09.27.22 -- Power Your Drug Discovery With Modeling And Simulation

Learn how having the right predictive sciences capabilities integrated into R&D workflows delivers a scientific decision support environment that reduces time and expense, improves quality, enhances collaboration, and accelerates innovation in bringing new drugs to market.

The development and manufacturing of biologics is highly complex, difficult, and costly, because biomolecular processes rely on a variety of dynamic interactions. Learn more about how to augment physical experimentation with in silico techniques, accelerate biologics characterization, and simplify biologics lead identification/optimization.

Improving the understanding of critical properties of antibodies as early as possible in development and formulation will impact speed and total cost to market. When 3D structures are not available from X-ray or NMR, 3D-generated in silico models are the solution.

The diversity of the pathogens implicated in NTDs, the relative complexity of their life cycles, and their poor tractability in the lab have resulted in a lack of potential therapeutic targets and candidates. Collaborations Pharmaceuticals was able to provide safe and efficacious treatments by repurposing existing HTS data for Ebola and Chagas disease to create machine learning models that could screen libraries for potential active compounds.

When COVID-19 became a pandemic, scientists at an academic research and development center in Israel began using applications and computational tools to apply their research to the study of COVID-19 mutations. See how they used these tools to accelerate their research and development of a possible vaccine against COVID-19.