Quantitation of Plasma Membrane Drug Transporters in Kidney Tissue and Cell Lines Using a Novel Proteomic Approach Enabled a Prospective Prediction of Metformin Disposition.

The successful prospective incorporation of in vitro transporter kinetics in physiologically based pharmacokinetic (PBPK) models to describe drug disposition remains challenging. Although determination of scaling factors to extrapolate in vitro to in vivo transporter kinetics has been facilitated by quantitative proteomics, no robust assessment comparing membrane recoveries between different cells/tissues has been made. HEK293 cells overexpressing OCT2, MATE1, and MATE2K or human kidney cortex were homogenized and centrifuged to obtain the total membrane fractions, which were subsequently subjected to liquid-liquid extraction followed by centrifugation and precipitation to isolate plasma membrane fractions. Plasma membrane recoveries determined by quantitation of the marker Na+/K+-ATPase in lysate and plasma membrane fractions were ≤20% but within 3-fold across different cells and tissues. A separate study demonstrated that recoveries are comparable between basolateral and apical membranes of renal proximal tubules, as measured by Na+/K+-ATPase and γ-glutamyl transpeptidase 1, respectively. The plasma membrane expression of OCT2, MATE1, and MATE2K was quantified and relative expression factors (REFs) were determined as the ratio between the tissue and cell concentrations. Corrections using plasma membrane recovery had minimal impact on REF values (<2-fold). In vitro transporter kinetics of metformin were extrapolated to in vivo using the corresponding REFs in a PBPK model. The simulated metformin exposures were within 2-fold of clinical exposure. These results demonstrate that transporter REFs based on plasma membrane expression enable a prediction of transporter-mediated drug disposition. Such REFs may be estimated without the correction of plasma membrane recovery when the same procedure is applied between different matrices. SIGNIFICANCE STATEMENT: Transporter REFs based on plasma membrane expression enable in vitro-in vivo extrapolation of transporter kinetics. Plasma membrane recoveries as determined by the quantification of sodium-potassium adenosine triphosphatase were comparable between the in vitro and in vivo systems used in the present study, and therefore had minimal impact on the transporter REF values.

Organic anion transporters and their implications in pharmacotherapy.

Organic anion transporters play an essential role in the distribution and excretion of numerous endogenous metabolic products and exogenous organic anions, including a host of widely prescribed drugs. The expression and activity of these transporters is influenced by several conditions, including transcriptional regulation, gender-dependent regulation, and genetic variation. In addition, the interaction of these transporters with several drugs and endogenous substrates has been well documented and may play a significant role in drug disposition and development of various disease states, such as nephrotoxicity and familial idiopathic hypouricemia. Members of this family of transporters have been localized mainly to the renal epithelia of various species. Much of the early research in this field has focused on their role in renal drug transport, yet increasing research on this family of transporters has localized them to various other epithelial tissues, including liver, brain, and placenta. Thus, an understanding of the role of these transporters in drug interaction and disposition in the kidney and other tissues may help in the determination of individual drug response, susceptibility to drug toxicity, and chemical carcinogenesis. This review seeks to summarize current knowledge of the molecular function and substrate profile of cloned organic anion transporters and to discuss recent progress in the understanding of the impact of interindividual variability, transcriptional regulation, and tissue distribution on individual drug response.

Current Practices, Gap Analysis, and Proposed Workflows for PBPK Modeling of Cytochrome P450 Induction: An Industry Perspective.

The International Consortium for Innovation and Quality (IQ) Physiologically Based Pharmacokinetic (PBPK) Modeling Induction Working Group (IWG) conducted a survey across participating companies around general strategies for PBPK modeling of induction, including experience with its utility to address various questions, regulatory interactions, and regulatory acceptance. The results highlight areas where PBPK modeling is used with high confidence and identifies opportunities where confidence is lower and further evaluation is needed. To enhance the survey results, the PBPK-IWG also collected case studies and analyzed recent literature examples where PBPK models were applied to predict CYP3A induction-mediated drug-drug interactions. PBPK modeling of induction has evolved and progressed significantly, proving to have great potential to accelerate drug discovery and development. With the aim of enabling optimal use for new molecular entities that are either substrates and/or inducers of CYP3A, the PBPK-IWG proposes initial workflows for PBPK application, discusses future trends, and identifies gaps that need to be addressed.

Case Study 3: Criticality of High-Quality Curve Fitting-"Getting a Km,app" Isn't as Simple as It May Seem.

In this chapter, we illustrate the criticality of proper fitting of enzyme kinetic data. Simple techniques are provided to arrive at meaningful kinetic parameters, illustrated using an example, nonmonotonic data set. In the initial analysis of this data set, derived Km and Vmax parameters incorporated into PBPK models resulted in outcomes that did not adequately describe clinical data. This prompted a re-review of the in vitro data set and curve-fitting procedures. During this review, it was found that the 3-parameter model was fitted on data that was improperly unweighted. Reanalysis of the data using a weighted model returned a better fit and resulted in kinetic parameters better aligning with clinical data. Tools and techniques used to identify and compare kinetic models of this data set are provided, including various replots, visual inspection, examination of residuals, and the Akaike information criterion.

Use of Physiologically Based Pharmacokinetic Modeling for Predicting Drug-Food Interactions: Recommendations for Improving Predictive Performance of Low Confidence Food Effect Models.

Food can alter drug absorption and impact safety and efficacy. Besides conducting clinical studies, in vitro approaches such as biorelevant solubility and dissolution testing and in vivo dog studies are typical approaches to estimate a drug's food effect. The use of physiologically based pharmacokinetic models has gained importance and is nowadays a standard tool for food effect predictions at preclinical and clinical stages in the pharmaceutical industry. This manuscript is part of a broader publication from the IQ Consortium's food effect physiologically based pharmacokinetic model (PBPK) modeling working group and complements previous publications by focusing on cases where the food effect was predicted with low confidence. Pazopanib-HCl, trospium-Cl, and ziprasidone-HCl served as model compounds to provide insights into why several food effect predictions failed in the first instance. Furthermore, the manuscript depicts approaches whereby PBPK-based food effect predictions may be improved. These improvements should focus on the PBPK model functionality, especially better reflecting fasted- and fed-state gastric solubility, gastric re-acidification, and complex mechanisms related to gastric emptying of drugs. For improvement of in vitro methodologies, the focus should be on the development of more predictive solubility, supersaturation, and precipitation assays. With regards to the general PBPK modeling methodology, modelers should account for the full solubility profile when modeling ionizable compounds, including common ion effects, and apply a straightforward strategy to account for drug precipitation.

Understanding Mechanisms of Food Effect and Developing Reliable PBPK Models Using a Middle-out Approach.

Over the last 10 years, 40% of approved oral drugs exhibited a significant effect of food on their pharmacokinetics (PK) and currently the only method to characterize the effect of food on drug absorption, which is recognized by the authorities, is to conduct a clinical evaluation. Within the pharmaceutical industry, there is a significant effort to predict the mechanism and clinical relevance of a food effect. Physiologically based pharmacokinetic (PBPK) models combining both drug-specific and physiology-specific data have been used to predict the effect of food on absorption and to reveal the underlying mechanisms. This manuscript provides detailed descriptions of how a middle-out modeling approach, combining bottom-up in vitro-based predictions with limited top-down fitting of key model parameters for clinical data, can be successfully used to predict the magnitude and direction of food effect when it is predicted poorly by a bottom-up approach. For nefazodone, a mechanistic clearance for the gut and liver was added, for furosemide, an absorption window was introduced, and for aprepitant, the biorelevant solubility was refined using multiple solubility measurements. In all cases, these adjustments were supported by literature data and showcased a rational approach to assess the factors limiting absorption and exposure.

Physiologically-Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug-Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations.

Physiologically-based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug-drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time-dependent inhibition, enzyme induction, and/or suppression. PBPK modeling has now gained reasonable acceptance with the regulatory authorities for the cytochrome-P450-mediated DDIs and is routinely used. However, the application of PBPK for transporter-mediated DDIs (tDDI) in drug development is relatively uncommon. Because the predictive performance of PBPK models for tDDI is not well established, here, we represent and discuss examples of PBPK analyses included in regulatory submission (the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA)) across various tDDIs. The goal of this collaborative effort (involving scientists representing 17 pharmaceutical companies in the Consortium and from academia) is to reflect on the use of current databases and models to address tDDIs. This challenges the common perceptions on applications of PBPK for tDDIs and further delves into the requirements to improve such PBPK predictions. This review provides a reflection on the current trends in PBPK modeling for tDDIs and provides a framework to promote continuous use, verification, and improvement in industrialization of the transporter PBPK modeling.

Mechanistic Physiologically Based Pharmacokinetic Modeling of the Dissolution and Food Effect of a Biopharmaceutics Classification System IV Compound-The Venetoclax Story.

Venetoclax, a selective B-cell lymphoma-2 inhibitor, is a biopharmaceutics classification system class IV compound. The aim of this study was to develop a physiologically based pharmacokinetic (PBPK) model to mechanistically describe absorption and disposition of an amorphous solid dispersion formulation of venetoclax in humans. A mechanistic PBPK model was developed incorporating measured amorphous solubility, dissolution, metabolism, and plasma protein binding. A middle-out approach was used to define permeability. Model predictions of oral venetoclax pharmacokinetics were verified against clinical studies of fed and fasted healthy volunteers, and clinical drug interaction studies with strong CYP3A inhibitor (ketoconazole) and inducer (rifampicin). Model verification demonstrated accurate prediction of the observed food effect following a low-fat diet. Ratios of predicted versus observed Cmax and area under the curve of venetoclax were within 0.8- to 1.25-fold of observed ratios for strong CYP3A inhibitor and inducer interactions, indicating that the venetoclax elimination pathway was correctly specified. The verified venetoclax PBPK model is one of the first examples mechanistically capturing absorption, food effect, and exposure of an amorphous solid dispersion formulated compound. This model allows evaluation of untested drug-drug interactions, especially those primarily occurring in the intestine, and paves the way for future modeling of biopharmaceutics classification system IV compounds.

Physiologically Based Pharmacokinetic Model Qualification and Reporting Procedures for Regulatory Submissions: A Consortium Perspective.

This work provides a perspective on the qualification and verification of physiologically based pharmacokinetic (PBPK) platforms/models intended for regulatory submission based on the collective experience of the Simcyp Consortium members. Examples of regulatory submission of PBPK analyses across various intended applications are presented and discussed. European Medicines Agency (EMA) and US Food and Drug Administration (FDA) recent draft guidelines regarding PBPK analyses and reporting are encouraging, and to advance the use and acceptability of PBPK analyses, more clarity and flexibility are warranted.

Metformin and cancer: from the old medicine cabinet to pharmacological pitfalls and prospects.

Metformin is a biguanide derivative used in the treatment of type II diabetes (T2D) and one of the world's most widely prescribed drugs. Owing to its safety profile, it has been recently promoted for a range of other indications, particularly for its role in cancer prevention. There is evidence from studies in diabetic cohorts, as well as laboratory studies, that the action of metformin depends on a balance between the concentration and duration of exposure, which depends crucially on cell- and tissue-specific pharmacological factors. Mechanistic studies have revealed the involvement of increasingly complex pathways. Yet, there are several missing links regarding the role of drug transporters and drug-drug interactions, as well as the expression levels of transporters in normal versus tumor tissues, which may affect patient exposure and dosing when metformin is used in cancer prevention. This review highlights the current knowledge on metformin action and pharmacology, including novel insights into genomic factors, with a specific focus on cancer prevention. Furthermore, future challenges that may influence therapeutic outcome will be discussed.