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Webinar: Early assessment of PK properties using ADMET Predictor® HTPK Simulation Technology. Deployment of a high-throughput mechanistic PBPK approach at Roche

April 21, 2021 @ 8:00 am - 9:00 am

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Physiologically based pharmacokinetic (PBPK) modeling combined with in vitro and in vivo extrapolation (IVIVE) approaches have shown a major impact on drug development. PBPK modeling applications span from early lead identification to late clinical development. PBPK modeling has the potential to accelerate small molecule (SM) drug discovery, reducing the need for in vivo animal studies and optimizing design cycle times. Building PBPK models in the early discovery space, however, is time-consuming due to cumbersome data gathering, complex model interfaces, the need for learning and confirm cycles, and limited in vitro data available at an early stage of drug discovery. Due to these factors, simpler yet limited approaches dominate the early discovery space (e.g., correlations, assumption-rich equations, etc.)


High throughput (HT)-PBPK modeling approaches, on the other hand, allow fast and seamless PBPK simulations leveraging the power of Machine Learning to fill in gaps in measured compound properties. Thereby bringing PBPK-based ADME insights into the early discovery space.  With HT-PBPK, teams can predict PK, PD, and ADME properties based only on sparse in vitro data and in silico predicted inputs.


On April 21st Dr. Andrés Olivares-Morales (Roche Innovation Center) will highlight the use of HT-PBPK modeling in early discovery projects and the implementation of this technology as part of the toolbox for early drug design and optimization. Dr. Eric Jamois, Director, Key Accounts & Strategic Alliances, Simulations Plus, Inc., will moderate the Q&A session.


April 21, 2021
8:00 am - 9:00 am

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