SOUTH SAN FRANCISCO, Calif., May 2, 2022–(BUSINESS WIRE)–insitro, a drug discovery and development company focused on machine learning, today announced the formation of a Scientific Advisory Board (SAB) comprised of industry leaders in their focus areas respective. insitro’s SAB brings extensive expertise in the areas of gene editing, genetics and genomics, machine learning, molecular design, and liver and central nervous system diseases. SAB members will work closely with the insitro team to provide insight and advice on the advancement of insitro’s technologies and development programs.
“insitro was founded with a vision to transform drug discovery and development by leveraging machine learning and large-scale data,” said Daphne Koller, Ph.D., founder and CEO of insitro . “This endeavor demands that we combine diverse capabilities at the cutting edge of science and technology, bringing them together in new ways. To support us on this journey, we are fortunate to have assembled an SAB comprised of an incredible group experts, who each bring unrivaled knowledge in their respective fields, who will play an active and integral role in helping us chart our course and advance our technologies and drug development programs, advising both the management of company and colleagues across the organization. We look forward to partnering with as we continue to advance our platform development and drug discovery efforts.”
The founding members of the SAB de l’insitro by scientific field are:
Statistical and translational genetics
Sir John Bell, MD, is Regius Professor of Medicine at the University of Oxford and was the founder of the Wellcome Trust Center for Human Genetics. He is an advisor to public and private sector bodies responsible for biomedical research in Canada, Sweden, Denmark, France, Singapore and the United Kingdom, and is one of the founders of Oxagen, Avidex and PowderJect. He chairs the board of Immunocore and previously served on the board of Roche. Dr. Bell has been extensively involved in the development of genetics and genomics research programs and the development of a clinical research program in the UK, and has pioneered several high throughput genomic methodologies in biomedical sciences , including structural genomics.
Daniel MacArthur, Ph.D., is Director of the Center for Population Genomics at the Garvan Institute for Medical Research in Australia and previously co-directed the Broad Institute’s Population and Medical Genetics Program and Center for Mendelian Genomics, which sequenced and analyzed genomic data from over of 10,000 people with rare diseases and discovered more than 100 new rare disease genes. He is known for leading the development of the Genome Aggregation Database (gnomAD), the largest and most widely used dataset of human exome and genome sequence data, which has collected data from over 140,000 sequenced individuals.
George Davey Smith, MD, DSc, FRS, is Professor of Clinical Epidemiology at the University of Bristol. Dr. Davey Smith’s work focused on improving causal inference in observational research, developing methods such as the use of what are now called “negative controls”, the use of intercontextual comparisons, sensitivity analyses, discrete data collection methods and randomized trials in situations considered difficult. He is probably best known for pioneering the approach of using germline genetic variants to study modifiable causes of disease (“Mendelian randomization”), and developed several extensions of the basic method and contributed to its application in many contexts.
Cell engineering and disease modeling
David R. Liu, Ph.D., is Professor Richard Merkin and Director of the Merkin Institute of Transformative Technologies in Healthcare, Vice Chairman of Faculty at the Broad Institute of Harvard and MIT, Thomas Dudley Cabot Professor of Natural Sciences at Harvard University, and a Howard Hughes Medical Institute (HHMI) investigator. He is one of the founders of Editas Medicine, Pairwise Plants, Exo Therapeutics, Beam Therapeutics and Prime Medicine. Dr. Liu has led innovation in the areas of genetic engineering, molecular evolution, and DNA-encoded libraries. It is known for pioneering technologies such as CRISPR, core and master editing, continuous biomolecule evolution technologies, and DNA template synthesis.
Dana Pe’er, Ph.D., is Chair of the Computational and Systems Biology Program at the Sloan Kettering Institute and Scientific Director of the Alan and Sandra Gerry Metastasis and Tumor Ecosystems Center. His work combines single-cell technologies and machine learning to answer fundamental questions about cancer, immunity and development. She is known for her pioneering contributions to the foundations of single-cell data analysis. His main research focuses on the mechanisms of cellular plasticity, by which cells reach healthy and aberrant fates, in their tissue context.
Oliver Stegle, Ph.D., is Professor of Computational Genomics at the University of Heidelberg, Head of the Division of Computational Genomics and Systems Genetics at the German Cancer Research Center (DKFZ) and Group Leader at EMBL in Heidelberg, Germany. He focuses on computational methods to unravel the genome-wide genotype-phenotype map using statistical inference, machine learning, and computational biology. He pioneered computational methods to integrate large and heterogeneous data sets across individuals and at the single-cell level.
Gene Yeo, Ph.D., MBA, is a professor of cellular and molecular medicine at the University of California, San Diego (UCSD). He is the founder of Locanabio, Eclipse Bioinnovations, Enzerna, Proteona and Trotana. Dr. Yeo is a computational and experimental scientist in the fields of neurodegeneration, RNA processing, computational biology, and stem cell models. He is a leader in the study of RNA processing and the roles that RNA-binding proteins (RBPs) play in cell homeostasis, development, and neurodegenerative diseases.
Molecular design and machine learning
Tommi Jaakkola, Ph.D., holds the Thomas Siebel Professorship in Electrical Engineering and Computer Science and the Institute for Data, Systems and Society at MIT’s Computer Science and Artificial Intelligence Laboratory. His research focuses on the theory, algorithms and applications of machine learning, statistical inference and estimation to natural language processing, computational biology, as well as machine learning for chemistry. .
Scott L. Friedman, MD, is the Dean of Therapeutic Discovery and Chief of the Division of Liver Diseases at the Icahn School of Medicine at Mount Sinai. His research was the first to understand the underlying causes of scarring or fibrosis associated with chronic liver disease and was among the first to isolate and characterize the hepatic stellate cell, the key cell type responsible for production of scars in the liver.
Giovanna Mallucci MD, Ph.D., is a Senior Researcher at Altos Labs Cambridge Institute of Science (UK). She was previously the van Geest Professor of Clinical Neuroscience at the University of Cambridge and Center Director of the UK Dementia Research Institute. She has led pioneering and groundbreaking work on common pathogenic mechanisms in neurodegeneration and dementia, including the role of the unfolded protein response in Alzheimer’s disease. His work combines clinical practice in dementia with research on mechanisms of synapse regeneration to prevent neurodegeneration and shared stress pathways to provide neuroprotection.
Roger M. Perlmutter, MD, Ph.D., is CEO and President of Eikon Therapeutics, Inc., and a member of the Board of Directors of insitro. He is a highly accomplished industry and academic leader with over 35 years of experience. He was previously Executive Vice President, Merck & Co., and President of Merck Research Laboratories, where he played a key role in the approval and development of the breakthrough immunotherapy treatment Keytruda®, in addition to more than two dozens of other drugs and vaccines that treat neoplastic, cardiovascular, metabolic and infectious diseases. Prior to Merck, Dr. Perlmutter was Executive Vice President and Head of Research and Development at Amgen, where he was responsible for the registration of several new drugs in the areas of oncology, endocrinology, hematology, inflammation and osteoporosis. Prior to his career in biopharmaceuticals, Dr. Perlmutter was a professor in the departments of Immunology, Biochemistry, and Medicine at the University of Washington, Seattle.
About the insitro
insitro is a data-driven drug discovery and development company that uses machine learning and large-scale data to transform the way drugs are discovered and developed for patients. insitro develops predictive machine learning models to uncover underlying biological states based on large-scale human cohort data and internally generated cellular data. These predictive models are applied to key pharmaceutical R&D bottlenecks to advance new targets and biomarkers for patients, design therapies, and inform clinical strategy. insitro advances a 100% owned and partnered pipeline of biological information and molecules in metabolism and neuroscience. Since its inception in mid-2018, insitro has raised over $700 million from leading investors in technology, biotechnology and crossbreeding, and through collaborations with pharmaceutical partners. For more information about insitro, please visit the company’s website at www.insitro.com.
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