Periodic Reporting for period 3 - OPTOMICS (Combining optoacoustic imaging phenotypes and multi-omics to advance diabetes healthcare)
Reporting period: 2023-07-01 to 2025-03-31
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 project thus far (51 months), the primary focus has been to implement clinical studies and collect data, integrate multimodal datasets for assessing type-2 diabetes patient staging, prognosis, and treatment monitoring, and develop an innovative Digital Twin tool for improving individualized healthcare.
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. Preparation and submission of ethics protocols, including patient questionnaires, informed consent forms, specialized training by clinicians, and Medical Device Regulation (MDR) documentation for the RSOM for all sites;
3. Completion of first timepoint achieving the targeted patient cohort through the Estonian Biobank, and initiation of first timepoint for the TUM-led study, which has been expanded to a multi-center study;
4. Integration of omics profiles, optoacoustic (RSOM) dynamic and static data (images and raw data), and advancing pipelines that will be used to refine and validate the Digital Twin.
5. Close work with an external Ethics Expert and Clinical Research Organization to ensure that all ethics, especially those concerning data protection and potential implications of project results, are understood, discussed and complied with by the Consortium;
6. 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. Frequent and open communication within the General Consortium, Management and Steering Committee (MSC), and Dissemination-Exploitation-Communication Committee (DECC);
2. Management and update of the Dissemination, Exploitation and Communication plan;
3. In-depth market strategy and stakeholder engagement initiated and continuously in progress to ensure clinical uptake and facilitate exploitation of identified IP;
3. Maintaining the project website and social media accounts (Twitter, LinkedIn, BlueSky), with frequent posts and organized Twitter campaigns lining up with important international awareness days;
4. Publication of nine peer-reviewed papers (6 in RP3, including one in Nature) and extensive participation in workshops and conferences by consortium members;
5. Participation in public outreach events and through media press releases ; and,
6. Collaboration with Complementary Grants and joint (1st) International Symposium for Digital Twins in Healthcare in 2024.
In the final stage of the project, the project will focus on continuing to integrate biomarker identification with deep molecular phenotyping in correlation studies and begin assessing disease progress with the start of the second timepoint of the clinical trials.
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. Preparation and submission of ethics protocols, including patient questionnaires, informed consent forms, specialized training by clinicians, and Medical Device Regulation (MDR) documentation for the RSOM for all sites;
3. Completion of first timepoint achieving the targeted patient cohort through the Estonian Biobank, and initiation of first timepoint for the TUM-led study, which has been expanded to a multi-center study;
4. Integration of omics profiles, optoacoustic (RSOM) dynamic and static data (images and raw data), and advancing pipelines that will be used to refine and validate the Digital Twin.
5. Close work with an external Ethics Expert and Clinical Research Organization to ensure that all ethics, especially those concerning data protection and potential implications of project results, are understood, discussed and complied with by the Consortium;
6. 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. Frequent and open communication within the General Consortium, Management and Steering Committee (MSC), and Dissemination-Exploitation-Communication Committee (DECC);
2. Management and update of the Dissemination, Exploitation and Communication plan;
3. In-depth market strategy and stakeholder engagement initiated and continuously in progress to ensure clinical uptake and facilitate exploitation of identified IP;
3. Maintaining the project website and social media accounts (Twitter, LinkedIn, BlueSky), with frequent posts and organized Twitter campaigns lining up with important international awareness days;
4. Publication of nine peer-reviewed papers (6 in RP3, including one in Nature) and extensive participation in workshops and conferences by consortium members;
5. Participation in public outreach events and through media press releases ; and,
6. Collaboration with Complementary Grants and joint (1st) International Symposium for Digital Twins in Healthcare in 2024.
In the final stage of the project, the project will focus on continuing to integrate biomarker identification with deep molecular phenotyping in correlation studies and begin assessing disease progress with the start of the second timepoint of the clinical trials.
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.