Ph.D., Chief Scientist Officer, N-of-One
Sheryl Krevsky Elkin, PhD, is the Chief Scientific Officer at N-of-One. An early member of the N-of-One team, Dr. Elkin has led the interpretation of thousands of patient cases, establishing a rigorous process for the analysis of scientific and clinical evidence and presentation of molecular and clinical evidence to physicians to help guide their therapeutic decisions. Dr. Elkin has taken a lead role in the development of the N-of-One clinical interpretation methodology to support clinicians in identifying therapeutic strategies specific to each patient. Prior to joining N-of-One, Dr. Elkin completed her postdoctoral fellowship at the Massachusetts Institute of Technology’s Center for Cancer Research, where she earned a fellowship from the Leukemia and Lymphoma Society. She earned her doctorate in Biological and Biomedical Sciences from Harvard Medical School and an A.B. in Biology and Music from Amherst College, graduating Phi Beta Kappa and summa cum laude, with High Distinction in Biology.
Session Abstract – PMWC 2019 Silicon Valley
Session Synopsis: Genomics-guided precision medicine has become more common practice for patient screening, disease diagnosis and profiling and treatment decision support in cancer and rare diseases. Yet there continues to be significant variability in the methods for analyzing, interpreting and reporting on genomic testing and most healthcare providers and testing laboratories have yet to integrate important clinical data into their testing protocols, such as stage of disease, prior treatments and outcomes data that can enhance or change the patient profiling or treatment. This panel will discuss the current state of diagnostic and theranostic testing and how Providers, Laboratories, Pharma and Payers can work collaboratively to establish more standardized protocols for the inclusion of RWE into more standardized test interpretation and reporting protocols and how these protocols can result in improved screening, treatment decisions support, patient cohort analytics for drug development, clinical trial design, matching of patients to trials and evidence based reimbursement decisions.