Insilico Medicine is one of the leaders in the field of machine learning for drug discovery and aging research. In this workshop, we will discuss how scientists apply novel machine learning models and techniques to accelerate drug discovery and biomarker development—a rapidly emerging field that holds the potential to disrupt the pharmaceutical industry. We will review several impactful research papers, recent advancements, and new challenges in the field. We will also organize a discussion about different representations of molecular entities and available frameworks and benchmarks for de-novo drug discovery problem.
This workshop is a chance to bring machine learning, chemistry, and bioinformatics researchers together to discuss challenging problems of Drug Discovery and Biomarker Development.
14:00-14:30
Alex Zhebrak, Insilico Medicine
Introduction to Insilico Medicine and machine learning for drug discovery
14:30-15:00
Thomas Kipf, University of Amsterdam
Structured deep models: Deep learning on graphs and beyond
15:00-15:30
Benjamin Sanchez-Lengeling, Harvard University
</p>
<p>15:30-16:00
Polina Mamoshina, University of Oxford
Machine learning for biomarkers of drug responses and human aging</p>
<p>16:00-16:30
Coffee Break</p>
<p>16:30-17:30
Daniil Polykovskiy, Insilico Medicine
Generative models for drug discovery</p>
<p>17:30-18:10
Alex Zhavoronkov, Insilico Medicine
Fight Aging to Defeat Cancer</p>
<p>18:10-18:30
Open Discussion</p>
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