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Opening Plenary Session 2020 Wallace H. Coulter Lectureship Award The Path to Indispensability for Laboratory Scientists: Becoming the Most Important Members of the Diagnostic Healthcare Team
Michael Laposata, MD, PhD Professor and Chair of the Department of Pathology at the University of Texas Medical Branch-Galveston
Clinical laboratory testing has become enormously complex and expensive. Many healthcare providers trying to establish their patient’s diagnosis may find it difficult to choose the right tests or interpret the results correctly. Laboratory scientists can no longer be satisfied with providing accurate test results. We must also provide guidance regarding test selection and test result interpretation. Stepping up and claiming our role in these important areas will help optimize test utilization, shorten length of stay, and reduce both morbidity and mortality due to diagnostic error. It will also make us indispensable members of the healthcare team. In this talk, Dr. Laposata will review the evolution of laboratory medicine and describe a plan to overcome barriers to our ability to function as true practitioners. He will draw on his 35-plus years of personal experience advocating for systematic consultation on test selection and result interpretation. His model of diagnostic management teams, using expert-driven algorithms and collaborative review of both the test results and the patient’s medical record, is the basis for his proposed plan for our future.
Metabolic Reprogramming in Human Cancer: Insights Into Mechanisms and Opportunities for New Therapies Ralph DeBerardinis, MD, PhD Chief, Division of Pediatric Genetics and Metabolism, University of Texas Southwestern Medical Center
Tumor cells often have abnormal metabolic processes as part of their cellular transformation, and also face a hostile microenvironment. Alterations in the metabolic network allow cancer cells to survive and grow. Some alterations in their metabolic profile provide better access to, and utilization of, key nutrients. Investigation of these changes using metabolomics and intra-operative infusions with labeled nutrients in human solid tumors can reveal novel metabolic dependencies, and lead to novel approaches to therapy.
T Cell Therapies for Cancer: CAR-Ts and Beyond Catherine Bollard, MD, MBChB Director, Center for Cancer and Immunology and Director, Program for Cell Enhancement and Technologies for Immunotherapy, Children’s Research Institute
Immunotherapy currently plays an important role in the treatment of patients with cancer. Approaches include monoclonal antibodies, vaccines, and cellular therapy. T cell therapies, in particular, show great promise for enhancing clinical responses and overall survival. T cells can actively migrate into tumors, be engineered to resist strategies used by tumors to evade immune surveillance, and recruit other components of the immune system to help target tumor cells. This session will present an overview of the use of T cells to generate effective anti-cancer therapies. These include T cell engineering using chimeric antigen receptors (CARs) and artificial T-cell receptors, as well as ex vivo expansion of antigen-specific T cells targeting viral and/or nonviral tumor-associated antigens.
Between Scylla and Charybdis: Navigating the Complex Waters of Machine Learning in Laboratory Medicine Ulysses G. J. Balis, MD, Fellow AIMBE Professor Pathology and Director, Division of Pathology Informatics, University of Michigan
Machine learning and artificial intelligence hold significant potential to enhance the practice of laboratory medicine, but validating and implementing big data analytic solutions into clinical care has proven to be a substantial challenge. This fact is borne out by the relative paucity of computational assays currently being offered as routine tests. This session will describe a 10-year experience at University of Michigan of developing, validating, and implementing machine-learning based tests, using the currently offered computational assay for 6-thioguanine nucleotide metabolites as the example. Key topics to be covered include the selection of optimal machine-learning approaches, validation issues including false discovery and assay failure, and provisions for seamless integration into the routine laboratory information system process of test ordering and result reporting.
Precision Medicine: Better Prevention, Diagnosis, and Treatment for All of Us Anastasia Wise, PhD Program Director, Division of Genomic Medicine, National Human Genome Research Institute (NHGRI), NIH
Longitudinal cohort studies help to investigate the causes of disease, identify risk factors, and determine the effects of treatment on health outcomes. However, many cohorts face challenges with size, diversity, and comprehensiveness of information, hindering their ability to provide benefit to all communities. Launched in 2018, a central goal of the All of Us Research Program is the creation of a cohort of at least one million persons in the United States. Electronic health records, biospecimens, and other measurements are provided by participants, including groups historically underrepresented in biomedical research, to create a data repository following the health and outcomes of participants for 10 years or more. This presentation will outline the status of the All of Us Research Program and present a timeline for its goals of accelerating health research and medical breakthroughs, and enabling individualized prevention, treatment, and care for all of us.
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