Speaker Profile
Ph.D., Director and Principal Diagnostic Scientist, Precision Medicine Laboratories at AstraZeneca
Biography
James leads the search for, and development of, innovative diagnostic assays and technologies for MDx, TDx and PDx working through collaborations and partnering with academia and industry. Previously he led the Genomics Core at Cambridge University’s Cambridge Institute, he is seconded with Genomics England, and has consulted widely on genomics technologies. He has worked with genomics technologies, especially NGS, for the past 10-15 years. He was awarded PhD at UEA. He has co-authored multiple influential papers in cancer genomics including one of the largest genomic studies of Breast Cancer (Nature 2012), some of the first reports of ctDNA liquid biopsy: using amplicons (STM 2012) or exomes (Nature 2013) and developed a sWGS CNV pipeline for exome sequencing (Cell 2016). He has been highly involved in the NGS community and writes a very well received blog and is considered a thought-leader in the field.
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.
