A delayed nonlinear PBPK model for genistein dosimetry in rats

Physiologically based pharmacokinetic modeling for predicting irinotecan exposure in human body

Colorectal cancer is the third leading cause of cancer-related deaths in the United States. Treatment of colorectal cancer remains a challenge to clinicians as well as drug developers. Irinotecan, a Camptothecin derivative, is successfully used for the treatment of this rapidly progressing malignancy and finds its place in the first line of therapeutic agents. Irinotecan is also effective in treating SCLC, malignant glioma and pancreatic adenocarcinoma. However, its adverse effects limit its clinical application. Mainly metabolized by hepatic route, and excreted through biliary tract, this dug has been found to possess high variation in patients in its pharmacokinetic (PK) profile. Physiologically based pharmacokinetic (PBPK) models using compartmental approach have attained their position to foresee the possible PK behavior of different drugs before their administration to patients and such models have been proposed for several anticancer agents. In this work, we used WB-PBPK technology to develop a model in a population of tumor patients who used IV irinotecan therapy. This model depicted the concentration of drug and its pharmacologically active metabolite in human body over a specific period of time. Knowledge about pharmacokinetic parameters is extracted from this profile and the model is evaluated by the observed results of clinical study presented in literature. The predicted behavior of the drug by this approach is in good agreement with the observed results and can aid in further exploration of PK of irinotecan in cancer patients, especially in those concomitantly suffer from other morbidity.

The pharmacokinetic/pharmacodynamic pipeline: translating anticancer drug pharmacology to the clinic

Progress in an understanding of the genetic basis of cancer coupled to molecular pharmacology of potential new anticancer drugs calls for new approaches that are able to address key issues in the drug development process, including pharmacokinetic (PK) and pharmacodynamic (PD) relationships. The incorporation of predictive preclinical PK/PD models into rationally designed early-stage clinical trials offers a promising way to relieve a significant bottleneck in the drug discovery pipeline. The aim of the current review is to discuss some considerations for how quantitative PK and PD analyses for anticancer drugs may be conducted and integrated into a global translational effort, and the importance of examining drug disposition and dynamics in target tissues to support the development of preclinical PK/PD models that can be subsequently extrapolated to predict pharmacologic characteristics in patients. In this article, we describe three different physiologically based (PB) PK modeling approaches, i.e., the whole-body PBPK model, the hybrid PBPK model, and the two-pore model for macromolecules, as well as their applications. General conclusions are that greater effort should be made to generate more clinical data that could validate scaled preclinical PB-PK/PD tumor-based models and, thus, stimulate a framework for preclinical to clinical translation. Finally, given the innovative techniques to measure tissue drug concentrations and associated biomarkers of drug responses, development of predictive PK/PD models will become a standard approach for drug discovery and development.