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Home / Resources / Webinar / Exploring ADC pharmacokinetics using QSP [APAC Webinar]

Exploring ADC pharmacokinetics using QSP [APAC Webinar]

Live webinar

The Pharmacokinetics (PK) of ADC therapeutics typically show a discrepancy between the PK of total antibody and that of conjugated antibody, carrying one or more payload molecules. This discrepancy is often attributed to deconjugation, however recent evidence suggests that the underlying mechanisms may be more complex.

In this webinar, we will present how quantitative systems pharmacology (QSP) modeling approaches provide biological insights into the impact of drug-to-antibody ratio and the resulting changes in molecular properties on overall PK and relative payload disposition as observed in preclinical and clinical studies.

For whom the webinar will be beneficial the most:

Scientists at pharmaceutical companies who are 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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Speaker
Apgar 8×10
Joshua Apgar, PhD
VP, Global Head of ABM Scientific Affairs
Before co-founding Applied BioMath, Josh was a Principal Scientist in the Systems Biology Group of the Department of Immunology and Inflammation at Boehringer Ingelheim Pharmaceuticals. His work leveraged physics-based models to: translate in vitro and in vivo data, assess target feasibility, understand drug mechanism of action, and predict human doses. The ultimate goal of this work was to reduce late stage attrition in drug development through a deep and quantitative interrogation of drug pharmacology and disease pathophysiology. Josh received his PhD from MIT in Biological Engineering where he worked on experiment design for Systems Biology, focusing on the identification of tractable experiments that could allow for the estimation of unknown parameters and reveal complex mechanisms in signal transduction networks. Before that Josh worked at Avaki to develop a highly scalable software platform to support High Performance Computing, and Enterprise Information Integration in the Life Sciences, and Engineering.