Recent Advances in Development and Application of Physiologically-Based Pharmacokinetic (PBPK) Models: a Transition from Academic Curiosity to Regulatory Acceptance

Curr Pharmacol Rep (2016) 2:161–169 DOI 10.1007/s40495-016-0059-9 PHARMACOMETRICS (H KIMKO, SECTION EDITOR) Recent Advances in Development and Application of Physiologically-Based Pharmacokinetic (PBPK) Models: a Transition from Academic Curiosity to Regulatory Acceptance Masoud Jamei 1 Published online: 14 April 2016 # The Author(s) 2016. This article is published with open access at Springerlink.com Abstract There is a renewed surge of interest in applications of physiologically-based pharmacokinetic (PBPK) models by the pharmaceutical industry and regulatory agencies. Developing PBPK models within a systems pharmacology context allows separation of the parameters pertaining to the animal or human body (the system) from that of the drug and the study design which is essential to develop generic drug-independent models used to extrapolate PK/PD properties in various healthy and patient populations. This has expanded the classical paradigm to a ‘predict-learn-confirm-apply’ concept. Recently, a number of drug labels are informed by simulation results generated using PBPK models. These cases show that either the simulations are used in lieu of conducting clinical studies or have informed the drug label that otherwise would have been silent in some specific situations. It will not be surprising to see applications of these models in implementing precision dosing at the point of care in the near future. Keywords Physiologically-based pharmacokinetics . Systems pharmacology . In vitro in vivo extrapolation . Modelling and simulation . Regulatory science . Precision medicine This article is part of the Topical Collection on Pharmacometrics * Masoud Jamei 1 Simcyp Limited (a Certara Company), Blades Enterprise Centre, John Street, Sheffield S2 4SU, UK Introduction Physiologically-based pharmacokinetic (PBPK) models map drug movements in the body to a physiologically realistic compartmental structure using sets of differential equations. It is suggested [30] that the origins of PBPK models go back to the work of Teorell in 1937 [36]. Teorell appreciated that an integrated model is needed to account for various processes affecting drug disposition around the body. As computational power increased, PBPK models were further developed in the 1960s and the 1970s, and the first article which appeared with the term PBPK in its title is [11]. The majority of early applications of PBPK models deal with issues related to anaesthesia and risk assessment of environmental chemicals due to their capability to predict the systemic exposure of chemicals in various parts of the body [30]. Recently, there has been a renewed surge of interest in applications of PBPK models by the pharmaceutical industry, especially in populations where designing and conducting clinical studies is more challenging [17]. The trend is part of wider applications of modelling and simulation (M&S) in the industry. A recent survey focusing on preclinical pharmacokinetic/pharmacodynamics (PK/PD) analysis was conducted across pharmaceutical companies who are members of the International Consortium for Quality and Innovation (IQ) in Pharmaceutical Development [34]. Based on the survey responses, ∼68 % of companies use preclinical PK/PD analysis in all therapeutic areas indicating its broad application, and the majority (∼86 %) indicated that systems pharmacology models are ‘sometimes’ used. Various factors have contributed to this rise in interest, including the increased cost of developing new drugs and progress made in better understanding the biology of systems making up the PBPK models and in particular the ability to predict enzyme and transporter functions in organs [27]. A 162 recent study by Poggesi and co-workers stated that while, since 2000, there has been an almost exponential rise in the use of PBPK models in the field of drug research and development, the number of publications using PBPK models for non-pharmaceutical agents has been almost at a steady-state level [23]. Commercial software platforms that facilitate rapid deployment of PBPK models have contributed to the increased use of PBPK models. Further, they paved the way for non-modellers, who historically could not easily use such models, to utilise PBPK models. Software features and values and limitations of both the ‘ready to use’ and the traditional user customizable packages are reviewed and compared elsewhere [3]. In this review, recent advances in developing PBPK models and their applications, leveraging population pharmacokinetic (PopPK) techniques in improving PBPK model performance, the impact of these models on regulatory sciences and applications and future directions are briefly discussed. IVIVE-Linked PBPK Models in a Systems Pharmacology Context By their nature, PBPK models are complex and depend on many parameters. Generally, these parameters represent combined effects of the administrated compound and the subject that the compound is administered to. For example, the fraction unbound in plasma (fu) is commonly considered as a drug parameter. However, in fact it is a combination of the drug affinity to human serum albumin and the individual’s albumin level in plasma [16]. PBPK models can be parametrised to either directly use fu, as a single value, or determine fu based on the individual’s albumin level and the drug affinity to albumin. The PBPK model structure in both of these approaches is the same. However, the latter approach allows integrating the body (system) and drug parameters to determine fu. Therefore, the covariates of PK properties, in this case the serum albumin level, are incorporated within the model which in turn facilitates predicting inter-subject variability [27]. In a systems pharmacology context, the PBPK model parameters should be divided into three categories, namely, the system or species (e.g. age, weight, height, genetic make-up, etc., of human or animal subjects), the drug (e.g. physicochemical characteristics determining permeability through membranes, partitioning to tissues, binding to plasma proteins, or affinities towards certain enzymes and transporter proteins) and the study design (e.g. dose, route and frequency of administration, the effect of concomitant drugs and food) [16]. This separation is vital to allow developing generic drugindependent models that can be used for a wide range of compounds. Further, it facilitates independent development of various databases of anatomical, biological, physiological and genetic characteristics of healthy and disease populations that can be used to simulate virtual clinical studies [27]. Curr Pharmacol Rep (2016) 2:161–169 The following factors have significantly expanded our ability to combine and integrate various prior datasets into PBPK models (see Fig. 1). & & & The availability of in vitro systems which act as surrogates for in vivo reactions relevant to the absorption, distribution, metabolism and excretion (ADME) processes Recent devel (...truncated)