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Exploring ADC Pharmacokinetics using QSP Modeling Strategies

Published on 09th August

A webinar presented by Joshua Apgar, Ph.D, Co-Founder and CSO of Applied BioMath, will show how quantitative systems pharmacology (QSP) modeling approaches provided biological insights into the impact of drug-to-antibody (DAR) ratio and the resulting changes in molecular properties on overall pharmacokinetics (PK) and relative payload disposition as observed in preclinical studies.

“We used QSP modeling to explore the PK of antibody-drug conjugate (ADC) therapeutics which typically show a discrepancy between the PK of total antibody and that of conjugated antibody, carrying one or more payload molecules,” Apgar said.

“This discrepancy is often attributed to deconjugation, however recent evidence suggests that the underlying mechanisms may be more complex. Modeling helps generate hypotheses that predict this complex behavior,” he noted.

“This ADC case study is a great example of how Model-Aided Drug Invention (MADI) helps project teams quickly discern important characteristics of a platform or drug candidate,” explained John Burke, Ph.D, Co-Founder, President, and CEO of Applied BioMath.

“We often hear from our clients how valuable these biological and drug insights, sometimes counterintuitive, are as it helps accelerate drug candidates into the clinic and to then better ensure the likelihood of testing proof of clinical concept,” Burke added

This webinar will air live at 2pm ET / 11am PT and is ideal for scientists interested in how computational models can be used to design novel ADCs and to optimize the discovery and development of existing ADCs.


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