By Huixin Yu, Jeroen J.M.A. Hendrikx, and Alwin D.R. Huitema
Many patients are treated with several drugs concomitantly, and this may lead to drug-drug interactions (DDIs). DDIs can generally affect two aspects of the drugs: pharmacokinetics (PK) and pharmacodynamics (PD). The effects on PK may result in increased or decreased plasma concentrations, which may later affect PD as well. The effects on PD bring about changes in side effects and/or therapeutic responses. DDIs can be destructive or desirable or both. For drugs with a narrow therapeutic index, altered PK could lead to lethal toxicities or failed treatment. For the drugs with low bioavailability, enhancement in PK by another drug may be very useful for improving treatment. However, the improved therapeutic responses may be concurrent with intolerable side effects. Therefore, the PK and PD of DDIs can be very complex yet important.
Preclinical and clinical studies are conducted to study the DDIs. Unfortunately, the interpretation of the results of these studies can be challenging. This is because the PK and PD effects can be so tangled together that it could be troublesome to conclude whether the effects on PD was caused only by PK or by combination of both PK and PD.
Nowadays, pharmacometrics has become widely adopted as a valuable tool in the pharmaceutical field. Population PK models help us to understand and quantify the PK characteristics of drugs. PK/PD models are used to explore the concentration-response relationships. These models can all be applied to test hypotheses by the comparison of model fits to observed experimental results. The most plausible hypothesis stands out with the best model fit. This use of pharmacometrics enables full understanding of the complex PK and PD of DDIs.
Our preclinical study explored the anti-tumor effect of docetaxel-ritonavir co-medication in mice. The results illustrated a significantly prolonged survival in co-treatment compared to docetaxel treatment alone. This could be caused by increased docetaxel concentrations in the tumor by ritonavir. But did ritonavir also contribute with a direct anti-tumor effect itself? There was limited PK data, and PK and PD effects were tangled.
Therefore, we initiated a follow-up study to re-examine the data with pharmacometric tools. A PK/PD model was built to describe the PK of docetaxel and ritonavir in plasma and in the tumor, which was linked with the tumor growth in the mice. Later the hypothesis of whether ritonavir also has a direct anti-tumor effect, in addition to its effect on PK of docetaxel, was tested. By comparing the model fits, we found that the increased anti-tumor effect in the mice with co-medication is mainly caused by boosting the docetaxel concentration in the tumor and to a minor extent by a direct tumor growth inhibitory effect of ritonavir. This example showed a successful application of pharmacometrics to help us understand the complex PK and PD of DDIs. Read more about our research in The AAPS Journal article Development of a Tumour Growth Inhibition Model to Elucidate the Effects of Ritonavir on Intratumoural Metabolism and Anti-tumour Effect of Docetaxel in a Mouse Model for Hereditary Breast Cancer.
What were the problems you encountered when analyzing complex DDIs? Are there other mathematical or experimental methods that you would suggest to use? Please comment below for further discussion.