Six years of progress in the oral biopharmaceutics area - A summary from the IMI OrBiTo project.

OrBiTo was a precompetitive collaboration focused on the development of the next generation of Oral Biopharmaceutics Tools. The consortium included world leading scientists from nine universities, one regulatory agency, one non-profit research organisation, three small/medium sized specialist technology companies together with thirteen pharmaceutical companies. The goal of the OrBiTo project was to deliver a framework for rational application of predictive biopharmaceutics tools for oral drug delivery. This goal was achieved through novel prospective investigations to define new methodologies or refinement of existing tools. Extensive validation has been performed of novel and existing biopharmaceutics tools using historical datasets supplied by industry partners as well as laboratory ring studies. A combination of high quality in vitro and in vivo characterizations of active drugs and formulations have been integrated into physiologically based in silico biopharmaceutics models capturing the full complexity of gastrointestinal drug absorption and some of the best practices has been highlighted. This approach has given an unparalleled opportunity to deliver transformational change in European industrial research and development towards model based pharmaceutical product development in accordance with the vision of model-informed drug development.

Scaling Drug Clearance from Adults to the Young Children for Drugs Undergoing Hepatic Metabolism: A Simulation Study to Search for the Simplest Scaling Method.

Previous research showed that scaling drug clearance from adults to children based on body weight alone is not accurate for all hepatically cleared drugs in very young children. This study systematically assesses the accuracy of scaling methods that, in addition to body weight, also take age-based variables into account for drugs undergoing hepatic metabolism in children younger than five years, namely scaling with (1) a body weight-based function using an age-dependent exponent (ADE) and (2) a body weight-based function with fixed exponent of 0.75 (AS0.75) combined with isoenzyme maturation functions (MFPBPK) similar to those implemented in physiologically based pharmacokinetic (PBPK) models (AS0.75 + MFPBPK). A PBPK-based simulation workflow was used, including hypothetical drugs with a wide range of properties and metabolized by different isoenzymes. Adult clearance values were scaled to seven typical children between one day and four years. Prediction errors of ± 50% were considered reasonably accurate. Isoenzyme maturation was found to be an important driver of changes in hepatic metabolic clearance in children younger than five years, which prevents the systematic accuracy of ADE scaling. AS0.75 + MFPBPK, when accounting for maturation of isoenzymes and microsomal protein per gram of liver (MPPGL), can reasonably accurately scale hepatic metabolic clearance for all low and intermediate extraction ratio drugs except for drugs binding to alpha-1-acid glycoprotein in neonates. As differences in the impact of changes in system-specific parameters on drugs with different properties yield differences in clearance ontogeny, it is unlikely that for the remaining drugs, scaling methods that do not take drug properties into account will be systematically accurate.

Application of the MechPeff model to predict passive effective intestinal permeability in the different regions of the rodent small intestine and colon.

A major component of physiologically based pharmacokinetic (PBPK) models is the prediction of the rate and extent of absorption of orally dosed drugs for which knowledge of effective passive intestinal permeability (Peff ) is essential. Single-pass intestinal perfusion (SPIP) studies are used to establish effective permeability in vivo but are difficult to perform in rodents, while mechanistic models to predict drug Peff in rat and mouse have not been published. This work evaluates the predictive performance of the 'MechPeff' model to predict Peff in the rodent intestine based upon knowledge of regional gut physiology and drug-specific physicochemical parameters. The 'MechPeff' model, built-in to the Simcyp Rat and Mouse Simulators, predicts transcellular, paracellular and mucus layer permeabilities and combines these to give the overall Peff . The jejunal and/or ileal Peff was predicted for 12 (4) acidic, 13 (12) basic, 10 (8) neutral and 2 (0) ampholytic drugs in the rat (mouse), spanning a wide range of MW and logPo:w , and compared with experimental Peff obtained using SPIP. A key input is the intrinsic transcellular permeability (Ptrans,0 ) which can be derived from modelling of appropriate in vitro permeability experiments or predicted from physicochemical properties. The Peff predictions were reasonably good when experimentally derived Ptrans,0 was used; from 42 Peff,rat values, 24 (57%) were within 3-fold, and of 19 Peff,mouse values, 12 (63%) were within 3-fold, of observed Peff . Considering the lack of alternative models to predict Peff in preclinical species, and the minimal drug-specific inputs required, this model provides a valuable tool within drug discovery and development programmes. Copyright © 2017 John Wiley & Sons, Ltd.

Why has model-informed precision dosing not yet become common clinical reality? lessons from the past and a roadmap for the future.

Patient groups prone to polypharmacy and special subpopulations are susceptible to suboptimal treatment. Refined dosing in special populations is imperative to improve therapeutic response and/or lowering the risk of toxicity. Model-informed precision dosing (MIPD) may improve treatment outcomes by achieving the optimal dose for an individual patient. There is, however, relatively little published evidence of large-scale utility and impact of MIPD, where it is often implemented as local collaborative efforts between academia and healthcare. This article highlights some successful applications of bringing MIPD to clinical care and proposes strategies for wider integration in healthcare. Considerations are brought up herein that will need addressing to see MIPD become "widespread clinical practice," among those, wider interdisciplinary collaborations and the necessity for further evidence-based efficacy and cost-benefit analysis of MIPD in healthcare. The implications of MIPD on regulatory policies and pharmaceutical development are also discussed as part of the roadmap.

Metformin and cimetidine: Physiologically based pharmacokinetic modelling to investigate transporter mediated drug-drug interactions.

Metformin is used as a probe for OCT2 mediated transport when investigating possible DDIs with new chemical entities. The aim of the current study was to investigate the ability of physiologically-based pharmacokinetic (PBPK) models to simulate the effects of OCT and MATE inhibition by cimetidine on metformin kinetics. PBPK models were developed, incorporating mechanistic kidney and liver sub-models for metformin (OCT and MATE substrate) and a mechanistic kidney sub-model for cimetidine. The models were used to simulate inhibition of the MATE1, MATE2-K, OCT1 and OCT2 mediated transport of metformin by cimetidine. Assuming competitive inhibition and using cimetidine Ki values determined in vitro, the predicted metformin AUC ratio was 1.0 compared to an observed value of 1.46. The observed AUC ratio could only be recovered with this model when the cimetidine Ki for OCT2 was decreased 1000-fold or the Ki's for both OCT1 and OCT2 were decreased 500-fold. An alternative description of metformin renal transport by OCT1 and OCT2, incorporating electrochemical modulation of the rate of metformin uptake together with 8-18-fold decreases in cimetidine Ki's for OCTs and MATEs, allowed recovery of the extent of the observed effect of cimetidine on metformin AUC. While the final PBPK model has limitations, it demonstrates the benefit of allowing for the complexities of passive permeability combined with active cellular uptake modulated by an electrochemical gradient and active efflux.

Semiphysiologically based pharmacokinetic model for midazolam and CYP3A mediated metabolite 1-OH-midazolam in morbidly obese and weight loss surgery patients.

This study aimed to describe the pharmacokinetics of midazolam and its cytochrome P450 3A (CYP3A) mediated metabolite 1-OH-midazolam in morbidly obese patients receiving oral and i.v. midazolam before (n = 20) and one year after weight loss surgery (n = 18), thereby providing insight into the influence of weight loss surgery on CYP3A activity in the gut wall and liver. In a semiphysiologically based pharmacokinetic (semi-PBPK) model in which different blood flow scenarios were evaluated, intrinsic hepatic clearance of midazolam (CLint,H) was 2 (95% CI 1.40-1.64) times higher compared to morbidly obese patients before surgery (P < 0.01). Midazolam gut wall clearance (CLint,G) was slightly lower in patients after surgery (P > 0.05), with low values for both groups. The results of the semi-PBPK model suggest that, in patients after weight loss surgery, CYP3A hepatic metabolizing capacity seems to recover compared to morbidly obese patients, whereas CYP3A mediated CLint,G was low for both populations and showed large interindividual variability.

Systematic and quantitative assessment of the effect of chronic kidney disease on CYP2D6 and CYP3A4/5.

Recent reviews suggest that chronic kidney disease (CKD) can affect the pharmacokinetics of nonrenally eliminated drugs, but the impact of CKD on individual elimination pathways has not been systematically evaluated. In this study we developed a comprehensive dataset of the effect of CKD on the pharmacokinetics of CYP2D6- and CYP3A4/5-metabolized drugs. Drugs for evaluation were selected based on clinical drug-drug interaction (CYP3A4/5 and CYP2D6) and pharmacogenetic (CYP2D6) studies. Information from dedicated CKD studies was available for 13 and 18 of the CYP2D6 and CYP3A4/5 model drugs, respectively. Analysis of these data suggested that CYP2D6-mediated clearance is generally decreased in parallel with the severity of CKD. There was no apparent relationship between the severity of CKD and CYP3A4/5-mediated clearance. The observed elimination-route dependency in CKD effects between CYP2D6 and CYP3A4/5 may inform the need to conduct clinical CKD studies with nonrenally eliminated drugs for optimal use of drugs in patients with CKD.

Physiologically Based Pharmacokinetics Is Impacting Drug Development and Regulatory Decision Making.

It is no coincidence that the reports of two meetings, one organized by the US Food and Drug Administration (FDA), in March 2014, and the other by the UK Medicines and Healthcare Products Regulatory (MHRA), in collaboration with ABPI (the Association of British Pharmaceutical Industry), in June 2014, have been published in tandem in CPT-PSP.12 Both reports deal with the same topic, namely, the impact of physiologically based pharmacokinetics (PBPK) in clinical drug development and the best practices for such applications. This reflects the transition of PBPK from academic curiosity to industrial norm, manifested by the regulatory agencies encouraging its use and receiving an increasing number of submissions containing PBPK models. The goal of both meetings was to help determine the need and facilitate the development of regulatory guidances on this subject within the conceptual framework of model informed drug development and regulatory decision-making. A further reflection of this intent is the publication by the European Medicines Agency of a Concept Paper on PBPK.3 One is reminded of a similar train of events surrounding the introduction of population PK/PD and nonlinear mixed effects modeling in the early-late 1990s, again with encouragement and receptivity of regulatory agencies leading to FDA guidance on the topic.4 Indeed, the intention of PBPK modeling and simulation is to complement other approaches, such as compartmental modeling, or, in some cases, replace them with a more mechanistic approach. PBPK models represent an important class of models that characterize absorption, distribution, metabolism, excretion (ADME) processes and their underlying biological and physiological drivers. An increased understanding of these drivers and their unique interactions with drug substance and formulation factors provides critical insights into how drugs will behave in healthy volunteers and patients with disease.

Application of an LC-MS/MS method for the simultaneous quantification of human intestinal transporter proteins absolute abundance using a QconCAT technique.

Transporter proteins expressed in the gastrointestinal tract play a major role in the oral absorption of some drugs, and their involvement may lead to drug-drug interaction (DDI) susceptibility when given in combination with drugs known to inhibit gut wall transporters. Anticipating such liabilities and predicting the magnitude of the impact of transporter proteins on oral drug absorption and DDIs requires quantification of their expression in human intestine, and linking these to data obtained through in vitro experiments. A quantitative targeted absolute proteomic method employing liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) together with a quantitative concatenation (QconCAT) strategy to provide proteotypic peptide standards has been applied to quantify ATP1A1 (sodium/potassium-ATPase; Na/K-ATPase), CDH17 (human peptide transporter 1; HPT1), ABCB1 (P-glycoprotein; P-gp), ABCG2 (breast cancer resistance protein; BCRP), ABCC2 (multidrug resistance-associated protein 2; MRP2) and SLC51A (Organic Solute Transporter subunit alpha; OST-α), in human distal jejunum (n=3) and distal ileum (n=1) enterocyte membranes. Previously developed selected reaction monitoring (SRM) schedules were optimised to enable quantification of the proteotypic peptides for each transporter. After harvesting enterocytes by calcium chelation elution and generating a total membrane fraction, the proteins were subjected to proteolytic digestion. To account for losses of peptides during the digestion procedure, a gravimetric method is also presented. The linearity of quantifying the QconCAT from an internal standard (correlation coefficient, R(2)=0.998) and quantification of all target peptides in a pooled intestinal quality control sample (R(2)≥ 0.980) was established. The assay was also assessed for within and between-day precision, demonstrating a <15% coefficient of variation for all peptides across 3 separate analytical runs, over 2 days. The methods were applied to obtain the absolute abundances for all targeted proteins. In all samples, Na/K-ATPase, HPT1, P-gp and BCRP were detected above the lower limit of quantitation (i.e., >0.2 fmol/µg membrane protein). MRP2 abundance could be quantified in distal jejunum but not in the distal ileum sample. OST-α was not detected in 2 out of 3 jejunum samples. This study highlights the utility of a QconCAT strategy to quantify absolute transporter abundances in human intestinal tissues.

Interaction Between Domperidone and Ketoconazole: Toward Prediction of Consequent QTc Prolongation Using Purely In Vitro Information.

We aimed to investigate the application of combined mechanistic pharmacokinetic (PK) and pharmacodynamic (PD) modeling and simulation in predicting the domperidone (DOM) triggered pseudo-electrocardiogram modification in the presence of a CYP3A inhibitor, ketoconazole (KETO), using in vitro-in vivo extrapolation. In vitro metabolic and inhibitory data were incorporated into physiologically based pharmacokinetic (PBPK) models within Simcyp to simulate time course of plasma DOM and KETO concentrations when administered alone or in combination with KETO (DOM+KETO). Simulated DOM concentrations in plasma were used to predict changes in gender-specific QTcF (Fridericia correction) intervals within the Cardiac Safety Simulator platform taking into consideration DOM, KETO, and DOM+KETO triggered inhibition of multiple ionic currents in population. Combination of in vitro-in vivo extrapolation, PBPK, and systems pharmacology of electric currents in the heart was able to predict the direction and magnitude of PK and PD changes under coadministration of the two drugs although some disparities were detected.

Application of a Physiologically Based Pharmacokinetic Model to Predict OATP1B1-Related Variability in Pharmacodynamics of Rosuvastatin.

Typically, pharmacokinetic-pharmacodynamic (PK/PD) models use plasma concentration as the input that drives the PD model. However, interindividual variability in uptake transporter activity can lead to variable drug concentrations in plasma without discernible impact on the effect site organ concentration. A physiologically based PK/PD model for rosuvastatin was developed that linked the predicted liver concentration to the PD response model. The model was then applied to predict the effect of genotype-dependent uptake by the organic anion-transporting polypeptide 1B1 (OATP1B1) transporter on the pharmacological response. The area under the plasma concentration-time curve (AUC0-∞) was increased by 63 and 111% for the c.521TC and c.521CC genotypes vs. the c.521TT genotype, while the PD response remained relatively unchanged (3.1 and 5.8% reduction). Using local concentration at the effect site to drive the PD response enabled us to explain the observed disconnect between the effect of the OATP1B1 c521T>C polymorphism on rosuvastatin plasma concentration and the cholesterol synthesis response.

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. Age, weight, Japanese ethnicity, and seven genetic polymorphisms-rs4149056 (SLCO1B1), rs776746 (CYP3A5), rs12422149 (SLCO2B1), rs2231142 (ABCG2), rs4148162 (ABCG2), rs4253728 (PPARA), and rs35599367 (CYP3A4)-were identified as significantly affecting model parameters. The developed model was used to assess combinations of these covariates, highlighting specific risk factors associated with altered SV/SVA pharmacokinetics, and consequently myopathy cases that cannot be solely attributed to the rs4149056 CC genotype.

Oral biopharmaceutics tools - time for a new initiative - an introduction to the IMI project OrBiTo.

OrBiTo is a new European project within the IMI programme in the area of oral biopharmaceutics tools that includes world leading scientists from nine European universities, one regulatory agency, one non-profit research organization, four SMEs together with scientists from twelve pharmaceutical companies. The OrBiTo project will address key gaps in our knowledge of gastrointestinal (GI) drug absorption and deliver a framework for rational application of predictive biopharmaceutics tools for oral drug delivery. This will be achieved through novel prospective investigations to define new methodologies as well as refinement of existing tools. Extensive validation of novel and existing biopharmaceutics tools will be performed using active pharmaceutical ingredient (API), formulations and supporting datasets from industry partners. A combination of high quality in vitro or in silico characterizations of API and formulations will be integrated into physiologically based in silico biopharmaceutics models capturing the full complexity of GI drug absorption. This approach gives an unparalleled opportunity to initiate a transformational change in industrial research and development to achieve model-based pharmaceutical product development in accordance with the Quality by Design concept. Benefits include an accelerated and more efficient drug candidate selection, formulation development process, particularly for challenging projects such as low solubility molecules (BCS II and IV), enhanced and modified-release formulations, as well as allowing optimization of clinical product performance for patient benefit. In addition, the tools emerging from OrBiTo are expected to significantly reduce demand for animal experiments in the future as well as reducing the number of human bioequivalence studies required to bridge formulations after manufacturing or composition changes.

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. To address this, an in vitro-in vivo extrapolation (IVIVE)-linked mechanistic physiologically based pharmacokinetic (PBPK) framework for modelling liver transporters and their interplay with liver metabolising enzymes has been developed and implemented within the Simcyp Simulator(®). METHODS: In this article an IVIVE technique for liver transporters is described and a full-body PBPK model is developed. Passive and active (saturable) transport at both liver sinusoidal and canalicular membranes are accounted for and the impact of binding and ionisation processes is considered. The model also accommodates tDDIs involving inhibition of multiple transporters. Integrating prior in vitro information on the metabolism and transporter kinetics of rosuvastatin (organic-anion transporting polypeptides OATP1B1, OAT1B3 and OATP2B1, sodium-dependent taurocholate co-transporting polypeptide [NTCP] and breast cancer resistance protein [BCRP]) with one clinical dataset, the PBPK model was used to simulate the drug disposition of rosuvastatin for 11 reported studies that had not been used for development of the rosuvastatin model. RESULTS: The simulated area under the plasma concentration-time curve (AUC), maximum concentration (C max) and the time to reach C max (t max) values of rosuvastatin over the dose range of 10-80 mg, were within 2-fold of the observed data. Subsequently, the validated model was used to investigate the impact of coadministration of cyclosporine (ciclosporin), an inhibitor of OATPs, BCRP and NTCP, on the exposure of rosuvastatin in healthy volunteers. CONCLUSION: The results show the utility of the model to integrate a wide range of in vitro and in vivo data and simulate the outcome of clinical studies, with implications for their design.

Pharmacometrics and Systems Pharmacology Software Tutorials and Use: Comments and Guidelines for PSP Contributions.

In addition to methodological Tutorials,(1) CPT:PSP has recently started to publish software Tutorials.(2,3) Our readership and authors may be wondering what kind of format or product is expected, and the review of submissions we have already received prompted several discussions within the PSP Editorial Team. This editorial reflects on these discussions and summarizes their salient points. It aims at providing some details about the current vision of CPT:PSP for software tutorial articles. In addition, it brings some clarity on the topic of what role commercial software tutorials can have in CPT:PSP and how CPT:PSP tutorials differ from publications which describe the software itself, as those which can be found in other computer science journals. Finally, the discussion includes reproducibility considerations and the general use of commercial and noncommercial software in CPT:PSP publications. We hope our thoughts, and especially a stated requirement to publish user input to the software to aid in reproducibility, will help in guiding our authors and will stimulate healthy debate among our readers about the evolving nature of our science, how it can be facilitated using software and associated databases as a conduit, and what role this journal can play in fostering both the best modeling and simulation practices and the best scientific approaches to computational modeling, to bring the advantages of modeling and simulation to all regular practitioners, and not to just a (self) selected few.

Evaluation of an In Silico PBPK Post-Bariatric Surgery Model through Simulating Oral Drug Bioavailability of Atorvastatin and Cyclosporine.

An increasing prevalence of morbid obesity has led to dramatic increases in the number of bariatric surgeries performed. Altered gastrointestinal physiology following surgery can be associated with modified oral drug bioavailability (Foral). In the absence of clinical data, an indication of changes to Foral via systems pharmacology models would be of value in adjusting dose levels after surgery. A previously developed virtual "post-bariatric surgery" population was evaluated through mimicking clinical investigations on cyclosporine and atorvastatin after bariatric surgery. Cyclosporine simulations displayed a reduced fraction absorbed through gut wall (fa) and Foral after surgery, consistent with reported observations. Simulated atorvastatin Foral postsurgery was broadly reflective of observed data with indications of counteracting interplay between reduced fa and an increased fraction escaping gut wall metabolism (FG). Inability to fully recover observed atorvastatin exposure after biliopancreatic diversion with duodenal switch highlights the current gap regarding the knowledge of associated biological changes.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e47; doi:10.1038/psp.2013.23; advance online publication 12 June 2013.

A physiologically based pharmacokinetic modeling approach to predict disease-drug interactions: suppression of CYP3A by IL-6.

Elevated cytokine levels are known to downregulate expression and suppress activity of cytochrome P450 enzymes (CYPs). Cytokine-modulating therapeutic proteins (TPs) used in the treatment of inflammation or infection could reverse suppression, manifesting as TP-drug-drug interactions (TP-DDIs). A physiologically based pharmacokinetic model was used to quantitatively predict the impact of interleukin-6 (IL-6) on sensitive CYP3A4 substrates. Elevated simvastatin area under the plasma concentration-time curve (AUC) in virtual rheumatoid arthritis (RA) patients, following 100 pg/ml of IL-6, was comparable to observed clinical data (59 vs. 58%). In virtual bone marrow transplant (BMT) patients, 500 pg/ml of IL-6 resulted in an increase in cyclosporine AUC, also in good agreement with the observed data (45 vs. 39%). In a different group of BMT patients treated with cyclosporine, the magnitude of interaction with IL-6 was underpredicted by threefold. The complexity of TP-DDIs highlights underlying pathophysiological factors to be considered, but these simulations provide valuable first steps toward predicting TP-DDI risk.

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. This review summarizes the mechanistic approaches to integrate suitable non-biased in vitro transporter kinetic data relevant to the intestine (i.e. 'intrinsic' K(i) , 'intrinsic' K(m) ), by in vitro system modelling for these kinetic inputs with the advantages of, and challenges for, generating these data for input into PBPK models. This step is considered as a prerequisite for mechanistic modelling of the oral absorption for drugs that are substrates for transporters. Various approaches are provided to integrate intestinal transporter expression into PBPK models with a perspective on the incorporation of the absolute abundance/activity of transporters to enhance the predictive power of the models. We define the key intestinal tissue and functional expression-based scaling factors required. The objective is to use these for facilitating the extrapolation from in vitro intestinal transporter assays to the in vivo system, using absolute quantification methodologies. The models could be used to elucidate the complex relationship and relative importance of metabolizing enzymes and transporters in drug disposition and toxicity.

Physiologically based pharmacokinetics joined with in vitro-in vivo extrapolation of ADME: a marriage under the arch of systems pharmacology.

Classic pharmacokinetics (PK) rarely takes into account the full knowledge of physiology and biology of the human body. However, physiologically based PK (PBPK) is built mainly from drug-independent "system" information. PBPK is not a new concept, but it has shown a very rapid rise in recent years. This has been attributed to a greater connectivity to in vitro-in vivo extrapolation (IVIVE) techniques for predicting drug absorption, distribution, metabolism, and excretion (ADME) and their variability in humans. The marriage between PBPK and IVIVE under the overarching umbrella of "systems biology" has removed many constraints related to cutoff approaches on prediction of ADME. PBPK-IVIVE linked models have repeatedly shown their value in guiding decisions when predicting the effects of intrinsic and extrinsic factors on PK of drugs. A review of the achievements and shortcomings of the models might suggest better strategies in extending the success of PBPK-IVIVE to pharmacodynamics (PD) and drug safety.