A Model Based Approach for Translation in Oncology - From Xenografts to RECIST
Poster (konferens), 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.
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.
Författare
Marcus Baaz
Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik
Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik
Tim Cardilin
Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik
Floriane Lignet
Merck KGaA
Mats Jirstrand
Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik
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Ämneskategorier
Språkteknologi (språkvetenskaplig databehandling)
Farmaceutisk vetenskap
Medicinsk laboratorie- och mätteknik