Physiologically Based Pharmacokinetic (PBPK) Modeling

Methods and Applications in Toxicology and Risk Assessment

Jeffrey W. Fisher,Jeffery M. Gearhart,Zhoumeng Lin

• Publisher: Academic Press
• Year: 2020
• ISBN:
  9780128196823
• Topic: Medicine
• Subtopic: Toxicology

Physiologically Based Pharmacokinetic (PBPK) Modeling: Methods and Applications in Toxicology and Risk Assessment presents foundational principles, advanced techniques and applications of PBPK modeling. Contributions from experts in PBPK modeling cover topics such as pharmacokinetic principles, classical physiological models, the application of physiological models for dose-response and risk assessment, the use of in vitro information, and in silico methods. With end-of-chapter exercises that allow readers to practice and learn the skills associated with PBPK modeling, dose-response, and its applications to safety and risk assessments, this book is a foundational resource that provides practical coverage of PBPK modeling for graduate students, academics, researchers, and more.

• Provides end-of-chapter exercises to teach hands-on computational tools used in toxicology
• Supplies computer code and explanations and includes examples of applied models used in regulatory toxicology and research
• Authored by expert editors and contributors who are among the best PBPK modelers in the world

Chapter 1

A history and recent efforts of selected physiologically based pharmacokinetic modeling topics

Zhoumeng Lin¹ and Jeffrey W. Fisher², ¹Institute of Computational Comparative Medicine (ICCM), Department of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, United States, ²Division of Biochemical Toxicology, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, United States

Abstract

Physiologically based pharmacokinetic (PBPK) modeling is a computational process that simulates the absorption, distribution, metabolism, and excretion of a substance in the body of an organism based on the interrelationships among key physiological, biochemical, and physicochemical factors using mathematical equations. This chapter provides a summary of the history and recent efforts of PBPK modeling in several applications, including (1) drug discovery and development, (2) toxicology and risk assessment, (3) veterinary pharmacology and animal-derived food safety assessment, and (4) nanomedicine and nanotoxicology. The history of PBPK modeling software programs, books, and the Society of Toxicology Biological Modeling Specialty Section is also briefly introduced. The authors’ perspective on the current and future applications of PBPK modeling in different fields, especially in toxicology and risk assessment, is presented.

Keywords

Food safety assessment; pharmacokinetics; physiologically based pharmacokinetic (PBPK) modeling; risk assessment; toxicology

1.1 Introduction

Pharmacokinetics is the science of studying the rate and extent of absorption, distribution, metabolism, and excretion (ADME) processes of chemicals and their metabolites within the body, as well as the factors that control the time course of these processes using experimental or mathematical modeling approaches. Pharmacokinetic modeling is the quantitative study of the time course of ADME processes of chemicals and their metabolites in the body using a set of mathematical equations. Pharmacokinetics of a chemical can be described using different quantitative approaches, including compartmental modeling (i.e., traditional or classical approach), noncompartmental approach (i.e., statistical moment approach), and physiologically based pharmacokinetic (PBPK) modeling approach. An overview of the compartmental and noncompartmental pharmacokinetic approaches is presented in Chapter 2, Introduction to classical pharmacokinetics. This first chapter covers the history and recent efforts of the development and applications of PBPK modeling. The rest of this book is devoted to the principles, methodology, and applications of PBPK models in the field of toxicology and risk assessment.

PBPK models are useful in risk assessment because they can link internal target organ concentrations of chemicals with the external doses of the chemicals that animals or humans are exposed to, and they can also be used to extrapolate the simulation results from one exposure scenario to another, from one species to another, and from in vitro to in vivo. This is important because one fundamental tenet in pharmacology and toxicology is that both the beneficial and toxic effects of chemicals are related to the concentrations of the chemicals at the target organs, rather than the concentrations of the chemicals at the site of exposure (Andersen et al., 2005). In addition, concentration-time data of different exposure regimens are often needed, whether it is for clinical dose optimization of a drug or for risk assessment of an environmental chemical. Traditional pharmacokinetic approaches are empirical approaches and are limited in usefulness in extrapolation beyond the range of the experimental data, whereas PBPK modeling is a physiologically based approach that can be extrapolated across species, exposure routes, exposure durations, and doses. Overall, PBPK models require more parameters, are relatively more complex and computationally more demanding than traditional pharmacokinetic models, but PBPK models are more robust than traditional pharmacokinetic models, and their unique strengths can better meet the needs of drug dose optimization or chemical risk assessment.

1.2 A historical perspective

The concept of PBPK modeling can be traced back to approximately the beginning of the 20th century. Fig. 1.1 lists representative studies of PBPK modeling and applications in the fields of pharmacology, toxicology, risk assessment, veterinary medicine, and food safety assessment that are further discussed below.

Figure 1.1 Representative studies and milestones in the history of PBPK modeling and applications.

1.2.1 Early efforts on inhaled compounds

In the 1920s, Haggard (1924a,b) developed mathematical equations to simulate the concentration of the volatile anesthetic ethyl ether in the blood after inhalation exposure. The model was limited to the first few breaths when the concentrations in the blood were still low due to lack of tools to solve the mathematical equations. According to the earlier book on PBPK modeling (Andersen et al., 2005), the American Chemical Society Monograph Series, Vol. 35 by Henderson and Haggard (1943) presents the first detailed discussion of toxicology of inhaled noxious gases in the context of the principles that control exposure, absorption, and distribution. This work is considered as the first articulation of the PBPK modeling concept in the field of occupational and environmental toxicology.

Based upon the earlier work by Haggard and Henderson (Haggard, 1924a,b; Henderson and Haggard, 1943), later studies published more comprehensive PBPK models for inhaled compounds, such as the studies by Kety (1951), Mapleson (1963), and Riggs (1963). Several new concepts described in these studies are still widely used. For example, in these models the body tissues were lumped together and divided into two groups of tissues according to the blood perfusion rates, generating two sets of tissues with different blood perfusion rates, referred to as richly perfused (also termed rapidly perfused) or poorly perfused (also termed slowly perfused) tissues. In Kety (1951), it was proposed that the kinetic behavior of the inhaled compounds in the tissue is related to three tissue characteristics: tissue volume, blood flow, and partition coefficient. This concept is still the basis of modern PBPK models. In the 1960s, Mapleson (1963) used an analog computer to solve mathematical rate equations describing the time-concentration course of inert gases in the body. This work represents a significant advancement in solving complex PBPK models using computers. Based on Mapleson’s work, Fiserova-Bergerova and colleagues also used analog computers to solve PBPK models for inhaled chemicals with a consideration of metabolism of the inhaled compounds in liver (Fiserova-Bergerova, 1976; Fiserova-Bergerova and Holaday, 1979; Fiserova-Bergerova et al., 1980). The consideration of metabolism is crucial in a PBPK model because many chemicals that require risk assessment can be metabolized in the body and the metabolites are often active metabolites that can contribute to the toxic response. Nowadays, it is very common to include a metabolite submodel in a PBPK model to fully describe the pharmacokinetics of a chemical in the body.

1.2.2 History and recent efforts in the pharmaceutical industry

As early as 1930s, Teorell (1937a,b) reported a set of rate equations to simulate the ADME processes of drugs in the body. These earlier publications are generally recognized as the pioneering PBPK work that considers whole-body distribution and simulates drug concentrations in the tissues. However, computational resources were not sufficient to solve the entire set of equations at that time. As a result, the exact mathematical solutions for drug distribution were only obtained for a simplified model structure in which the body was reduced to a small number of compartments that did not correspond directly with specific physiological organ compartments (i.e., all tissues were pooled as a single tissue compartment). Nevertheless, these pioneering studies provide a basis for subsequent pharmacokinetic modeling work.

From 1930s to 1960s, pharmacokinetic modeling was focused on simpler mathematical descriptions with exact solutions instead of focusing on developing physiologically based models that correspond to the anatomical structure of the organism due to limitations in computational resources. These simpler approaches are termed “data-based” or “data-driven” compartmental modeling, empirical approaches, or traditional/classical pharmacokinetic approaches. Using these “data-based” approaches, the concentration-time data are analyzed by assuming a particular model structure (i.e., one-, two-, or three-compartment) and estimating a small number of parameters by curve-fitting methods. In these earlier simplified models, all ADME processes were described using first-order equations (i.e., a constant proportion of a drug or chemical is eliminated per unit time or in other words, the rate of elimination of drug or chemical is directly proportional to the concentration or the amount of the drug in the body). In the 1960s and early 1970s, there was a growing concern on the suitability of “data-based” compartmental modeling and whether first-order equations can be used to simulate all ADME processes because it was found that ADME processes could be saturated at higher doses. Once the ADME processes are saturated, they should be described using nonlinear equations. The need for using more mechanism-based models and the availability of sufficient computational capacities led to the development of whole-body mechanism-based PBPK models.

In the last 10 years, PBPK models are widely used in new drug discovery, development, and regulatory ap...