Multiscale modeling reveals inhibitory and stimulatory effects of caffeine on acetaminophen-induced toxicity in humans.

Acetaminophen (APAP) is a widely used analgesic drug that is frequently co-administered with caffeine (CAF) in the treatment of pain. It is well known that APAP may cause severe liver injury after an acute overdose. However, the understanding of whether and to what extent CAF inhibits or stimulates APAP-induced hepatotoxicity in humans is still lacking. Here, a multiscale analysis is presented that quantitatively models the pharmacodynamic (PD) response of APAP during co-medication with CAF. Therefore, drug-drug interaction (DDI) processes were integrated into physiologically based pharmacokinetic (PBPK) models at the organism level, whereas drug-specific PD response data were contextualized at the cellular level. The results provide new insights into the inhibitory and stimulatory effects of CAF on APAP-induced hepatotoxicity for crucially affected key cellular processes and individual genes at the patient level. This study might facilitate the risk assessment of drug combination therapies in humans and thus may improve patient safety in clinical practice.

Applied Concepts in PBPK Modeling: How to Build a PBPK/PD Model.

The aim of this tutorial is to introduce the fundamental concepts of physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling with a special focus on their practical implementation in a typical PBPK model building workflow. To illustrate basic steps in PBPK model building, a PBPK model for ciprofloxacin will be constructed and coupled to a pharmacodynamic model to simulate the antibacterial activity of ciprofloxacin treatment.

Clinical translation in the virtual liver network.

The liver is the central detoxifying organ, continuously removing xenobiotics from the vascular system. Given its role in drug metabolism, a functional understanding of liver physiology is crucial to optimizing drug efficacy and patient safety. The Virtual Liver Network (VLN), a German national flagship research program, focuses on producing validated computer models of human liver physiology. These models are used to analyze patient-derived data and thereby gain mechanistic insights in the processes underlying drug pharmacokinetics (PK).

A mechanistic, model-based approach to safety assessment in clinical development.

Assessing the safety of pharmacotherapies is a primary goal of clinical trials in drug development. The low frequency of relevant side effects, however, often poses a significant challenge for risk assessment. Methodologies allowing robust extrapolation of safety statistics based on preclinical data and information from clinical trials with limited numbers of patients are hence needed to further improve safety and efficacy in the drug development process. Here, we present a generic systems pharmacology approach integrating prior physiological and pharmacological knowledge, preclinical data, and clinical trial results, which allows predicting adverse event rates related to drug exposure. Possible fields of application involve high-risk populations, novel drug candidates, and different dosing scenarios. As an example, the approach is applied to simvastatin and pravastatin and the prediction of myopathy rates in a population with a genotype leading to a significantly increased myopathy risk.CPT: Pharmacometrics & Systems Pharmacology (2012) 1, e13; doi:10.1038/psp.2012.14; advance online publication 7 November 2012.