The drug discovery and development process can be an arduous endeavor. Manufacturers spend considerable resources and money chasing down potential candidate molecules to create a potential new therapeutic—often resulting in abandoning the candidate in the very later stages of development due to minor factors that might have been overlooked at the onset of the discovery process. Thankfully, there have always been those investigators who sought to merge the fields of mathematics and biology while taking advantage of advanced computing algorithms to help inform and de-risk drug discovery decisions and streamline the development pipeline. This mechanistic modeling approach is helping to transform drug R&D projects by giving pharma and biotech companies the vital information they need to make the critical decisions in a drug’s path toward clinical success.
In this GENcast, we sat down with an expert in mechanistic modeling to discuss the specific of this approach and how companies are employing the technology successfully. Jump into the discussion and take a listen!
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Panelist:
John M. Burke, PhD
Co-Founder, President and CEO
Applied Biomath
Podcast Sponsored By:
