A Bayesian K-PD model for synergy: a case study

Co-administration of two or more compounds can alter both the pharmacokinetics (PK) and pharmacodynamics (PD) of individual compounds.While experiments on PD drug-drug interactions are usually performed in an in-vitro setting, this experiment focuses on an in-vivo setting. The change over time of a safety biomarker is modeled using an indirect response model, in which the virtual PK profile of one compound drives the effect of the other. Several experiments at different dose level combinations were performed sequentially. While a traditional frequentist analysis consists of estimating the model parameters based on all the data simultaneously, in this work we consider a Bayesian inference framework allowing to incorporate the results from a historical dose-response experiment.