A Model Based Approach for Translation in Oncology - From Xenografts to RECIST
Conference poster, 2022

A major problem in drug development is translating results from preclinical studies to the clinical setting. Therefore, we ev
alu ate the translational potential of semi mechanistic tumor models (based on xenograft data) to predict clinical oncology results (RECIST
data). Two commonly used translational methods are evaluated: (1) replacement with human PK, and (2) allometric scaling of PD pa rameters. We then compute optimal scaling coefficients given the observed clinical data and relate them to the standard allom etr ic
exponents in method (2). The analysis is performed for three drug combinations: binimetinib/encorafenib (shown below), binime tin ib/ribociclib, and cetuximab/encorafenib.

Author

Marcus Baaz

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Fraunhofer-Chalmers Centre

Tim Cardilin

Fraunhofer-Chalmers Centre

Floriane Lignet

Merck KGaA

Mats Jirstrand

Fraunhofer-Chalmers Centre

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Subject Categories

Language Technology (Computational Linguistics)

Pharmaceutical Sciences

Medical Laboratory and Measurements Technologies

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Latest update

10/26/2023