Discover Lessons Learned from Real World Applications & Practical Implementations of AI and Machine Learning to Improve Your Target Identification and Drug Discovery Efforts
The AI-ML: Drug Discovery Summit – the industry’s leading R&D data event – returns in 2020, with brand-new case studies, cutting-edge discussions, and industry-shaping debates to help you overcome your data quality, standardization, and sharing challenges.
Across 3 days of learning with key decision makers from pharma, biotech drug developers and technology companies, this summit will provide the roadmap to augmented R&D decision making with reduced failure rates, increased speed and improved margins.
Join us in San Diego to improve your:
- Target, pathway and molecule selection – identify which will treat individual disease indications better
- Predictive preclinical models – know from the beginning how drug candidates will react when administered to in vivo and in vitro models
- Translational research – use predictive analytics and augmented intelligence to harness available data for earlier decision making – from early biomarker identification to in vivo and in vitro mode selection
Join 80+ like-minded peers to overhaul R&D and reflect on the lessons learned from the successes and mistakes made from a year of implementation and utilization.
Walk away with a blueprint for more accurate, more efficient and more effective R&D processes.
Download the Full Event Guide to get a taste of the real-world case studies you'll be joining at the conference.
Expert Speakers at the 3rd AI-ML Drug Discovery & Development Summit Include:
Senior Director, Head of ECD Informatics
Professor - Medicine & Chief of Translational Informatics Division & Internal Medicine
University of New Mexico
Senior Director - Biomedical Informatics & Global Head of Computational Biology Biomedical Informatics
ATOM, Director - Business Development & Operations
University of Califorina, San Francisco
PhD Candidate, Pande and Leskovec Groups