23 min

Mechanistic Modeling Improves Drug Discovery Workflows and Speeds Therapeutic Development GEN Podcasts

    • Technology

This is the final episode in our three-part GENcast series, where we discuss the virtues of mechanistic modeling and how it can significantly impact critical decision-making points in the drug discovery process, especially as drug developers move closer toward the IND process. In our two previous podcasts, we were introduced to mechanistic modeling concepts and the basics of how they can be applied to drug discovery workflows. You can listen to the earlier podcasts with the following links: episode 1, episode 2. In this latest GENcast, I met up once again with Dr. John Burke, President, CEO, and Co-founder of Applied BioMath, to discuss the specific applications of mechanistic modeling, especially concerning the process of deciding the first human dose numbers, and how his company is helping biotech and pharma organizations reduce their late-stage drug attrition rates. Take a listen!
Hosted on Acast. See acast.com/privacy for more information.

This is the final episode in our three-part GENcast series, where we discuss the virtues of mechanistic modeling and how it can significantly impact critical decision-making points in the drug discovery process, especially as drug developers move closer toward the IND process. In our two previous podcasts, we were introduced to mechanistic modeling concepts and the basics of how they can be applied to drug discovery workflows. You can listen to the earlier podcasts with the following links: episode 1, episode 2. In this latest GENcast, I met up once again with Dr. John Burke, President, CEO, and Co-founder of Applied BioMath, to discuss the specific applications of mechanistic modeling, especially concerning the process of deciding the first human dose numbers, and how his company is helping biotech and pharma organizations reduce their late-stage drug attrition rates. Take a listen!
Hosted on Acast. See acast.com/privacy for more information.

23 min

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