July 16, 2020 — Computational approaches using COVID-19 data can be invaluable in quickly generating insights for drug repurposing, target pathway selection, and many other challenges. In this webinar, QuartzBio’s Renee Deehan will discuss how teams are combining deep biological knowledge with computational and machine learning approaches.
The global pandemic caused by SARS-CoV-2 has resulted in an incredible mobilization of biopharma resources and attention.
Agile research groups are recognizing the valuable opportunity for computational approaches to accelerate paths to insight generation. Mechanistically-guided methods have significant potential to inform and expedite critical decisions that would have previously required time consuming and costly de novo research studies.
Join us to learn how teams are combining deep biological knowledge with computational and machine learning approaches.
You’ll see how high resolution modeling of COVID-19 and related conditions enables:
- Predictive analysis of drug response for re-purposing or indication expansion
- Investigation of mechanism of action for potential therapeutic agents
- Analysis of preclinical model recapitulation
- Co-therapeutic target pathway selection
