optoacoustic technology and 3) cutting-edge computational approaches leveraging progress in Artificial Intelligence. This research will develop and validate a Digital Twin model that catalyses a step change in shortening the path to translation, enabling applications in the entire spectrum from target identification and prevention/prognosis to patient stratification for type-2 diabetes and its complications.
In addition to the research and technology goals, OPTOMICS places special attention to the ethical needs and implications of the work performed and further aims at exemplary project management, human measurements, dissemination and communication activities and updating an adept exploitation plan for the Digital Twin developed.
OPTOMICS aims to research methodology that can deliver a paradigm shift in type-2 diabetes healthcare, by integrating 1) molecular phenotyping, 2) a new generation of phenotypic measurements in humans, representative of diabetes onset and progression, allowed by novel portable and non-invasive optoacoustic technology and 3) cutting-edge computational approaches leveraging progress in Artificial Intelligence. This research will develop and validate a Digital Twin model that catalyses a step change in shortening the path to translation, enabling applications in the entire spectrum from target identification and prevention/prognosis to patient stratification for type-2 diabetes and its complications.
In addition to the research and technology goals, OPTOMICS places special attention to the ethical needs and implications of the work performed and further aims at exemplary project management, human measurements, dissemination and communication activities and updating an adept exploitation plan for the Digital Twin developed.
During the first 12 months (RP1) of the project, the main focus of the work were centered on preparing for the start of the clinical trials, which will take place at TUM and UTARTU. This included the following important steps:
1. Design of the study including the clinical procedures and sampling protocols, data management and transfer, quality control and dynamic imaging algorithms, and data protection and handling procedures; and
2. Subsequent preparation and submission of ethics protocols, including (in addition to the study design) patient questionnaires, informed consent forms, and Medical Device Regulation (MDR) documentation for the RSOM for both clinical sites;
3. Placement of and training on identical RSOM C50 devices at both clinical sites;
4. Addition of an external Ethics Expert and hosting of an Ethics Workshop to ensure that all ethics, especially those concerning data protection, are understood by the Consortium;
5. Design and implementation of the structure and data access procedures of the central database;
To exploit and disseminate the current set of results, several actions were taken, including:
1. Completion of the Consortium Agreement (CA) as a means of internal IP protection and establishment of the Management and Steering Committee (MSC) and Dissemination-Exploitation-Communication Committee (DECC);
2. Development of an initial Dissemination, Exploitation and Communication plan, with an OPTOMICS ‘Communication Guide’ and Cross-Project Collaboration (CPC) plan outlining joint synergies and possible actions with Complementary Beneficiaries DIGIPREDICT and Neurotwin to promote Digital Twin technologies for life sciences;
3. Creation of a visual identity (logo, website banners, etc.), the project website, and social media accounts. Active updates and posting on the website and social media accounts, three media releases (TUM, H2020 and FETFX press offices), attendance of consortium members to conferences, and submission of journal articles (currently in peer-review).
In the next months of the project through the entirety of RP2, the project will move into phase 1 of data collection producing optoacoustic images for biomarker identification to be paired with deep molecular phenotyping in correlation studies.
1. Design of the study including the clinical procedures and sampling protocols, data management and transfer, quality control and dynamic imaging algorithms, and data protection and handling procedures; and
2. Subsequent preparation and submission of ethics protocols, including (in addition to the study design) patient questionnaires, informed consent forms, and Medical Device Regulation (MDR) documentation for the RSOM for both clinical sites;
3. Placement of and training on identical RSOM C50 devices at both clinical sites;
4. Addition of an external Ethics Expert and hosting of an Ethics Workshop to ensure that all ethics, especially those concerning data protection, are understood by the Consortium;
5. Design and implementation of the structure and data access procedures of the central database;
To exploit and disseminate the current set of results, several actions were taken, including:
1. Completion of the Consortium Agreement (CA) as a means of internal IP protection and establishment of the Management and Steering Committee (MSC) and Dissemination-Exploitation-Communication Committee (DECC);
2. Development of an initial Dissemination, Exploitation and Communication plan, with an OPTOMICS ‘Communication Guide’ and Cross-Project Collaboration (CPC) plan outlining joint synergies and possible actions with Complementary Beneficiaries DIGIPREDICT and Neurotwin to promote Digital Twin technologies for life sciences;
3. Creation of a visual identity (logo, website banners, etc.), the project website, and social media accounts. Active updates and posting on the website and social media accounts, three media releases (TUM, H2020 and FETFX press offices), attendance of consortium members to conferences, and submission of journal articles (currently in peer-review).
In the next months of the project through the entirety of RP2, the project will move into phase 1 of data collection producing optoacoustic images for biomarker identification to be paired with deep molecular phenotyping in correlation studies.
With diabetes affecting so many worldwide, OPTOMICS’ ambition is to address a global health problem by advancing healthcare beyond state of the art. Our aim is to build a unique data set incorporating a novel biosensing concept that uses the skin as a measurement window with deep molecular phenotyping (genomics, proteomics, metabolomics). Diabetes care already relies on the use of sensors, in particular glucose sensors, which help with daily disease management and regulating insulin levels in the blood, but are not appropriate for characterizing the systemic effects of the disease. Furthermore, diabetes is a progressive disease, but the characterization of diabetes severity is currently performed using a crude set of clinical symptoms and glucose measurements, which has been identified as an impediment to precise care and accurate assessment of intervention effects. The ability to quantify systemic effects of diabetes, not only glucose levels, in a disseminated and portable manner could be critical for health management of such a large patient pool.
The aim of the OPTOMICS project is to use a portable, non-invasive optoacoustic imaging device (RSOM) coupled with molecular phenotyping to produce a Digital Twin model with highly predictive prognostic and stratification value, which is necessary for improving diabetes healthcare. This novel paradigm of quantitatively combining molecular imaging and –omics profiles, which leads the way in the biophotonics field, will permit causal interference analysis and the identification of effector genes for risk loci, and advance our understanding of the underlying disease aetiopathogenisis. Leveraging advances in Artificial Intelligence, we expect to use this unique, trans-disciplinary dataset to identify multiple unknown links between systemic effects of diabetes and molecular underpinnings. The subsequent development of multifaceted patient stratification through the Digital Twin will be capable of clinical decision making and be used to improve prediction, prevention, early detection and prognosis through individualized healthcare.
We envision that the entire platform proposed in OPTOMICS is not only suitable to provide new insights into diabetes research and healthcare, but can become a practical approach for administering diabetes healthcare in a personalized manner. RSOM is a portable, label-free and non-invasive method that is relatively inexpensive (compared to current standards like PET or MRI) and is well suited for point of care settings and large populations. An adept exploitation plan will be created by selecting a portfolio of biomarkers that can maximize healthcare impact and optimize cost to benefit of the Digital Twin model, after its performance is validated and ethical considerations are examined.
The aim of the OPTOMICS project is to use a portable, non-invasive optoacoustic imaging device (RSOM) coupled with molecular phenotyping to produce a Digital Twin model with highly predictive prognostic and stratification value, which is necessary for improving diabetes healthcare. This novel paradigm of quantitatively combining molecular imaging and –omics profiles, which leads the way in the biophotonics field, will permit causal interference analysis and the identification of effector genes for risk loci, and advance our understanding of the underlying disease aetiopathogenisis. Leveraging advances in Artificial Intelligence, we expect to use this unique, trans-disciplinary dataset to identify multiple unknown links between systemic effects of diabetes and molecular underpinnings. The subsequent development of multifaceted patient stratification through the Digital Twin will be capable of clinical decision making and be used to improve prediction, prevention, early detection and prognosis through individualized healthcare.
We envision that the entire platform proposed in OPTOMICS is not only suitable to provide new insights into diabetes research and healthcare, but can become a practical approach for administering diabetes healthcare in a personalized manner. RSOM is a portable, label-free and non-invasive method that is relatively inexpensive (compared to current standards like PET or MRI) and is well suited for point of care settings and large populations. An adept exploitation plan will be created by selecting a portfolio of biomarkers that can maximize healthcare impact and optimize cost to benefit of the Digital Twin model, after its performance is validated and ethical considerations are examined.