12.08.21 -- Accelerate Drug Discovery With Molecular 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.

Detecting and preventing unwanted sources of immunogenicity remains a challenge for scientists, as the underlying mechanisms of unwanted immunogenicity still are not completely understood. Predictive analytics has emerged as a leading tool to identify immunogenicity in biotherapeutics during the discovery phase of drug development. However, the value of a predictive approach depends on the quality and variety of the data supporting it.

Autoxidation risk assessments of potential formulations was causing a bottleneck in Sanofi's pharmaceutical development workflow as well as driving up unnecessary spend on materials and equipment. By implementing materials modeling and simulation tools, they were able to improve what had previously been a laborious, manual process.

The diversity of the pathogens implicated in neglected tropical diseases (NTDs) has resulted in a lack of potential therapeutic targets and candidates. By repurposing existing data for Ebola and Chagas Disease to create machine learning models that could screen libraries for potential active compounds, an R&D company was able to help create safe and efficacious treatments for those who need them most.

Improving the understanding of critical properties of antibodies as early as possible in development and formulation can impact speed and total cost to market. Many properties cannot be predicted from sequence alone or can be predicted more accurately with access to a 3D antibody structure. When 3D structures are not available from X-ray or NMR, 3D in silico models are the solution.

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