Drug Metabolism Prediction

Johannes Kirchmair, Raimund Mannhold, Hugo Kubinyi, Gerd Folkers

• Publisher: Wiley-VCH
• Year: 2014
• Print ISBN:
  9783527335664
• eBook ISBN:
  9783527673018
• Edition: 1
• Topic: Medicine
• Subtopic: Pharmacology

The first professional reference on this highly relevant topic, for drug developers, pharmacologists and toxicologists.

The authors provide more than a systematic overview of computational tools and knowledge bases for drug metabolism research and their underlying principles. They aim to convey their expert knowledge distilled from many years of experience in the field. In addition to the fundamentals, computational approaches and their applications, this volume provides expert accounts of the latest experimental methods for investigating drug metabolism in four dedicated chapters. The authors discuss the most important caveats and common errors to consider when working with experimental data.

Collating the knowledge gained over the past decade, this practice-oriented guide presents methods not only used in drug development, but also in the development and toxicological assessment of cosmetics, functional foods, agrochemicals, and additives for consumer goods, making it an invaluable reference in a variety of disciplines.

Part One
Introduction

1
Metabolism in Drug Development

Bernard Testa

1.1 What? An Introduction

Drug metabolism, and more generally xenobiotic metabolism, has become a major pharmacological and pharmaceutical science with particular relevance to biology, therapeutics, and toxicology, as abundantly explained and illustrated in a number of recent books [1–8] and reviews [9–18]. As such, drug metabolism is also of great importance in medicinal chemistry and clinical pharmacology because it influences the deactivation, activation, detoxification, and toxification of most drugs [19–22]. This broader pharmacological context will be considered in Section 1.2. There, I shall address the “Why?” question, namely “Why does drug metabolism deserve so much attention?”

Given the major impact of biotransformation reactions and resulting metabolites on the preclinical and clinical success or failure of drug candidates, it comes as no surprise that huge efforts are being deployed toward developing ever earlier and faster biological tools. Here, the objective is to assess as rapidly as possible the viability of such candidates. This brings us to the “How?” question (Section 1.3), namely “How to obtain useful data and predictions on the metabolism of candidates?” Although an overview of modern analytical technologies is provided in Chapter 19 of this book, a first focus here will be on the many factors affecting the fate of a drug. Having gathered many sound if narrow experimental results, drug researchers need to make sense of them. In other words, they seek the help of artificial intelligence to extract reliable information from experimental data and transform it into valuable knowledge permitting extrapolative predictions to new molecules. This, as the reader knows, is the focus of this multi-authored book, the present chapter serving as a bird's eye view of the field.

As much as we live in an artificial world of hardware and software, human beings, so we believe and hope, must remain masters of the game by defining objectives, being cognizant of limits, and interpreting as wisely as possible the predictions generated by machines. The point made in Section 1.4 will thus be a “Who?” question and conclusion, namely “Who among scientists are best able to assess the soundness and reliability of drug metabolism predictions?” Should these be software specialists, chemists, biologists, or physicians? This section will end with a plea to pool competences and create teams whose total expertise will be greater than the sum of individual expertise.

1.2 Why? Metabolism in Drug Development

1.2.1 The Pharmacological Context

To put the present book in a global context, it appears useful to ponder the fate of medicines in the body and, more specifically, in the human body. The upper part of Figure 1.1 illustrates in schematic form the two aspects of the interactions between a xenobiotic and a biological system [15,23]. Note that a “biological system” is defined here very broadly and includes functional proteins (e.g., receptors), monocellular organisms and cells isolated from multicellular organisms, isolated tissues and organs, multicellular organisms, and even populations of individuals, be they uni- or multicellular. As for the interactions between a drug (or any xenobiotic) and a biological system, they may be simplified to “what the compound does to the biological system” and “what the biological system does to the compound.”

Figure 1.1 The upper part of this scheme illustrates the interaction between a drug (or any xenobiotic) and the organism (or any biological system). The salient point is the interdependence between pharmacodynamic processes (“what the drug does to the body,” namely activity (Act) and toxicity (Tox)) and pharmacokinetic processes (“what the body does to the drug,” namely absorption (A), distribution (D), metabolism (M = biotransformation), and excretion (E)). The lower part of the scheme is meant to make explicit the potential role of metabolites in the PD effects of a drug. It emphasizes that a metabolite, once formed, will also be involved in PK processes. More important, the figure highlights the fact that metabolite(s) may also play PD roles. Such roles are two, namely pharmacological activity and/or toxic effects (modified from Ref. [23]).

In pharmacology, one speaks of “pharmacodynamic (PD) effects” to indicate what a drug does to the body, and “pharmacokinetic (PK) effects” to indicate what the body does to the drug [24]. But one must appreciate that these two aspects of the behavior of xenobiotics are inextricably interdependent. Absorption, distribution, and excretion (abbreviated as ADE) will obviously have a decisive influence on the intensity and duration of pharmacodynamic effects, whereas metabolism (meaning biotransformation) will generate metabolites that may have distinct pharmacodynamic effects of their own. Conversely, by its own pharmacodynamic effects, a compound may affect the state of the organism (e.g., hemodynamic changes and enzyme activities) and hence its capacity to handle xenobiotics. Only a systemic approach as used in pharmacokinetic–pharmacodynamic (PKPD) modeling and in clinical pharmacology is able to grasp the global nature of this interdependence.

When looking in more detail at the behavior of a drug in the body, one finds a number of pharmacokinetic hurdles to be overcome before the sites of action can be reached. As schematized in Figure 1.2 for oral administration [25], a drug must (i) be liberated from its pharmaceutical form (often a tablet), (ii) dissolve in the gastrointestinal fluid, (iii) escape metabolism by the gut wall and flora, (iv) be absorbed through the intestinal wall passively (via permeation) and/or actively (via transporters), (v) escape excretion in the intestinal lumen by efflux transporters (mainly phosphoglycoprotein; see Chapter 15), (vi) escap...

Table of contents

• Cover
• Related Titles
• Title Page
• Copyright
• List of Contributors
• Preface
• A Personal Foreword
• Part One: Introduction
• Part Two: Software, Web Servers and Data Resources to Study Metabolism
• Part Three: Computational Approaches to Study Cytochrome P450 Enzymes
• Part Four: Computational Approaches to Study Sites and Products of Metabolism
• Part Five: Computational Approaches to Study Enzyme Inhibition and Induction
• Part Six: Experimental Approaches to Study Metabolism
• Index
• End User License Agreement