Roche uses PK/PD modeling to screen compounds

To cut down on drug failures at the clinical trial stage, Roche researchers are using pharmacodynamic/pharmacokinetic modeling for early prediction of drug efficacy. Roche created the PK/PD models and combined them with models of organs. The combination gives researchers a tool for screening drug compounds, predicting their efficacy and safety, and guiding dosing regimens.

"Researchers need to predict drug efficacy as early as possible from animal experiments," says Thierry Lavé, global head of preclinical modeling at Roche, in a case history. "Modeling helps determine how fast the drug is cleared from the body, how safe the drug is, and how effective--which is often the most difficult characteristic to model."

The PK/PD and organ models, which the researchers built using tools from technical computing software maker Mathworks, use complex systems of ordinary differential equations (ODEs) and partial differential equations (PDEs). Through simulation, the researchers adjusted various parameters and determined dosing schedules for preclinical and early clinical trials.

In an anticancer drug project, the research team created a model that tracks the effect of white blood cell maturation. Another model monitors the transport and accumulation of biologicals, such as antibodies, in tissues, according to the case history. Researchers used the Mathworks MATLAB, Optimization Toolbox, and Curve Fitting Toolbox in their modeling efforts.

One PK/PD model helps researchers predict the disposition of a drug from the body and its penetration to the target organs. The model incorporates data from animal tests on the new drug and on a similar, existing drug, as well as publicly available data for the existing drug derived from human clinical trials. It helps the researchers estimate the efficacy of the new drug in humans and guides early decision-making in clinical trials.

- see the Mathworks case history

Sponsored By Metabolon

Five Translational Insights Key to a Successful First-in-Human (FIH) Study – Metabolite-Based Biomarker Discovery and Validation

Translational success rates from pre-clinical animal studies to human clinical trials remain frustratingly low. Learn how metabolomics helps you bridge between the theoretical & practical, between the function & actual activity of your drug molecule to get you closer to the phenotype, sooner.