insitro, a machine learning-driven drug discovery and development company, today announced the formation of a scientific advisory board (SAB) composed of industry leaders in their respective focus areas. insitro’s SAB brings broad expertise across 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 insights and guidance into the advancement of insitro’s technologies and development programs.

“insitro was founded with a vision of transforming drug discovery and development by leveraging machine learning and data at scale,” said Daphne Koller, Ph.D., founder and chief executive officer of insitro. “This endeavor requires that we combine diverse capabilities at the cutting edge of science and technology, putting them together in new ways. To support us on this journey, we are fortunate to have assembled an SAB comprising an incredible group of experts, who each bring unparalleled knowledge in their respective fields. They will play an active and integral role in helping us chart our path and in the advancement of our technologies and drug development programs, advising both company leadership and colleagues across the entire organization. We look forward to partnering with them as we continue to advance our platform development and drug discovery efforts.”

The founding members of insitro’s SAB by scientific area are:

Statistical and Translational Genetics

• Sir John Bell, M.D., is Regius Professor of Medicine at Oxford University and was the founder of the Wellcome Trust Center for Human Genetics. He is an advisor for public and private sector bodies responsible for biomedical research in Canada, Sweden, Denmark, France, Singapore and the UK, and is a founder 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 research programs in genetics and genomics and in the development of a clinical research program in the UK, and pioneered multiple high-throughput genomic methodologies in biomedical science, 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 Medical and Population Genetics Program and Center for Mendelian Genomics, which has sequenced and analyzed genomic data from over 10,000 individuals 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 data set of human exome and genome sequence data, which has collated data from over 140,000 sequenced individuals.
• George Davey Smith, M.D., DSc, FRS, is a professor of clinical epidemiology at the University of Bristol. Dr. Davey Smith’s work has concentrated on improving causal inference in observational research, through developing methods such as use of what are now called ‘negative controls,’ the use of cross-context comparisons, sensitivity analyses, unobtrusive data collection methods and randomized trials in thought-to-be difficult situations. He is probably best known for pioneering the approach of using germline genetic variants to investigate modifiable causes of disease (‘Mendelian randomization’), and has developed several extensions of the basic method, and contributed to its application in many settings.

Cellular Engineering and Disease Modeling

• David R. Liu, Ph.D., is the Richard Merkin Professor and director of the Merkin Institute of Transformative Technologies in Healthcare, vice chair of the faculty at the Broad Institute of Harvard and MIT, the Thomas Dudley Cabot Professor of the Natural Sciences at Harvard University, and a Howard Hughes Medical Institute (HHMI) investigator. He is a founder 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. He is known for pioneering technologies such as CRISPR, base editing and prime editing, continuous biomolecule evolution technologies and DNA-templated synthesis.
• Dana Pe’er, Ph.D., is the 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. Her work combines single cell technologies and machine learning to address fundamental questions in cancer, immunity and development. She is known for her pioneering contributions to the foundations of single cell data analysis. Her primary research focuses on the mechanisms of cellular plasticity, by which cells reach healthy and aberrant fates, within their tissue context.
• Oliver Stegle, Ph.D., is professor of Computational Genomics at Heidelberg University, head of the Computational Genomics and Systems Genetics Division at the German Cancer Research Center (DKFZ) and group leader at EMBL in Heidelberg, Germany. He focuses on computational methods to unravel the genotype–phenotype map on a genome-wide scale using statistical inference, machine learning and computational biology. He has pioneered computational methods for integrating large and heterogeneous datasets 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 a founder of Locanabio, Eclipse Bioinnovations, Enzerna, Proteona and Trotana. Dr. Yeo is a computational and experimental scientist in the areas 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 cellular homeostasis, development and neurodegenerative disease.

Molecular Design and Machine Learning

• Tommi Jaakkola, Ph.D., is the Thomas Siebel Professor of Electrical Engineering and Computer Science and the Institute for Data, Systems, and Society at the MIT Computer Science and Artificial Intelligence Laboratory. His research covers theory, algorithms, and applications of machine learning, from statistical inference and estimation to natural language processing, computational biology, as well as machine learning for chemistry.

Therapeutic Advisors

• Scott L. Friedman, M.D., is the dean for Therapeutic Discovery and chief of the Division of Liver Diseases, at the Icahn School of Medicine at Mount Sinai. His research pioneered the understanding of 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 scar production in the liver.
• Giovanna Mallucci M.D., Ph.D., is a principal investigator at Altos Labs Cambridge Institute of Science (UK). She was previously van Geest Professor of Clinical Neurosciences at the University of Cambridge and Center Director of the UK Dementia Research Institute. She has led pioneering and paradigm-shifting work on common pathogenic mechanisms in neurodegeneration and dementia, including the role of the unfolded protein response in Alzheimer’s disease. Her work combines clinical practice in dementia and research on mechanisms of synapse regeneration to prevent neurodegeneration and of shared stress pathways to provide neuroprotection.
• Roger M. Perlmutter, M.D., Ph.D., is CEO and chairman of Eikon Therapeutics, Inc., and a member of insitro’s Board of Directors. 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 dozen other drugs and vaccines that address 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 multiple new drugs in the areas of oncology, endocrinology, hematology, inflammation and osteoporosis. Prior to his career in biopharma, Dr. Perlmutter was a professor in the departments of immunology, biochemistry and medicine at the University of Washington, Seattle.

About insitro

insitro is a data-driven drug discovery and development company using machine learning and data at scale to transform the way that drugs are discovered and developed for patients. insitro is developing predictive machine learning models to discover underlying biologic states based on human cohort data and in-house generated cellular data at scale. These predictive models are being brought to bear on key bottlenecks in pharmaceutical R&D to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of biologic insights and molecules in metabolism and neuroscience. Since formation in mid 2018, insitro has raised over $700 million from top tech, biotech, and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit the company’s website at www.insitro.com.

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