Leo Anthony Celi, MD, MSc, MPH
Dr. Celi is a clinical research director and principle research scientist at the Laboratory of Computational Physiology at the Massachusetts Institute of Technology (MIT). His group created and maintains the Medical Information Mart for Intensive Care (MIMIC) database with aims of bringing clinicians and data scientists together to support research using data collected in the intensive care unit. This public-access database allows free access to clinical data from over 30 countries under a data use agreement, with the goal of building an international collaborative research community around health data analytics. Dr. Celi also founded and is the co-director of Sana, a cross-disciplinary organization at MIT whose purpose is to improve health outcomes in low- and middle-income countries using information technology. Sana has received the mHealth Alliance Award from the United Nations Foundation and the Wireless Innovation Award from the Vodafone Foundation in 2010.
Adam Renslo, Ph.D.
Dr. Renslo serves as an associate professor in the Department of Pharmaceutical Chemistry and an associate director at the Small Molecule Discovery Center at University of California, San Francisco (UCSF). Dr. Renslo received his Ph.D. in Organic Chemistry at the Massachusetts Institute of Technology in 1998. He then took a postdoctoral position at The Scripps Research Institute. Dr. Renslo worked at Vicuron Pharmaceuticals as a senior scientist then as an associate director for 5 years before moving to a faculty position at UCSF. His research focuses on designing and synthesizing small molecules to modulate disease pathology, such as in cancer, infectious diseases, and neurodegeneration. His lab employs small molecule probes to understand mechanisms underlying artemisinin and related antimalarial drugs. Dr. Renslo is currently inventing and using new platform technologies with the objective of expanding the realm of druggable target space. Some of these technologies include fragment-based approach to target protein-protein interaction interfaces and allosteric modulation of enzymes, using unnatural amino acids to create cell-permeable peptides, and using targeted prodrugs in cancer and infectious diseases.
Bin Chen, Ph.D.
Dr. Chen is an Assistant Professor in the Department of Pediatrics and the Department of Pharmacology & Toxicology at Michigan State University. He received his PhD in Informatics at Indiana University and trained as a postdoc in Bioinformatics at Stanford University. He also worked as a computational scientist at Novartis, Pfizer, and Merck. Dr. Chen’s lab works on developing computational methods and tools to discover new or better therapeutic candidates for cancers, particularly leveraging artificial intelligence to connect different components in translational research. One of his current projects utilize a systems-based approach to identify drugs that reverse molecular state of a disease. Dr. Chen is also currently investigating different deep learning methods that may be used for drug optimization and predictions for drug-induced gene expression.
Klaus Romero, MD, MS, FCP
Dr. Romero serves as an Adjunct Professor for USC School of Pharmacy at the Titus Family Department of Clinical Pharmacy. He is also the director at the Center for Quqntitative Drug and Disease Modeling at USC. Dr. Romero received his M.D. from the Xavierian University School of Medicine and his postgraduate training in clinical pharmacology and epidemiology at Columbian National University. Dr. Romero has developed models to predict safety and efficacy of drugs for Alzheimer’s disease, multiple sclerosis, polycystic kidney disease, and tuberculosis. These models have been accepted by the FDA as fit for purpose models and has significantly improved decisions for moving from phase 2 to phase 3 trials. Dr. Romero also leads development of sophisticated data management and analytics core at USC, which then builds longitudinal models that integrate disease dynamics with exposure-response relationships.
Michael Engles, Ph.D.
Dr. Engles is a Senior Biological Research Scientist at Allergan. He received his Ph.D. in Psychology from University of Georgia. Prior to joining Allergan, he was an Adjunct Associate Professor at University of Kansas and an Assistant Professor at University of Georgia. Dr. Engles’ research revolves around resolving the challenges in the disconnect between pre-clinical and clinical outcomes using predictive modeling software. He works with partners in the clinic, liaisons, marketing professionals, and patients to identify the most clinically relevant disease attributes to guide disease model development. Dr. Engles collaborates with Clinical Development and Regulatory to design robust clinical trials to ensure efficacy, tolerability and endpoint feasibility in these studies.