Physiologically based pharmacokinetic modelling

In silico modelling and simulations are becoming increasingly common in drug development (Rowland et al., 2011). PBPK modelling is an instrument that can be used to predict the in vivo pharmacokinetics of drugs, and evaluate the effects of diverse intrinsic and extrinsic factors (such as other drugs) on their concentrations (FDA, 2012). As compared to static models, PBPK models are dynamic, thus simulating changes in drug concentrations over time.

A PBPK model consists of a system-dependent component and a drug-dependent component (Figure 9). The system-dependent module integrates physiological data on body fluid dynamics, tissue composition and sizes, abundance of drug receptors, drug-metabolising enzymes and membrane transporters in different tissues and organs (Zhao et al., 2011). Thus, it forms a ‘virtual human’, which may range from simplified, truncated models containing only a few tissue/organ compartments to very complex systems comprising multiple compartments. ‘Population-based’ PBPK models generate different populations of these

’virtual humans’, and can provide information related to variability and uncertainty of the pharmacokinetic profiles in different patient and ethnic subgroups (Rowland et al., 2011, Zhao et al., 2011).

The drug-dependent component contains in vitro and in vivo data of the drug of interest (Figure 9). Physicochemical parameters of the drug can be used to estimate its tissue partition characteristics, microsomal protein binding, and permeability (unless they have been experimentally determined) (Zhao et al., 2011). Metabolism, transport and interaction data from in vitro studies are incorporated to the model. When comprehensive drug-dependent in vivo parameters are not available, the construction of a PBPK model relies mainly on in vitro and in silico data. As in vivo data is obtained, it is integrated into the model to refine it. Thus, the model is constantly evolving as more information is acquired. Model validation is crucial when developing a PBPK model, and is done by comparing simulated pharmacokinetic profiles with those from available clinical studies (Rowland et al., 2011, Zhao et al., 2011).

Incorporation of in vitro data on the intrinsic clearance and identities of the enzymes and transporters involved in the pharmacokinetics of a drug can be used to predict its elimination and liability to drug interactions. Interaction simulations link two or more drug-dependent components (drugs) to the system-drug-dependent component. PBPK simulations can be especially useful for simulating time-dependent events such as mechanism-based inhibition and induction. Except for standard pharmacokinetic and interaction simulations, well-designed PBPK models incorporating inter-individual variability can also be used to optimise clinical study designs, and project pharmacokinetics profiles under different scenarios and in different patient populations (Zhao et al., 2011).

Figure 9.

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designs in which the same subjects receive substrate Typical study designs im drug + perpetrator drug or

victim drug + perpetrator drug followed by victim drug), one-sequence cross-over (victim drug followed by victim drug + perpetrator drug), or parallel (victim drug in one group of subjects and substrate + perpetrator drug in another group) schemes (FDA, 2012, EMA, 2013). The selection of design depends on several factors, including dosing, interaction mechanism, safety considerations etc. Due to the risk of confounding inter-individual variability, a parallel group design is usually not preferred. However, it can be useful in cases where it is not possible to perform cross-over or one-sequence studies. Unless pharmacodynamics endpoints are critical to the assessment of the interaction, clinical interaction studies can usually be performed as open studies (FDA, 2012, EMA, 2013).

Substrate and perpetrator drugs. A probe substrate should be used when testing whether the drug candidate inhibits or induces a specific enzyme or transporter. In order to see the largest impact of the interaction potential of the drug candidate, the selected probe should be one whose pharmacokinetics is markedly altered by co-administration of known specific inhibitors/inducers of the affected pathway. Cocktail approaches may be used to investigate the effect on several enzymes and transporters simultaneously. When testing the drug candidate for the possibility that its metabolism is inhibited or induced, known inhibitors/inducers of the pathway studied should be selected. Comparison of drug pharmacokinetics in poor and extensive metabolisers may replace interaction studies for a particular pathway when the drug is metabolised by a polymorphic enzyme (FDA, 2012, EMA, 2013).

Dose. Several dosing regimens of the interacting drugs can be used, including both single and multiple doses of the victim and perpetrator (FDA, 2012, EMA, 2013). When possible, the perpetrator and victim drugs should be dosed so that the exposures of both drugs are relevant to their clinical use, including the highest doses (steady state) likely to be used in clinical practice. For a drug under investigation, the administration route should be the one planned for clinical use, but lower doses can be used if there are safety concerns.

Timing of administration. Additional factors include consideration of the sequence of administration and the time interval between dosing of victim drug and perpetrator (FDA, 2012). A rapid reversible inhibitor may be administered either just before or simultaneously with the substrate to ensure maximum exposure to the two drugs together. An inducer or mechanism-based inhibitor, however, should be administered before the victim drug to maximise the effect. The maximum effect is expected to occur when the affected enzyme has reached a new steady state level. Timing of administration is particularly critical in complex interaction situations, such as concurrent inhibition and induction. Furthermore, it is important to evaluate the duration of the interaction effect after the perpetrator drug has been eliminated (FDA, 2012, EMA, 2013).

Subjects. Pharmacokinetic interaction studies are usually performed in healthy volunteers unless safety considerations preclude their participation (FDA, 2012, EMA, 2013). In some cases, the use of patients offers advantages, such as the opportunity to study pharmacodynamic markers not present in or relevant to healthy subjects. The subject number should be based on considerations taking into account intra-subject variability and the magnitude of the effect considered relevant to detect. Because the extent of drug interactions may vary depending on the genotype for the enzyme or transporter being evaluated, genotyping can be carried out when appropriate. Studies in polymorphic subpopulations are recommended when possible (FDA, 2012).

Endpoints. Changes in pharmacokinetic parameters are generally used to assess the clinical importance of drug-drug interactions (FDA, 2012, EMA, 2013). Pharmacokinetic exposure of the victim drug such as AUC, peak concentration (Cmax), time to Cmax (tmax), and others as appropriate should always be obtained. In some cases, obtaining the pharmacokinetics of the perpetrator drug may also be of interest, in particular when the study intends to assess possible changes in the disposition of both drugs. In addition, in some cases, measurement of pharmacodynamic endpoints in addition to pharmacokinetic parameters may be useful. The sampling frequency should be adequate to allow accurate determination of the relevant measures and/or parameters for the victim drug and its metabolites (FDA, 2012, EMA, 2013).