プレナリー基調講演プログラム

Discovery on Targetのプレナリー基調講演プログラムには世界中の業界関係者が参加します。創薬の専門家のコミュニティ全体が一堂に会して、この分野の著名人から全体像の視点、革新的な技術、示唆に富む動向を学ぶことができる、イベントの両側面を橋渡しする唯一の機会です。

This year’s program features three expert speakers and runs on Wednesday, September 27 from 10:40 am - 12:25 pm EDT.

9月27日（水）

10:55 The New Science of Therapeutics
Jay E. Bradner, MD, Physician Scientist, Former President, Novartis Institutes for BioMedical Research, Inc.
I will share reflections on how new paradigms in the science of therapeutics are creating opportunities to approach historic challenges in medicine. Specifically, I will share approaches to targeting transcription factors and discuss how modularity is a paradigm for next-generation low-molecular weight and biological therapeutics. Finally, I will offer reflections on drug development and the fitness, opportunities, and challenges of the biomedical ecosystem.

11:40 Accelerating Drug Discovery Using Machine Learning and Cell Painting Images
Anne E. Carpenter, PhD, Senior Director, Imaging Platform & Institute Scientist, Broad Institute
Shantanu Singh, PhD, Senior Group Leader, Machine Learning, Imaging Platform, Broad Institute
Microscopy images can reveal whether a cell is diseased, is responding to a drug treatment, or whether a pathway has been disrupted by a genetic mutation. In a strategy called image-based profiling, often using the Cell Painting assay, we extract hundreds of features of cells from images. Just like transcriptional profiling, the similarities and differences in the patterns of extracted features reveal connections among diseases, drugs, and genes.

PLENARY KEYNOTE BIOGRAPHIES
基調講演者略歴

Jay E. Bradner, MD, Physician Scientist, Former President, Novartis Institutes for BioMedical Research, Inc.
Dr. James (Jay) Bradner, MD, served as President of the Novartis Institutes for BioMedical Research (NIBR) and Member of the Executive Committee of Novartis Inc. 2016-2022. Prior to joining Novartis, Dr. Bradner was on the faculty of Harvard Medical School in the Department of Medical Oncology at the Dana-Farber Cancer Institute in the United States from 2005 through 2015. He is a co-founder of five biotechnology companies and has authored more than 180 scientific publications and 30 US patent applications. Dr. Bradner is a graduate of Harvard University and the University of Chicago Medical School. He completed his residency in medicine at Brigham and Women’s Hospital and his fellowship in medical oncology and hematology at the Dana-Farber Cancer Institute. He has been honored with many awards and was elected into the American Society for Clinical Investigation in 2011 and the Alpha Omega Alpha Honor Medical Society in 2013.

Anne E. Carpenter, PhD, Senior Director, Imaging Platform & Institute Scientist, Broad Institute
Dr. Anne E. Carpenter is an Institute Scientist at the Broad Institute of Harvard and MIT. Her research group develops algorithms and strategies for large-scale experiments involving images. The team’s open-source CellProfiler software is used by thousands of biologists worldwide and their Cell Painting assay has been adopted throughout the pharma industry to accelerate drug discovery. Her PhD is in cell biology from the University of Illinois, Urbana-Champaign and her postdoc in high-throughput image analysis was at the Whitehead Institute for Biomedical Research and MIT’s CSAIL (Computer Sciences/Artificial Intelligence Laboratory). Dr. Carpenter has been named an NSF CAREER awardee, an NIH MIRA awardee, a Massachusetts Academy of Sciences fellow (its youngest at the time), and is listed in Deep Knowledge Analytics’ top-100 AI Leaders in Drug Discovery and Advanced Healthcare.

Shantanu Singh, PhD, Senior Group Leader, Machine Learning, Imaging Platform, Broad Institute
Dr. Shantanu Singh is a senior group leader in the Imaging Platform at the Broad Institute. He leads a data science group that develops computational and statistical methods to create fingerprints of genes, chemicals, and diseases from microscopy images of cells. Using assays like Cell Painting that capture a broad range of their morphological properties, cellular populations are characterized at single-cell resolution to discover similarities and differences among treatments. This work has the potential to transform how both the targets and therapies for disease are identified. After completing his PhD at Ohio State in computer science, Shantanu joined the Imaging Platform, inspired by the group’s vision to make cell morphology as computable as genomes. He has previously worked in research groups at Mercedes-Benz R&D, GE Global Research, and Lawrence Livermore National Laboratory, where he applied computer vision and machine learning techniques to a wide range of problems in road safety, cell biology, and geospatial imaging.