Large data sets of high relevance to hematologists are being developed at an accelerating pace, as are advanced informatic techniques to assemble, curate, aggregate and analyze them. Machine learning and artificial intelligence hold promise to help clinicians, patients and scientists interpret data and make actionable decisions that will impact the pace of scientific discovery, the translation of discoveries to therapies, and the implementation of individualized “precision” medicine. This session will explore these topics from three different perspectives.
Dr. Mary Horowitz will explore how iterative analysis of systematically collected data can be used to continually refine treatment strategies and to make clinical decisions for individual patients. She will use examples from the Center for International Blood and Marrow Transplant Research, an ongoing clinical outcomes registry spanning over 45 years to demonstrate how this approach transformed selection of unrelated donors leading to marked decreases in transplant-related mortality, and led to development of prediction algorithms for donor availability and transplant outcomes now used to make clinical decisions for individual patients. The potential to increase utility of registries using newer techniques for acquisition and analysis of big data and barriers to adoption will also be discussed.
Dr. Russ Altman will discuss application of computing and informatics technologies to advance understanding of drug action at molecular, cellular, organism and population levels with a focus on how human genetic variation impacts adverse drug responses. He will also discuss how these analytic tools and technologies impact regulatory science and innovation.
Using her experiences in academia, industry, and government, Dr. Amy Abernethy will discuss and explore the impact on therapeutic development and healthcare delivery of increasingly available high quality and near-real-time clinical and biological data. The 21st Century Cures Act established a national agenda to modernize clinical evidence development, including streamlined clinical trial designs powered by informatics, and use of real-world evidence derived from electronic health records and other sources. She will discuss how EHR data linked to next-generation-sequencing can be used to identify new drug targets, define treatment effectiveness, and generate contemporaneous control data for single arm trials, while also supporting real-time healthcare quality monitoring and potentially even new payment models. Dr. Abernathy will also discuss how partners across the ecosystem, including government, technology and biopharma companies, healthcare systems, clinicians, and researchers, are coming together to make this possible; and how FDA can play a critical role to make the ecosystem efficient by setting guideposts and establishing boundaries.
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