Date/Time
Date(s) - 21 Apr 2020 - 22 Apr 2020
12:00 pm - 3:30 pm
Location
Pfizer
Categories
Organising Committee
Justin Boyd (Pfizer), Dominic Clark (Pistoia Alliance), Holger Hoefling (Novartis), Sukru Kaymakcalan (AbbVie), Brian Martin (AbbVie), Zahid Tharia (Pistoia Alliance),
Background and Motivation
Continuous improvement in methods of drug discovery is a key driver for the pharmaceutical industry. Machine Learning has already had some success and promises further developments as the quality and breath of data sets are increased (Vamathevan et al. (2019) NRDD, DOI: 10.1038/s41573-019-0024-5).
Better models of diseases and assay methods present an opportunity for generating more comprehensive data sets with higher dimensionality through deep phenotyping. The challenge is then to make sense of this higher dimensional data through AI/ML so that it can most effectively be leveraged in drug discovery programmes.
The focus of this symposium will be on applying AI/ML in high-dimensional data analysis for Drug Discovery and design of personal medicine stratified clinical trials.
The new methods and approaches will be exemplified through presentations from key opinion leaders, industry case studies and new innovative approaches.
Relation to other Pistoia Alliance activities
The symposium will have links to the Pistoia Alliance community of interest in Cell Painting and the Pistoia Alliance Centre of Excellence for AI/ML in Life Sciences.
Scope and coverage
The key topic areas to be covered at the symposium is approaches of ML in Drug Discovery: biomarker, new targets and new drugs with a focus on high dimensional data analysis.
Anticipated outcomes
The Symposium will showcase best practice and promote knowledge exchange between speakers and delegates through case studies, discussion and panel sessions. The Symposium will facilitate enhanced discussion around Pistoia Alliance Cell Painting CoI and AI/ML CoE.
The symposium will have links to the Pistoia Alliance community of interest in Cell Painting and the Pistoia Alliance Centre of Excellence for AI/ML in Life Sciences.