CARTA Fall 2019 IAB Guest Speakers
Machine learning in immunological synapse research
Human immune system consists of a network of billions of independent, self-organized cells that interact with each other to form a highest intelligence. Artificial intelligence (AI) is being used in immunological research. Machine learning (ML) is an AI tool that can process huge data and generate models for immune system and immunological research. One of the most exciting, recent breakthroughs in immunological research is cancer immunotherapy. Specifically, one such therapy involves engineering immune cells to express chimeric antigen receptors (CAR), which combine tumor antigen specificity with immune cell activation in a single receptor. The adoptive transfer of these CAR-modified immune cells (especially T cells, CAR T) into patients has shown remarkable success in treating multiple refractory blood cancers. To improve their efficacy and to expand their applicability to other cancer types, different CARs with different modifications are actively optimized. However, predicting and ranking the efficacy of different CAR T cell products are limited by the current, time-consuming, costly, and labor-intensive conventional tools used to evaluate efficacy. In this talk, potential collaboration between computer science and immunology will be discussed.
About Dr. Liu:
Dongfang Liu, PhD recently joined the Department of Pathology, Immunology & Laboratory Medicine and the Center for Immunity and Inflammation as an Associate Professor. In 2012, Dr. Liu was recruited to Baylor College of Medicine as a tenure-track Assistant Professor in the Department of Pediatrics and Department of Pathology & Immunology, before joining Houston Methodist Hospital (a teaching hospital affiliated with Weill Cornell Medical College) as an assistant professor in 2015. In 2018, Dr. Liu was promoted to an Associate Professor in Houston Methodist Research Institute. Dr. Liu did his postdoctoral training on natural killer (NK) cells at the National Institute of Allergy and Infectious Diseases (NIAID) in National Institutes of Health (NIH) from 2005 to 2011. After completing the postdoctoral training, he joined Ragon Institute of MGH, MIT and Harvard in 2011 as a senior research scientist, where he worked on HIV-specific CTL dysfunction with a focus on PD-1 in HIV-specific CTLs. His current research is primarily focused on the immunobiology of chimeric antigen receptor (CAR) T and NK cells, immunoreceptors, CAR immunotherapy, and HIV-specific CTLs in chronic HIV and its related malignancies, with a focus on immunological synapse biology and its clinical applications. His research is supported by several NIH grants, including an R01 and three R21 grants. For more info, please check: http://njms.rutgers.edu/departments/labs/dongfang/
A New Era of Analytics in Medicines Development
Recent advances in developing ground-breaking therapies such as immune-oncology, CAR T cells and gene editing with CRISPR are promising cures for deadly and previously incurable diseases. To achieve this promise we have to change how we develop new treatments and transition to personalized medicines. Challenges of finding suitable patients for rare disease studies, ability to process vast and complex data streams from wearable devices, virtualization of clinical trials, and need to monitor and protect patients from unknown adverse reactions are just a few examples where data analytics is not just a useful tool, but a primary enabler of a successful medicine development.
About Dr. Lobanov:
Dr. Lobanov is Vice President and Global Head of Xcellerate® Informatics at Covance. He joined Covance in 2013 to establish a practice of data science and employ best practices in data integration, data warehousing and visual analytics to improve quality, speed, and efficiency of clinical development while providing differentiated services to pharmaceutical clients. Dr. Lobanov oversees development, implementation and commercialization of the award-winning Xcellerate® technology products for Covance’s clinical development and clinical testing businesses as well as their clients, investigators, and patients. He supervises a global team of data scientists, software engineers, database developers and IT professionals engaged in the design, architecture, development, and support of innovative analytics and technology solutions aimed to address emerging industry needs for data-driven, near real-time and intelligent decision support in clinical development.
Prior to joining Covance, Dr. Lobanov served as Senior Director of Translational Informatics at Janssen Research & Development LLC where he was responsible for the design and implementation of innovative solutions and systems for research data management and predictive analytics. As part of the cross-functional team, he lead the development of the industry-first scientific data warehouse for pharmaceutical research data (ABCD) and pioneering data mining and visualization application for rapid and domain-aware analysis of biological activity and chemical structure data (3DX). He also lead the Health Informatics Center or Excellence and partnered with the Epidemiology and Neuroscience teams to implement novel approaches for observational data mining and biomarker discovery. As a representative from Janssen R&D, he served on the Private Partner Scientific Board for the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Dr. Lobanov started his career as a research scientist at 3-Dimensional Pharmaceuticals, Inc. working on computational algorithms for virtual screening and lead optimization in drug discovery.
Dr. Lobanov received BS/MS in chemistry from Lomonosov Moscow State University and PhD in computational chemistry from the University of Tartu. He completed his post-doctoral training at the University of Florida with Professor Alan R. Katritzky where he developed a novel application for quantitative modeling of structure-activity relationships (CODESSA) which has been copyrighted by the University of Florida and commercialized. Dr. Lobanov is an author of more than forty peer-reviewed publications and several patents and is a frequent presenter at scientific and commercial conferences.