Identification of the effect of multiple polymorphisms on the pharmacokinetics of simvastatin and simvastatin acid using a population-modeling approach.

The aim of this work was to develop a joint population pharmacokinetic model for simvastatin (SV) and its active metabolite, simvastatin acid (SVA), that incorporates the effects of multiple genetic polymorphisms and clinical/demographic characteristics. SV/SVA plasma concentrations, demographic/clinical data, and genotypes for 18 genetic variants were collected from 74 individuals (three clinical trials) and analyzed using a nonlinear mixed-effects modeling approach. The structural model that best described the data included a two- and a one-compartment disposition model for SV and SVA, respectively.

The effects of six antipsychotic agents on QTc--an attempt to mimic clinical trial through simulation including variability in the population.

Background: Many drugs (belonging to different chemical groups) have the potential for QT interval prolongation associated with ionic channel blockade in the cardiomyocyte membrane. Due to the fact that this phenomenon is linked to a higher risk of TdP, the ability to predict its scale is one of the most important outcomes of cardiotoxicity assessment of new agents.

Methods: With use of the Cardiac Safety Simulator (CSS), the effect of six antipsychotic drugs was predicted in silico.

Incorporating Target Shedding Into a Minimal PBPK-TMDD Model for Monoclonal Antibodies.

Shedding of a pharmacological target from cells, giving rise to a soluble target that can also bind therapeutic proteins, is a common phenomenon. In this study, a minimal physiologically based pharmacokinetic model was used to simulate the pharmacokinetics of trastuzumab and the simultaneous binding of the compound to soluble (in blood and tissue interstitial space) and membrane-bound (in the tissue interstitial space) forms of human epidermal growth factor receptor 2 (HER2). The parameter values describing binding of trastuzumab to HER2 were largely derived from in vitro data, and the effects of varying HER2 levels, the affinity difference between membrane-bound HER2 and shed antigen, and slow binding kinetics were investigated.

In vitro-in vivo extrapolation of drug-induced proarrhythmia predictions at the population level.

Drug cardiotoxicity is a serious issue for patients, regulators, pharmaceutical companies and health service payers because they are all affected by its consequences. Despite the wide range of data they generate, existing approaches for cardiac safety testing might not be adequate and sufficiently cost-effective, probably as a result of the complexity of the problem. For this reason, translational tools (based on biophysically detailed, mathematical models) allowing for in vitro-in vivo extrapolation are gaining increasing interest.

PBPK models for the prediction of in vivo performance of oral dosage forms.

Drug absorption from the gastrointestinal (GI) tract is a highly complex process dependent upon numerous factors including the physicochemical properties of the drug, characteristics of the formulation and interplay with the underlying physiological properties of the GI tract. The ability to accurately predict oral drug absorption during drug product development is becoming more relevant given the current challenges facing the pharmaceutical industry. Physiologically-based pharmacokinetic (PBPK) modeling provides an approach that enables the plasma concentration-time profiles to be predicted from preclinical in vitro and in vivo data and can thus provide a valuable resource to support decisions at various stages of the drug development process.

Quantitative prediction of formulation-specific food effects and their population variability from in vitro data with the physiologically-based ADAM model: a case study using the BCS/BDDCS Class II drug nifedipine.

Quantitative prediction of food effects (FE) upon drug pharmacokinetics, including population variability, in advance of human trials may help with trial design by optimising the number of subjects and sampling times when a clinical study is warranted or by negating the need for conduct of clinical studies. Classification and rule-based systems such as the BCS and BDDCS and statistical QSARs are widely used to anticipate the nature of FE in early drug development. However, their qualitative rather than quantitative nature makes them less appropriate for assessing the magnitude of FE.

Animal versus human oral drug bioavailability: do they correlate?

Oral bioavailability is a key consideration in development of drug products, and the use of preclinical species in predicting bioavailability in human has long been debated. In order to clarify whether any correlation between human and animal bioavailability exist, an extensive analysis of the published literature data was conducted. Due to the complex nature of bioavailability calculations inclusion criteria were applied to ensure integrity of the data.

A mechanistic framework for in vitro-in vivo extrapolation of liver membrane transporters: prediction of drug-drug interaction between rosuvastatin and cyclosporine.

Background And Objectives: The interplay between liver metabolising enzymes and transporters is a complex process involving system-related parameters such as liver blood perfusion as well as drug attributes including protein and lipid binding, ionisation, relative magnitude of passive and active permeation. Metabolism- and/or transporter-mediated drug-drug interactions (mDDIs and tDDIs) add to the complexity of this interplay. Thus, gaining meaningful insight into the impact of each element on the disposition of a drug and accurately predicting drug-drug interactions becomes very challenging.

Differences in cytochrome p450-mediated pharmacokinetics between chinese and caucasian populations predicted by mechanistic physiologically based pharmacokinetic modelling.

Background: International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) guidelines emphasize the need for better understanding of the influence of ethnicity on drug response to minimize duplication of clinical studies, thereby expediting drug approval.

Objectives: We have developed a Chinese database for the prediction of differences in the population kinetics of drugs mainly metabolized by cytochromes P450 (CYPs) relative to Caucasian populations. Such predictions should help to inform the need for duplication of in vivo pharmacokinetic studies in the two ethnic groups and the design of such studies.

Application of permeability-limited physiologically-based pharmacokinetic models: part I-digoxin pharmacokinetics incorporating P-glycoprotein-mediated efflux.

A prerequisite for the prediction of the magnitude of P-glycoprotein (P-gp)-mediated drug-drug interactions between digoxin and P-gp inhibitors (e.g. verapamil and its metabolite norverapamil) or P-gp inducers (e.

Application of permeability-limited physiologically-based pharmacokinetic models: part II - prediction of P-glycoprotein mediated drug-drug interactions with digoxin.

Digoxin is the recommended substrate for assessment of P-glycoprotein (P-gp)-mediated drug-drug interactions (DDIs) in vivo. The overall aim of our study was to investigate the inhibitory potential of both verapamil and norverapamil on the P-gp-mediated efflux of digoxin in both gut and liver. Therefore, a physiologically-based pharmacokinetic (PBPK) model for verapamil and its primary metabolite was developed and validated through the recovery of observed clinical plasma concentration data for both moieties and the reported interaction with midazolam, albeit a cytochrome P450 3A4-mediated DDI.

S[+] Apomorphine is a CNS penetrating activator of the Nrf2-ARE pathway with activity in mouse and patient fibroblast models of amyotrophic lateral sclerosis.

Compelling evidence indicates that oxidative stress contributes to motor neuron injury in amyotrophic lateral sclerosis (ALS), but antioxidant therapies have not yet achieved therapeutic benefit in the clinic. The nuclear erythroid 2-related-factor 2 (Nrf2) transcription factor is a key regulator of an important neuroprotective response by driving the expression of multiple cytoprotective genes via its interaction with the antioxidant response element (ARE). Dysregulation of the Nrf2-ARE system has been identified in ALS models and human disease.

Predicting drug-drug interactions: application of physiologically based pharmacokinetic models under a systems biology approach.

The development of in vitro-in vivo extrapolation (IVIVE), a 'bottom-up' approach, to predict pharmacokinetic parameters and drug-drug interactions (DDIs) has accelerated mainly due to an increase in the understanding of the multiple mechanisms involved in these interactions and the availability of appropriate in vitro systems that act as surrogates for delineating various elements of the interactions relevant to absorption, distribution, metabolism and elimination. Recent advances in the knowledge of the population variables required for IVIVE (demographic, anatomical, genetic and physiological parameters) have also contributed to the appreciation of the sources of variability and wider use of this approach for different scenarios within the pharmaceutical industry. Initially, the authors present an overview of the integration of IVIVE into 'static' and 'dynamic' models for the quantitative prediction of DDIs.

Application of in vitro-in vivo extrapolation (IVIVE) and physiologically based pharmacokinetic (PBPK) modelling to investigate the impact of the CYP2C8 polymorphism on rosiglitazone exposure.

Purpose: To predict the impact of the CYP2C8 3 genotype on rosiglitazone exposure in the absence and presence of trimethoprim.

Methods: Prior in vitro and in vivo information for rosiglitazone and trimethoprim were collated from the literature. Specifically, data on the frequency of the different allelic forms of CYP2C8 and their metabolic activity for rosiglitazone were incorporated into a physiologically-based pharmacokinetic (PBPK) model within the Simcyp Simulator (V11.

Novel and mathematical models for the prediction of chemical toxicity.

The focus of much scientific and medical research is directed towards understanding the disease process and defining therapeutic intervention strategies. The scientific basis of drug safety is very complex and currently remains poorly understood, despite the fact that adverse drug reactions (ADRs) are a major health concern and a serious impediment to development of new medicines. Toxicity issues account for ∼21% drug attrition during drug development and safety testing strategies require considerable animal use.

The simcyp population based simulator: architecture, implementation, and quality assurance.

Developing a user-friendly platform that can handle a vast number of complex physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models both for conventional small molecules and larger biologic drugs is a substantial challenge. Over the last decade the Simcyp Population Based Simulator has gained popularity in major pharmaceutical companies (70% of top 40 - in term of R&D spending). Under the Simcyp Consortium guidance, it has evolved from a simple drug-drug interaction tool to a sophisticated and comprehensive Model Based Drug Development (MBDD) platform that covers a broad range of applications spanning from early drug discovery to late drug development.

Absolute abundance and function of intestinal drug transporters: a prerequisite for fully mechanistic in vitro-in vivo extrapolation of oral drug absorption.

The use of whole body physiological-based pharmacokinetic (PBPK) models linked with in vitro-in vivo extrapolation (IVIVE) of kinetic parameters from laboratory experiments, has become embedded within many of the pharmaceutical industry and is used even as part of regulatory submissions. These include the influence of transporter proteins on drug disposition, a subject for which we have witnessed an increasing awareness. A combination of the development of high-powered analytical techniques and antibody-based technology, together with a realization that an understanding of absolute transporter protein abundances together with activity can potentially enhance the modelling of transporter kinetics by PBPK-IVIVE link models.

Anatomical, physiological and metabolic changes with gestational age during normal pregnancy: a database for parameters required in physiologically based pharmacokinetic modelling.

Background: Pregnancy is associated with considerable changes in the physiological, anatomical and biochemical attributes in women. These may alter the exposure to xenobiotics between pregnant and non-pregnant women who receive similar doses, with implications for different susceptibility to environmental pollutants or therapeutic agents. Physiologically based pharmacokinetic (PBPK) models together with in vitro in vivo extrapolation (IVIVE) of absorption, distribution, metabolism and excretion (ADME) characteristics may capture the likely changes.

Physiologically-based pharmacokinetic (PBPK) models for assessing the kinetics of xenobiotics during pregnancy: achievements and shortcomings.

The physiological changes that occur in the maternal body and the placental-foetal unit during pregnancy influence the absorption, distribution, metabolism, and excretion (ADME) of xenobiotics. These include drugs that are prescribed for therapeutic reasons or chemicals to which women are exposed unintentionally from the surrounding environment. The pregnancy physiologically-based pharmacokinetic (p-PBPK) models developed for theoretical assessment of the kinetics of xenobiotics during pregnancy should take into account all the dynamic changes of the maternal and embryonic/foetal physiological functions.

Sex differences in the clearance of CYP3A4 substrates: exploring possible reasons for the substrate dependency and lack of consensus.

Sex differences in the clearance of substrates of Cytochrome P4503A (CYP3A4) have been reported frequently although there has been no consensus on reasons for variation in observations amongst drugs which are seemingly all dependent on this enzyme for their metabolism. Moreover, these observations could not be replicated in all studies even when investigating the same drugs. Differing study designs and inadequate power to identify the sex differences may explain the conflicting reports.

Research priorities in pharmacokinetics.

An opinion is expressed on the past, present and future roles of pharmacokinetic-pharmacodynamic research in the context of UK clinical pharmacology. On the basis of its current constitution, it seems unlikely that this area of research will be driven from within academic clinical pharmacology in the UK. Therefore, in order to bring its expertise and experience to bear effectively on the evolving emphasis on translational medicine and modelling and simulation, this community would need to reach out beyond its current preoccupations to increase interactions with the next generation of pharmacokineticists and pharmacometricians.

Modeling and predicting drug pharmacokinetics in patients with renal impairment.

Current guidance issued by the US FDA to assess the impact of renal impairment on the pharmacokinetics of a drug under development has recently been updated to include evaluation of drugs with nonrenal elimination routes. Renal impairment not only affects elimination of the drug in the kidney, but also the nonrenal route of drugs that are extensively metabolized in the liver. Renal failure may influence hepatic drug metabolism either by inducing or suppressing hepatic enzymes, or by its effects on other variables such as protein binding, hepatic blood flow and accumulation of metabolites.

Prediction of time-dependent CYP3A4 drug-drug interactions by physiologically based pharmacokinetic modelling: impact of inactivation parameters and enzyme turnover.

Predicting the magnitude of time-dependent metabolic drug-drug (mDDIs) interactions involving cytochrome P-450 3A4 (CYP3A4) from in vitro data requires accurate knowledge of the inactivation parameters of the inhibitor (K(I), k(inact)) and of the turnover of the enzyme (k(deg)) in both the gut and the liver. We have predicted the magnitude of mDDIs observed in 29 in vivo studies involving six CYP3A4 probe substrates and five mechanism based inhibitors of CYP3A4 of variable potency (azithromycin, clarithromycin, diltiazem, erythromycin and verapamil). Inactivation parameters determined anew in a single laboratory under standardised conditions together with data from substrate and inhibitor files within the Simcyp Simulator (Version 9.

Sources of interindividual variability in IVIVE of clearance: an investigation into the prediction of benzodiazepine clearance using a mechanistic population-based pharmacokinetic model.

Prediction of metabolic clearance in extreme individuals rather than the 'average human' is becoming an attractive tool within the pharmaceutical industry. The current study involved prediction of variability in metabolic clearance for alprazolam, triazolam and midazolam with emphasis on the following factors: first, evaluation of clearance prediction accuracy using intrinsic clearance (CL(int)) data from in vitro metabolic data and back-calculation from in vivo clearance data. Second, the sensitivity of predicted in vivo variability to changes in variability for physiological parameters (e.