Kirstin Thelen

Cytochrome P450‐mediated metabolism in the human gut wall

Objective Although the human small intestine serves primarily as an absorptive organ for nutrients and water, it also has the ability to metabolise drugs. Interest in the small intestine as a drug‐metabolising organ has been increasing since the realisation that it is probably the most important extrahepatic site of drug biotransformation.

A Computational Systems Biology Software Platform for Multiscale Modeling and Simulation: Integrating Whole-Body Physiology, Disease Biology, and Molecular Reaction Networks

Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multiscale by nature, project work, and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug–drug, or drug–metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach.

Evolution of a detailed physiological model to simulate the gastrointestinal transit and absorption process in humans, Part 1: Oral solutions

To enable more precise prediction of oral drug absorption, an existing physiologically based absorption model was revised. The revised model reflects detailed knowledge of human gastrointestinal (GI) physiology including fluid secretion and absorption, and comprises an elaborate representation of the intestinal mucosa. The alimentary canal from the stomach to the rectum was divided into 12 compartments. A mucosal compartment was added to each luminal segment of the intestine. A training set of 111 passively absorbed drugs with reported fractions of dose absorbed was used to optimize the semiempirical equation, which calculates intestinal permeability coefficients. The model was subsequently integrated into an established physiologically based pharmacokinetic software and validated by prediction of plasma concentration-time profiles of eight test compounds with diverse physicochemical properties. A good correlation between the simulated and experimental fractions of dose absorbed was established for the 111 compounds in the training set. Subsequently, the concentration-time profiles of six out of eight test compounds were predicted with high accuracy. The detailed model for GI transit and absorption presented in this study can help to understand the complex processes of oral absorption better and will be useful during the drug development process.

Towards quantitative prediction of oral drug absorption.

Although several routes of administration can be considered for new drug entities, the oral route remains the most popular. To predict the in vivo performance of a drug after oral administration from in vitro data, it is essential that the factors limiting absorption can be modelled. Factors limiting oral drug absorption are typically slow and/or incomplete dissolution, formation of insoluble complexes and/or decomposition in the gastrointestinal lumen, poor net permeability and first-pass metabolism. Although many attempts have been made to make global forecasts of oral bioavailability based on a single parameter (ranging from the partition coefficient [logP] to the polar surface area), it is clear from the diversity of properties that can influence delivery of drugs via the oral route that such an approach can at best lead to a qualitative estimation. To predict in vivo performance in a more quantitative way, it is instead necessary to identify the extent to which each of the aforementioned factors can limit absorption, and then combine the information into a comprehensive model of the absorptive processes. Much progress has been made in the last 10 years on developing methods to pin down the extent to which each of the factors actually limits the absorption of a given compound and, concomitantly, physiological models have been evolved, which show promise in terms of being able to integrate the information generated about each of the individual limiting factors. This article attempts to summarize recent progress on the various fronts as a kind of ‘progress report’ towards quantitative prediction of oral drug absorption.

Evolution of a Detailed Physiological Model to Simulate the Gastrointestinal Transit and Absorption Process in Humans, Part II: Extension to Describe Performance of Solid Dosage Forms

The physiological absorption model presented in part I of this work is now extended to account for dosage-form-dependent gastrointestinal (GI) transit as well as disintegration and dissolution processes of various immediate-release and modified-release dosage forms. Empirical functions of the Weibull type were fitted to experimental in vitro dissolution profiles of solid dosage forms for eight test compounds (aciclovir, caffeine, cimetidine, diclofenac, furosemide, paracetamol, phenobarbital, and theophylline). The Weibull functions were then implemented into the model to predict mean plasma concentration-time profiles of the various dosage forms. On the basis of these dissolution functions, pharmacokinetics (PK) of six model drugs was predicted well. In the case of diclofenac, deviations between predicted and observed plasma concentrations were attributable to the large variability in gastric emptying time of the enteric-coated tablets. Likewise, oral PK of furosemide was found to be predominantly governed by the gastric emptying patterns. It is concluded that the revised model for GI transit and absorption was successfully integrated with dissolution functions of the Weibull type, enabling prediction of in vivo PK profiles from in vitro dissolution data. It facilitates a comparative analysis of the parameters contributing to oral drug absorption and is thus a powerful tool for formulation design.

Mechanism-based prediction of particle size-dependent dissolution and absorption: Cilostazol pharmacokinetics in dogs

A previously developed physiologically based pharmacokinetic (PBPK) model for gastro-intestinal transit and absorption was combined with a mechanistic dissolution model of the Noyes-Whitney type for spherical particles with a predefined particle size distribution. To validate the combined model, the plasma concentration-time curves for cilostazol obtained in beagle dogs using three different types of suspensions with varying particle diameters were simulated. In vitro dissolution information was also available for different formulations, but this data could only predict the in vivo outcome qualitatively. The mechanistic PBPK model, on the other hand, could predict the influence of the particle size on the rate and extent of absorption under both fasted and fed conditions accurately, and the gap between the in vitro dissolution data and the in vivo outcome could successfully be explained. We conclude that by integrating the processes of particle dissolution, gastro-intestinal transit and permeation across the intestinal epithelium into a mechanistic model, oral drug absorption from suspensions can be predicted quantitatively. The model can be applied readily to typical formulation development data packages to better understand the relative importance of dissolution and permeability and pave the way for successful formulation of solid dosage forms.

Physiologically Based Pharmacokinetic Modeling of Tamoxifen and its Metabolites in Women of Different CYP2D6 Phenotypes Provides New Insight into the Tamoxifen Mass Balance

Tamoxifen is a first-line endocrine agent in the mechanism-based treatment of estrogen receptor positive (ER+) mammary carcinoma and applied to breast cancer patients all over the world. Endoxifen is a secondary and highly active metabolite of tamoxifen that is formed among others by the polymorphic cytochrome P450 2D6 (CYP2D6). It is widely accepted that CYP2D6 poor metabolizers exert a pronounced decrease in endoxifen steady-state plasma concentrations compared to CYP2D6 extensive metabolizers. Nevertheless, an in-depth understanding of the chain of cause and effect between CYP2D6 genotype, endoxifen steady-state plasma concentration, and subsequent tamoxifen treatment benefit still remains to be evolved. In this study, physiologically based pharmacokinetic (PBPK)-modeling was applied to mechanistically investigate the impact of CYP2D6 phenotype on endoxifen formation in female breast cancer patients undergoing tamoxifen therapy. A PBPK-model of tamoxifen and its pharmacologically important metabolites N-desmethyltamoxifen (NDM-TAM), 4-hydroxytamoxifen (4-OH-TAM), and endoxifen was developed and validated. This model is able to simulate the pharmacokinetics (PK) after single and repeated oral tamoxifen doses in female breast cancer patients in dependence of the CYP2D6 phenotype. A detailed model-based analysis of the mass balance offered support for a recent hypothesis stating a more prominent role for endoxifen formation from 4-OH-TAM. In the future this model provides a good basis to further investigate the linkage of PK, mode of action, and treatment outcome in dependence of factors such as phenotype, ethnicity, or co-treatment with CYP2D6 inhibitors.

Utilizing in vitro and PBPK tools to link ADME characteristics to plasma profiles: Case example nifedipine immediate release formulation

One of the most prominent food-drug interactions is the inhibition of intestinal cytochrome P450 (CYP) 3A enzymes by grapefruit juice ingredients, and, as many drugs are metabolized via CYP 3A, this interaction can be of clinical importance. Calcium channel-blocking agents of the dihydropyridine type, such as felodipine and nifedipine, are subject to extensive intestinal first pass metabolism via CYP 3A, thus resulting in significantly enhanced in vivo exposure of the drug when administered together with grapefruit juice. Physiologically based pharmacokinetic (PBPK) modeling was used to simulate pharmacokinetics of a nifedipine immediate release formulation following concomitant grapefruit juice ingestion, that is, after inhibition of small intestinal CYP 3A enzymes. For this purpose, detailed data about CYP 3A levels were collected from the literature and implemented into commercial PBPK software. As literature reports show that grapefruit juice (i) leads to a marked delay in gastric emptying, and (ii) rapidly lowers the levels of intestinal CYP 3A enzymes, inhibition of intestinal first pass metabolism following ingestion of grapefruit juice was simulated by altering the intestinal CYP 3A enzyme levels and simultaneously decelerating the gastric emptying rate. To estimate the in vivo dispersion and dissolution behavior of the formulation, dissolution tests in several media simulating both the fasted and fed state stomach and small intestine were conducted, and the results from the in vitro dissolution tests were used as input function to describe the in vivo dissolution of the drug. Plasma concentration-time profiles of the nifedipine immediate release formulation both with and without simultaneous CYP 3A inhibition were simulated, and the results were compared with data gathered from the literature. Using this approach, nifedipine plasma profiles could be simulated well both with and without enzyme inhibition. A reduction in small intestinal CYP 3A levels by 60% was found to yield the best results, with simulated nifedipine concentration-time profiles within 20% of the in vivo observed results. By additionally varying the dissolution input of the PBPK model, a link between the dissolution characteristics of the formulation and its in vivo performance could be established.

An update on computational oral absorption simulation.

Introduction: Within the last decades, computational models have developed rapidly and some of these models have proven useful in understanding how physiological, physicochemical and formulation factors affect oral drug absorption. Nowadays, complex computer-based absorption models are being used as standard tools in both academia and the pharmaceutical industry at several stages of the drug development process. Areas covered: Areas covered include the progress of computational tools for predicting drug absorption. The various qualitative and quantitative approaches that have been proposed are summarized, with special emphasis on a key tool for predicting oral drug absorption, physiologically based pharmacokinetic modeling (PBPK). The theories of the different models are described and recent applications within drug research and development are summarized and evaluated. Additionally, the current state of computational absorption models is discussed, including areas for potential improvements. Expert opinion: The field of pharmacokinetics modeling has undergone a major transformation over the last 10 – 20 years and there will most likely be even more exciting developments ahead. With the availability of generic physiologically based absorption models, more and more case examples using PBPK models have been published that demonstrate either improved ability to predict oral drug absorption or have allowed a more mechanistic interpretation of experimentally observed data.

Whole‐body physiologically based pharmacokinetic population modelling of oral drug administration: inter‐individual variability of cimetidine absorption

Objectives Inter‐individual variability of gastrointestinal physiology and transit properties can greatly influence the pharmacokinetics of an orally administered drug in vivo. To predict the expected range of pharmacokinetic plasma concentrations after oral drug administration, a physiologically based pharmacokinetic population model for gastrointestinal transit and absorption was developed and evaluated.