Michelle Gill - Artificial Intelligence Driven Drug Discovery
Artificial Intelligence Driven Drug Discovery
By Michelle Gill
Abstract:
At BenevolentAI, we use machine learning to facilitate drug discovery. This talk will introduce the drug discovery process and explain how machine learning maps to these stages. We will then cover challenges specifically related to using machine learning for scientific discovery, and conclude with a specific application of reinforcement learning to generate novel compounds in silico.
Bio:
Michelle Gill is a Senior Data Scientist at BenevolentAI, an AI healthcare company with capabilities from early discovery to late stage clinical development. At BenevolentAI, she utilizes data science and machine learning to facilitate both the target identification and lead optimization stages of drug discovery. Previously, Michelle was a deep learning consultant within NVIDIA’s Professional Services Group where she assisted clients in the pharmaceutical and materials science domains develop proof of concept deep learning pipelines. As a scientist at the National Cancer Institute, she developed software utilizing machine learning and compressed sensing algorithms. She holds a PhD in Molecular Biophysics and Biochemistry from Yale University and completed a postdoctoral research fellowship at Columbia University Medical School, where she developed and applied biophysical methods to study the function of cancer-associated enzymes. Michelle's scientific and machine learning work has been published in peer reviewed journals and covered by the press.
Twitter: @modernscientist
Presented at the 2019 New York Conference (May 10th, 2019)
Видео Michelle Gill - Artificial Intelligence Driven Drug Discovery канала Lander Analytics
By Michelle Gill
Abstract:
At BenevolentAI, we use machine learning to facilitate drug discovery. This talk will introduce the drug discovery process and explain how machine learning maps to these stages. We will then cover challenges specifically related to using machine learning for scientific discovery, and conclude with a specific application of reinforcement learning to generate novel compounds in silico.
Bio:
Michelle Gill is a Senior Data Scientist at BenevolentAI, an AI healthcare company with capabilities from early discovery to late stage clinical development. At BenevolentAI, she utilizes data science and machine learning to facilitate both the target identification and lead optimization stages of drug discovery. Previously, Michelle was a deep learning consultant within NVIDIA’s Professional Services Group where she assisted clients in the pharmaceutical and materials science domains develop proof of concept deep learning pipelines. As a scientist at the National Cancer Institute, she developed software utilizing machine learning and compressed sensing algorithms. She holds a PhD in Molecular Biophysics and Biochemistry from Yale University and completed a postdoctoral research fellowship at Columbia University Medical School, where she developed and applied biophysical methods to study the function of cancer-associated enzymes. Michelle's scientific and machine learning work has been published in peer reviewed journals and covered by the press.
Twitter: @modernscientist
Presented at the 2019 New York Conference (May 10th, 2019)
Видео Michelle Gill - Artificial Intelligence Driven Drug Discovery канала Lander Analytics
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Machine learning in drug discovery: what can go wrong? — Vikram SundarArtificial Intelligence and Machine Learning: Innovations in Clinical Trial Data AutomationArtificial intelligence and algorithms: pros and cons | DW Documentary (AI documentary)Alan Turing and the Birth of Artificial Intelligence - Dermot Turing, at USIAI for Drug Design - Lecture 16 - Deep Learning in the Life Sciences (Spring 2021)Drug Discovery/Medicinal Chemistry at UCLA: Xtandi and OthersDrug Discovery, Biotech, and AI with Alex Zhavoronkov, CEO, Insilico Medicine (CXOTalk #327)SchrödingerDrug discovery and development processThe incredible inventions of intuitive AI | Maurice ContiJim Wells and Michelle Arkin(UCSF) Part 1: Introduction to Drug DiscoveryAWS re:Invent 2019: Enhancing clinical trials with machine learning (LFS203)From idea to medicine | Drug development at RocheMachine Learning: A New Approach to Drug Discovery | Daphne Koller | WiDS 2020Artificial Intelligence Colloquium: Accelerating Chemistry with AIMachine learning for drug designTarget Validation / Biochemical and Cellular Assay DevelopmentMIT Quest for Intelligence Launch: AI-Driven Drug DiscoveryFrom the Human Genome Project to Precision Medicine: A Journey to Advance Human Health - Eric GreenUsing AI to Accelerate Drug Discovery // Jerome Pesenti, BenevolentAI (FirstMark's Data Driven)