HARNESSING THE INTERSECTION OF EPIDEMIOLOGIC AND GENETIC EVIDENCE

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1 Lisa Torosyan CDRH/FDA MDEpiNet Oct 19, 2017 HARNESSING THE INTERSECTION OF EPIDEMIOLOGIC AND GENETIC EVIDENCE 1

2 Study Endpoints and Analytics as the Main Prerequisites for Effective Evaluation of Medical Devices throughout the TPLC Indicative of real-world performance: - quantitative - continuous - patient-centric (individual susceptibility, subclinical events) - Linkage of disparate data - Multivariate analysis - High-dimensional feature extraction - Interpretable visualization of complex results 2

3 Use of RWE for Supporting Biomarker-based Precision Medicine Applications Use of RWE to Support Regulatory Decision-Making for Medical Devices (Guidance from CDRH and CBER, Aug 2017): RWE for understanding medical device performance at different points in the TPLC Purposes for which RWE may be used: to identify, demonstrate, or support the clinical validity of a biomarker to update the labeling and indications for use (eg, more precisely identified target subpopulations) 3

4 Big Data Analytics tools Registry-based epi evidence for hypothesis generation Genomic evidence from target subpopulations 4

5 Precision Medicine Needs: from addressing individual susceptibility to establishing subpopulation-centric phenotypes Requirements for biomarkers that can be used as reliable study endpoints in clinical and regulatory settings: Indicative of in vivo device performance Suitable for labeling needs such as adequately defined Intention-to-Treat subpopulations Capable of predicting and monitoring adverse outcomes in individual patients as well as in patient subgroups (eg, sex/race-stratified subpopulations) 5

6 Initial Selection of Biomarker Candidates during Discovery: an Evidentiary Bottleneck that is Often Overshadowed by Subsequent Confirmatory Challenges Basic Discovery Data Collection Statistical Analysis Selection of biomarker candidates Analytical and Clinical Verification of pre-selected candidates: Validation & - High-Throughput Analysis - RCT Qualifica tion NEW EVIDENTIARY APPROACHES Regulatory approval Infrastructure Implemen Healthcare changes tation for optimizing discovery of biomarkers prior to confirmatory studies: Selection of biomarker candidates guided by epidemiologic / clinical evidence Use of unconventional advanced analytics In silico analysis of biological and clinical plausibility of the pre-selected candidates 6

7 In silico Translational Research Framework (DEPI/CDRH): the Need for NEW Analytic Approaches for Simultaneous Synthesis of Disparate Evidence Monodisciplinary Results separated silos by decades Genetic Demographic Markers Factors Adverse Outcomes SYNTHESIZED Epidemiologic and Genetic EVIDENCE 7

8 Clustering Heatmap Presenting Correlations between SNP Alleles and Periprosthetic Osteolysis in Sex/Race-stratified Subjects with Hip Replacement (Image generated using HIVE High-performance Integrated Virtual Environment) Male PO subcluster of SNPs (x5) with the increased frequencies of putative risk alleles Female PO subclusters of SNPs (x7) with the decreased frequencies of putative protective alleles 8

9 In silico Research Principles for Advancing Evidence Synthesis Apply Systems Biology/Medicine approach to integrate multidisciplinary evidence, specifically harnessing the advances in Translational Epidemiology, Genetics/Genomics, and Bioinformatics Extract new information by: using unconventional data sources such as open-access omic knowledgebases reanalyzing raw pre-existing data Incorporate pre-clinical and clinical findings applying multidirectional data integration and using disparate data types from multiple sources Data analysis and interpretation using new Bioinformatics-based approaches including causal analytics and other modeling and simulation tools Elicit and test new hypotheses via synthesis and cross-validation of different evidence streams Re-utilization of pre-existing data: the gift that keeps on giving 9

10 In silico Translational Research Framework (DEPI/CDRH): Potential for Precision Medicine and Other Health Care Applications EPIDEMIOLOGICAL EVIDENCE from retrospective analysis of registrybased or other observational data Discovery of Biomarkers and Risk Factors Based on In Silico Synthesized Epi-Gen Evidence GENETIC EVIDENCE based on open-source and other available omic data from prior - human and animal - studies 10

11 Precision Medicine Informatics: an Example of In Silico Discovery of Ventilation-related Candidate Biomarkers Torosyan et al. JAMIA

12 Current DEPI/CDRH Projects on In Silico Discovery of Device-Related Biomarkers in Collaboration with MCRI, NHGRI-eMERGE, TMJA, In Silico Integration of Epidemiologic and Genetic Evidence on Sex/RaceRelated Modifying Effects on Hip Arthroplasty Outcomes (ICPE ; manuscript in submission) Pipeline: Temporomandibular Disorders and Temporomandibular Joint Arthroplasty (TMD/TMJA) Intrauterine Devices and Hysteroscopic Sterilization 12

13 SUMMARY: Expected Benefits from In Silico Research with Health Care Applications Ø Identify and adjudicate biomarker-based study endpoints: Ø Pertaining to devices and biomaterials Ø Applicable in pre-clinical testing and clinical studies Ø Enhance device performance by implementing new biomarker-based approaches to biomaterial/device evaluation : Ø Model real-world performance in patient segments Ø Fine-tune device labeling for different Intention-to-Treat subpopulations Ø Predict adverse events and determine scalable actions for improving treatment outcomes on individual and population levels: Ø Identify vulnerable individuals with enhanced susceptibility Ø Categorize risk factors in sex/race-stratified subpopulations Ø Implement individualized surveillance based on the predicted risk Ø Explore demographics-related modifying effects, distinguishing between health disparities due to genetic vs. socioeconomic factors 13

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