Vanessa Baier (1,2), José V. Castell (3), Hanna Kreutzer (1), Annika Schneider (1), Henrik Cordes (1), Lars Kuepfer (1)
(1) Institute of Applied Microbiology - iAMB, Aachen Biology and Biotechnology – ABBt, RWTH Aachen University, Germany (2) esqLABS GmbH (3) Instituto de Investigación Sanitaria. Hospital Universitario La Fe, Valencia, Spain
Objectives: Drug-induced liver injury (DILI) is a serious adverse reaction that can lead to liver damage or failure. It is often of idiosyncratic nature what means that it occurs independently from dosage, possibly with a long latency, and frequently related to a drug metabolising enzyme phenotype. This hampers a quick diagnose and even more a reliable susceptibility prediction. [1] However, both of which would be of great use in the clinical routine. Up to date, the prediction of such an idiosyncratic DILI risk regarding a specific drug and a patient is not possible without conducting invasive, expensive and time-consuming testing. [2] Thus, our aim is to use PBPK model for the prediction of patients’ DILI risk phenotypes in a fast and non-invasive manner that could be applicable in the clinical daily routine. The idea is to characterize the metabolic capability of a DILI patient’s liver by administering a safe, low-dose drug cocktail whose components are specifically metabolised by a disjunct set of CYP enzymes. Following drug administration, the blood pharmacokinetics (PK) are measured and an individualised PBPK model is built, in order to estimate non-invasively the drug metabolising activities in the liver. Its simulated PK profile is then compared against a reference profile such that a specific metabolic phenotype can be identified according to the simulated differences.
Methods: This approach is based on physiologically-based pharmacokinetic (PBPK) modelling to simulate the drug concentration-time profiles. The drug-specific PBPK models were built with the Open Systems Pharmacology Suite. [3] Patient data was gathered in the hospital La Fe in Valencia, Spain, in the course of an approved clinical trial. The participants were given a low-dose of a marketed anti-influenza drug (Frenadol) which consists of a cocktail of four different drugs chlorpheniramine, caffeine, dextromethorphane, and acetaminophen. Blood plasma samples as well as urine samples were taken at defined time intervals. In Phase II of the clinical trial the test was conducted in selected patients undergoing programmed liver surgery and liver biopsies were obtained and analysed to assess individual CYP enzyme levels, and to compare with model’s prediction.
Results: So far, PBPK models of chlorpheniramine and caffeine for a healthy average individual have been built. These base models were informed by literature data and were in good agreement with the PK measurements. In a next step, the models were individualised to describe the proprietary clinical PK measurements after drug-cocktail administration in the phase I and II study. The individualised phase I fits were generally good, while the simulation of phase II individuals was not straight forward due to unexpected high data variability. In addition, no obvious correlation between the measured enzyme activities from the liver biopsies and compound concentrations in blood could be found. We therefore suggest increasing the patient cohorts and shifting of the measurement time points to facilitate the metabolic in vivo phenotyping.
Conclusions: The need for a hands-on non-invasive clinical test for DILI susceptibility is obvious. This study is an excellent starting point to achieve such a demanded test. However, some refinements are still necessary to make the HEPATEST applicable in clinical routine. A final validation with PK measurements in actual DILI patients is ongoing.
References:
[1] Roth, R. A., and Ganey, P. E. (2010). Intrinsic versus idiosyncratic drug-induced hepatotoxicity–two villains or one? J Pharmacol Exp Ther 332, 692–697. doi: 10.1124/jpet.109.162651.
[2] Chalasani, N., and Björnsson, E. (2010). Risk factors for idiosyncratic drug-induced liver injury. Gastroenterology 138, 2246–2259. doi: 10.1053/j.gastro.2010.04.001.
[3] Open Systems Pharmacology Suite. http://www.open-systems-pharmacology.org/.
Reference: PAGE () Abstr 9422 [www.page-meeting.org/?abstract=9422]
Poster: Drug/Disease Modelling - Absorption & PBPK