Mohammed Ullah

Refining the in vitro and in vivo critical parameters for P-glycoprotein, [I]/IC50 and [I2]/IC50, that allow for the exclusion of drug candidates from clinical digoxin interaction studies.

The objective of this work was to further investigate the reasons for disconcordant clinical digoxin drug interactions (DDIs) particularly for false negative where in vitro data suggests no P-glycoprotein (P-gp) related DDI but a clinically relevant DDI is evident. Applying statistical analyses of binary classification and receiver operating characteristic (ROC), revised cutoff values for ratio of [I]/IC(50) < 0.1 and [I(2)]/IC(50) < 5 were identified to minimize the error rate, a reduction of false negative rate to 9% from 36% (based on individual ratios). The steady state total C(max) at highest dose of the inhibitor is defined as [I] and the ratio of the nominal maximal gastrointestinal concentration determined for highest dose per 250 mL volume defined [I(2)](.) We also investigated the reliability of the clinical data to see if recommendations can be made on values that would allow predictions of 25% change in digoxin exposure. The literature derived clinical digoxin interaction studies were statistically powered to detect relevant changes in exposure associated with digitalis toxicities. Our analysis identified that many co-meds administered with digoxin are cardiovascular (CV) agents. Moreover, our investigations also suggest that the presence of CV agents may alter cardiac output and/or kidney function that may act alone or are additional components to enhance digoxin exposure along with P-gp interaction. While we recommend digoxin as the probe substrate to define P-gp inhibitory potency for clinical assessment, we observed high concordance in P-gp inhibitory potency for calcein AM as a probe substrate.

In Vitro Characterization of Axitinib Interactions with Human Efflux and Hepatic Uptake Transporters. Implications for Disposition and Drug Interactions.

Axitinib is an inhibitor of tyrosine kinase vascular endothelin growth factor receptors 1, 2, and 3. The ATP-binding cassette (ABC) and solute carrier (SLC) transport properties of axitinib were determined in selected cellular systems. Axitinib exhibited high passive permeability in all cell lines evaluated (Papp ≥ 6 × 10−6 cm/s). Active efflux was observed in Caco-2 cells, and further evaluation in multidrug resistance gene 1 (MDR1) or breast cancer resistance protein (BCRP) transfected Madin-Darby canine kidney cells type 2 (MDCK) cells indicated that axitinib is at most only a weak substrate for P-glycoprotein (P-gp) but not BCRP. Axitinib showed incomplete inhibition of P-gp-mediated transport of digoxin in Caco-2 cells and BCRP transport of topotecan in BCRP-transfected MDCK cells with IC50 values of 3 μM and 4.4 μM, respectively. Axitinib (10 mg) did not pose a risk for systemic drug interactions with P-gp or BCRP per regulatory guidance. A potential risk for drug interactions through inhibition of P-gp and BCRP in the gastrointestinal tract was identified because an axitinib dose of 10 mg divided by 250 mL was greater than 10-fold the IC50 for each transporter. However, a GastroPlus simulation that considered the low solubility of axitinib resulted in lower intestinal concentrations and suggested a low potential for gastrointestinal interactions with P-gp and BCRP substrates. Organic anion transporting polypeptide 1B1 (OATP1B1) and OATP1B3 transfected human embryonic kidney 293 (HEK293) cells transported axitinib to a minor extent but uptake into suspended hepatocytes was not inhibited by rifamycin SV suggesting that high passive permeability predominates. Mouse whole-body autoradiography revealed that [14C]axitinib-equivalents showed rapid absorption and distribution to all tissues except the brain. This suggests that efflux transport of axitinib may occur at the mouse blood-brain barrier.

The Need for Human Breast Cancer Resistance Protein Substrate and Inhibition Evaluation in Drug Discovery and Development: Why, When, and How?

Although the multiplicity in transport proteins assessed during drug development is continuously increasing, the clinical relevance of the breast cancer resistance protein (BCRP) is still under debate. Here, our aim is to rationalize the need to consider BCRP substrate and inhibitor interactions and to define optimum selection and acceptance criteria between cell-based and vesicle-based assays in vitro. Information on the preclinical and clinical pharmacokinetics (PK), drug-drug interactions, and pharmacogenomics data was collated for 13 marketed drugs whose PK is reportedly associated with BCRP interaction. Clinical examples where BCRP impacts drug PK and efficacy appear to be rare and confounded by interactions with other transporters. Thirty-seven compounds were selected to be tested as BCRP substrates in a cell-based assay using MDCKII cells (Madin-Darby canine kidney cells) and 18 in membrane vesicles. Depending on the physicochemical compound properties, we observed both in vitro systems to give false-negative readouts. In addition, the inhibition potential of 19 compounds against BCRP was assessed in vesicles and in MDCKII cells, where we observed significant system and substrate-dependent IC50 values. Therefore, neither of the two test systems is superior to the other. Instead, one system may offer advantages under certain situations (e.g., low permeability) and thus should be selected based on the physicochemical compound properties. Finally, given the clinical relevance of BCRP, we propose that its evaluation should remain issue-driven: for low permeable, low bioavailable drugs, in particular when other more common processes do not allow a mechanistic understanding of any unexpected absorption or brain disposition, and for drugs with a low therapeutic window.

Calibration of in vitro multidrug resistance protein 1 substrate and inhibition assays as a basis to support the prediction of clinically relevant interactions in vivo.

The multidrug resistance protein 1 (MDR1) is known to limit brain penetration of drugs and play a key role in drug-drug interactions (DDIs). Theoretical cut-offs from regulatory guidelines are used to extrapolate MDR1 interactions from in vitro to in vivo. However, these cut-offs do not account for interlaboratory variability. Our aim was to calibrate our experimental system to allow better in vivo predictions. We selected 166 central nervous system (CNS) and non-CNS drugs to calibrate the MDR1 transport screening assay using Lewis lung cancer porcine kidney 1 epithelial cells overexpressing MDR1 (L-MDR1). A threshold efflux ratio (ER) of 2 was established as one parameter to assess brain penetration in lead optimization. The inhibitory potential of 57 molecules was evaluated using IC50 values based on the digoxin ER—IC50(ER)—or apparent permeability—IC50(Papp)—in L-MDR1 cells. Published clinical data for 68 DDIs involving digoxin as the victim drug were collected. DDI risk assessments were based on intestinal concentrations ([I2]) as well as unbound [I1u] and total plasma [I1T] concentrations. A receiver operating characteristic analysis identified an [I2]/IC50(ER) of 6.5 as the best predictor of a potential interaction with digoxin in patients. The model was further evaluated with a test set of 11 digoxin DDIs and 16 nondigoxin DDIs, resulting in only one false negative for each test set, no false positives among the digoxin DDIs, and two among the nondigoxin DDIs. Future refinements might include using cerebrospinal fluid to unbound plasma concentration ratios rather than therapeutic class, better estimation of [I2], and dynamic modeling of MDR1-mediated DDIs.

Successful prediction of in vivo hepatobiliary clearances and hepatic concentrations of rosuvastatin using sandwich-cultured rat hepatocytes, transporter-expressing cell lines, and quantitative proteomics

We determined whether in vivo transporter-mediated hepatobiliary clearance (CL) and hepatic concentrations of rosuvastatin (RSV) in the rat could be predicted by transport activity in sandwich-cultured rat hepatocytes (SCRHs) and/or transporter-expressing cell lines scaled by differences in transporter protein expression between SCRHs, cell lines, and rat liver. The predicted hepatobiliary CLs and hepatic concentrations of RSV were compared with our previously published positron emission tomography imaging data. Sinusoidal uptake CL () and efflux (canalicular and sinusoidal) CLs of [3H]-RSV in SCRHs were evaluated in the presence and absence of Ca2+ and in the absence and presence of 1 mM unlabeled RSV (to estimate passive diffusion CL). of RSV into cells expressing organic anion transporting polypeptide (Oatp) 1a1, 1a4, and 1b2 was also determined. Protein expression of Oatps in SCRHs and Oatp-expressing cells was quantified by liquid chromatography tandem mass spectrometry. SCRHs well predicted the in vivo RSV sinusoidal and canalicular efflux CLs but significantly underestimated in vivo . Oatp expression in SCRHs was significantly lower than that in the rat liver. , based on RSV into Oatp-expressing cells (active transport) plus passive diffusion CL in SCRHs, scaled by the difference in protein expression in Oatp cells versus SCRH versus rat liver, was within 2-fold of that observed in SCRHs or in vivo. In vivo hepatic RSV concentrations were well predicted by Oatp-expressing cells after correcting for Oatp protein expression. This is the first demonstration of the successful prediction of in vivo hepatobiliary CLs and hepatic concentrations of RSV using transporter-expressing cells and SCRHs.

Simultaneous Assessment of Clearance, Metabolism, Induction and Drug-Drug Interaction Potential using a Long-Term In Vitro Liver Model for a Novel Hepatitis B Virus Inhibitor

Long-term in vitro liver models are now widely explored for human hepatic metabolic clearance prediction, enzyme phenotyping, cross-species metabolism, comparison of low clearance drugs, and induction studies. Here, we present studies using a long-term liver model, which show how metabolism and active transport, drug-drug interactions, and enzyme induction in healthy and diseased states, such as hepatitis B virus (HBV) infection, may be assessed in a single test system to enable effective data integration for physiologically based pharmacokinetic (PBPK) modeling. The approach is exemplified in the case of (3S)-4-[[(4R)-4-(2-Chloro-4-fluorophenyl)-5-methoxycarbonyl-2-thiazol-2-yl-1,4-dihydropyrimidin-6-yl]methyl]morpholine-3-carboxylic acid RO6889678, a novel inhibitor of HBV with a complex absorption, distribution, metabolism, and excretion (ADME) profile. RO6889678 showed an intracellular enrichment of 78-fold in hepatocytes, with an apparent intrinsic clearance of 5.2 µl/min per mg protein and uptake and biliary clearances of 2.6 and 1.6 µl/min per mg protein, respectively. When apparent intrinsic clearance was incorporated into a PBPK model, the simulated oral human profiles were in good agreement with observed data at low doses but were underestimated at high doses due to unexpected overproportional increases in exposure with dose. In addition, the induction potential of RO6889678 on cytochrome P450 (P450) enzymes and transporters at steady state was assessed and cotreatment with ritonavir revealed a complex drug-drug interaction with concurrent P450 inhibition and moderate UDP-glucuronosyltransferase induction. Furthermore, we report on the first evaluation of in vitro pharmacokinetics studies using HBV-infected HepatoPac cocultures. Thus, long-term liver models have great potential as translational research tools exploring pharmacokinetics of novel drugs in vitro in health and disease.

Transport Kinetics, Selective Inhibition, and Successful Prediction of In Vivo Inhibition of Rat Hepatic Organic Anion Transporting Polypeptides

For successful in vitro-to-in vivo extrapolation of hepatic drug uptake and drug-drug interactions (DDI), it is important to characterize the kinetic properties of the individual transporters involved, their fraction (ft) contribution to hepatic uptake, and their selective inhibitors. Here, we characterized the in vitro transport kinetics of two model drugs, rosuvastatin (RSV) and olmesartan acid (OLM), by rat hepatic organic anion transporting polypeptides (Oatp1a1, 1a4, and 1b2) and identified selective inhibitors of these transporters. [3H]-RSV was transported by Oatp1a1, 1a4, and 1b2, and their Michaelis-Menten constant (Km) values were estimated to be 9.61, 67.2, and 28.1 µM, respectively. In contrast, [3H]-OLM was transported by only Oatp1b2 (Km: 72.8 µM). Digoxin (IC50: 0.107 µM) and rifamycin SV (IC50: 0.140 and 0.088 µM for RSV and OLM, respectively) were potent and selective inhibitors of Oatp1a4 and 1b2, respectively, and glyburide (100 µM) completely inhibited all three rat hepatic Oatps. These inhibitors can therefore be used alone and in combination to determine the contribution of each Oatp to hepatic influx. In addition, the magnitude of in vivo inhibition of sinusoidal uptake clearance of RSV by rifampin was well predicted using rifampin IC50 profiles for each Oatps and RSV ft by each Oatp. This is the first report to 1) detail the transport kinetics of RSV and OLM by rat hepatic Oatps, 2) identify selective inhibitor concentrations of rat Oatps, and 3) demonstrate successful prediction of the magnitude of transporter-mediated in vivo DDI from IC50 profiles of an inhibitor and ft of a drug by each transporter.

Toward in vitro-to-in vivo translation of monoclonal antibody pharmacokinetics: Application of a neonatal Fc receptor-mediated transcytosis assay to understand the interplaying clearance mechanisms

ABSTRACT Monoclonal antibodies (mAbs) are a rapidly growing drug class for which great efforts have been made to optimize certain molecular features to achieve the desired pharmacokinetic (PK) properties. One approach is to engineer the interactions of the mAb with the neonatal Fc receptor (FcRn) by introducing specific amino acid sequence mutations, and to assess their effect on the PK profile with in vivo studies. Indeed, FcRn protects mAbs from intracellular degradation, thereby prolongs antibody circulation time in plasma and modulates its systemic clearance. To allow more efficient and focused mAb optimization, in vitro input that helps to identify and quantitatively predict the contribution of different processes driving non-target mediated mAb clearance in vivo and supporting translational PK modeling activities is essential. With this aim, we evaluated the applicability and in vivo-relevance of an in vitro cellular FcRn-mediated transcytosis assay to explain the PK behavior of 25 mAbs in rat or monkey. The assay was able to capture species-specific differences in IgG-FcRn interactions and overall correctly ranked Fc mutants according to their in vivo clearance. However, it could not explain the PK behavior of all tested IgGs, indicating that mAb disposition in vivo is a complex interplay of additional processes besides the FcRn interaction. Overall, the transcytosis assay was considered suitable to rank mAb candidates for their FcRn-mediated clearance component before extensive in vivo testing, and represents a first step toward a multi-factorial in vivo clearance prediction approach based on in vitro data.

Chapter 10:Transporter Drug–Drug Interactions: A Pharmaceutical Industry Perspective

Over the last few decades, active drug transporters have gained increasing attention in basic and applied research, since they can substantially modulate drug absorption, distribution, metabolism and excretion (ADME) routes, interact with co-medications and endogenous products, and thereby strongly impact drug efficacy and safety profiles. Therefore, these interactions between substrates and inhibitors need to be assessed during drug development and are part of every new entitys pharmacokinetic (PK) and safety package. This chapter provides a general overview of the most important drug–drug interaction (DDI) aspects from a pharmaceutical industry perspective. Clinically relevant DDIs at the various barrier tissues are described via a comprehensive DDI table, listing substrate–inhibitor pairs with the respective PK/pharmacodynamic (PD) effects and their implicated therapeutic consequences. Transporter DDI assessment during the early and late drug development stages is discussed, followed by insights into a clinical strategy paradigm to address this issue in humans. Both sections emphasize the importance of adjusting a transporter DDI strategy individually to the characteristics of the compound and the project, and the difficulty of interpreting the obtained data correctly. Two prominent transporter DDI examples are discussed as case studies: digoxin and the cholesterol-reducing statins. The chapter concludes by outlining the current gaps and future challenges in this emerging field.

Response to “Breast Cancer Resistance Protein Substrate and Inhibition Evaluation: Why, When, and How?”

We thank you for the opportunity to respond to the comments made by [Ware et al. (2014)][1] on our recently published article “The Need for Human Breast Cancer Resistance Protein Substrate and Inhibition Evaluation in Drug Discovery and Development: Why, When, and How?” ([Poirier et al., 2014][2