Drug transporters in drug disposition - the year 2022 in review.

On behalf of all the authors, I am pleased to share our third annual review on drug transporter science with an emphasis on articles published and deemed influential in signifying drug transporters' role in drug disposition in the year 2022. As the drug transporter field is rapidly evolving several key findings were noted including promising endogenous biomarkers, rhythmic activity, IVIVE approaches in transporter-mediated clearance, new modality interaction, and transporter effect on gut microbiome. As identified previously (Chothe et Cal. 2021, 2022) the goal of this review is to highlight key findings without a comprehensive overview of each article and to this end, each coauthor independently selected 1-3 peer-reviewed articles published or available online in the year 2022 (Table 1). Each article is summarized in synopsis and commentary with unbiased viewpoints by each coauthor. We strongly encourage readers to consult original articles for specifics of the study. Finally, I would like to thank all coauthors for their continued support in writing this annual review on drug transporters and invite anyone interested in contributing to future versions of this review.

Current Approaches for Predicting Human PK for Small Molecule Development Candidates: Findings from the IQ Human PK Prediction Working Group Survey.

Accurate prediction of human clearance (CL) and volume of distribution at steady state (Vd,ss) for small molecule drug candidates is an essential component of assessing likely efficacious dose and clinical safety margins. In 2021, the IQ Consortium Human PK Prediction Working Group undertook a survey of IQ member companies to understand the current PK prediction methods being used to estimate these parameters across the pharmaceutical industry. The survey revealed a heterogeneity in approaches being used across the industry (e.g., the use of allometric approaches, differing incorporation of binding terms, and inconsistent use of empirical correction factors for in vitro-in vivo extrapolation, IVIVE), which could lead to different PK predictions with the same input data. Member companies expressed an interest in improving human PK predictions by identifying the most appropriate compound-class specific methods, as determined by physiochemical properties and knowledge of CL pathways. Furthermore, there was consensus that increased understanding of the uncertainty inherent to the compound class-dependent prediction would be invaluable in aiding communication of human PK and dose uncertainty at the time of candidate nomination for development. The human PK Prediction Working Group is utilizing these survey findings to help interrogate clinical IV datasets from across the IQ consortium member companies to understand PK prediction accuracy and uncertainty from preclinical datasets.

Novel insights in drug transporter sciences: the year 2021 in review.

On behalf of the team I am pleased to present the second annual 'novel insights into drug transporter sciences review' focused on peer-reviewed articles that were published in the year 2021. In compiling the articles for inclusion, preprints available in 2021 but officially published in 2022 were considered to be in scope. To support this review the contributing authors independently selected one or two articles that were thought to be impactful and of interest to the broader research community. A similar approach as published last year was adopted whereby key observations, methods and analysis of each paper is concisely summarized in the synopsis followed by a commentary highlighting the impact of the paper in understanding drug transporters' role in drug disposition. As the goal of this review is not to provide a comprehensive overview of each paper but rather highlight important findings that are well supported by the data, the reader is encouraged to consult the original articles for additional information. Further, and keeping in line with the goals of this review, it should be noted that all authors actively contributed by writing synopsis and commentary for individual papers and no attempt was made to standardize language or writing styles. In this way, the review article is reflective of not only the diversity of the articles but also that of the contributors. I extend my thanks to the authors for their continued support and also welcome Diane Ramsden and Pallabi Mitra as contributing authors for this issue (Table 1).[Table: see text].

Recent advances in drug transporter sciences: highlights from the year 2020.

Drug Metabolism Reviews has an impressive track record of providing scientific reviews in the area of xenobiotic biotransformation over 47 years. It has consistently proved to be resourceful to many scientists from pharmaceutical industry, academia, regulatory agencies working in diverse areas including enzymology, pharmacology, pharmacokinetics, and toxicology. Over the last 5 years Drug metabolism Reviews has annually published an industry commentary aimed to highlight novel insights and approaches that have made significant impacts on the field of biotransformation (led by Cyrus Khojasteh). We hope to continue this tradition by providing an overview of advances made in the field of drug transporters during 2020. The field of drug transporters is rapidly evolving as they play an essential role in drug absorption, distribution, clearance, and elimination. In this review, we have selected outstanding drug transporter articles that have significantly contributed to moving forward the field of transporter science with respect to translation and improved understanding of diverse aspects including uptake clearance, clinical biomarkers, induction, proteomics, emerging transporters, and tissue targeting. The theme of this review consists of a synopsis that summarizes each article followed by our commentary. The objective of this work is not to provide a comprehensive review but rather to exemplify novel insights and state-of-the-art highlights of recent research that have advanced our understanding of drug transporters in drug disposition. We are hopeful that this effort will prove useful to the scientific community and as such request feedback, and further extend an invitation to anyone interested in contributing to future reviews.

IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 3: Identifying gaps in system parameters by analysing In Silico performance across different compound classes.

Three Physiologically Based Pharmacokinetic software packages (GI-Sim, Simcyp® Simulator, and GastroPlus™) were evaluated as part of the Innovative Medicine Initiative Oral Biopharmaceutics Tools project (OrBiTo) during a blinded "bottom-up" anticipation of human pharmacokinetics. After data analysis of the predicted vs. measured pharmacokinetics parameters, it was found that oral bioavailability (Foral) was underpredicted for compounds with low permeability, suggesting improper estimates of intestinal surface area, colonic absorption and/or lack of intestinal transporter information. Foral was also underpredicted for acidic compounds, suggesting overestimation of impact of ionisation on permeation, lack of information on intestinal transporters, or underestimation of solubilisation of weak acids due to less than optimal intestinal model pH settings or underestimation of bile micelle contribution. Foral was overpredicted for weak bases, suggesting inadequate models for precipitation or lack of in vitro precipitation information to build informed models. Relative bioavailability was underpredicted for both high logP compounds as well as poorly water-soluble compounds, suggesting inadequate models for solubility/dissolution, underperforming bile enhancement models and/or lack of biorelevant solubility measurements. These results indicate areas for improvement in model software, modelling approaches, and generation of applicable input data. However, caution is required when interpreting the impact of drug-specific properties in this exercise, as the availability of input parameters was heterogeneous and highly variable, and the modellers generally used the data "as is" in this blinded bottom-up prediction approach.

IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 2: An introduction to the simulation exercise and overview of results.

Orally administered drugs are subject to a number of barriers impacting bioavailability (Foral), causing challenges during drug and formulation development. Physiologically-based pharmacokinetic (PBPK) modelling can help during drug and formulation development by providing quantitative predictions through a systems approach. The performance of three available PBPK software packages (GI-Sim, Simcyp®, and GastroPlus™) were evaluated by comparing simulated and observed pharmacokinetic (PK) parameters. Since the availability of input parameters was heterogeneous and highly variable, caution is required when interpreting the results of this exercise. Additionally, this prospective simulation exercise may not be representative of prospective modelling in industry, as API information was limited to sparse details. 43 active pharmaceutical ingredients (APIs) from the OrBiTo database were selected for the exercise. Over 4000 simulation output files were generated, representing over 2550 study arm-institution-software combinations and approximately 600 human clinical study arms simulated with overlap. 84% of the simulated study arms represented administration of immediate release formulations, 11% prolonged or delayed release, and 5% intravenous (i.v.). Higher percentages of i.v. predicted area under the curve (AUC) were within two-fold of observed (52.9%) compared to per oral (p.o.) (37.2%), however, Foral and relative AUC (Frel) between p.o. formulations and solutions were generally well predicted (64.7% and 75.0%). Predictive performance declined progressing from i.v. to solution and immediate release tablet, indicating the compounding error with each layer of complexity. Overall performance was comparable to previous large-scale evaluations. A general overprediction of AUC was observed with average fold error (AFE) of 1.56 over all simulations. AFE ranged from 0.0361 to 64.0 across the 43 APIs, with 25 showing overpredictions. Discrepancies between software packages were observed for a few APIs, the largest being 606, 171, and 81.7-fold differences in AFE between SimCYP and GI-Sim, however average performance was relatively consistent across the three software platforms.

The Antimicrobial Agent Fusidic Acid Inhibits Organic Anion Transporting Polypeptide-Mediated Hepatic Clearance and May Potentiate Statin-Induced Myopathy.

Chronic treatment of methicillin-resistant Staphylococcus aureus strains with the bacteriostatic agent fusidic acid (FA) is frequently associated with myopathy including rhabdomyolysis upon coadministration with statins. Because adverse effects with statins are usually the result of drug-drug interactions, we evaluated the inhibitory effects of FA against human CYP3A4 and clinically relevant drug transporters such as organic anion transporting polypeptides OATP1B1 and OATP1B3, multidrug resistant protein 1, and breast cancer resistance protein, which are involved in the oral absorption and/or systemic clearance of statins including atorvastatin, rosuvastatin, and simvastatin. FA was a weak reversible (IC50= 295 ± 1.0µM) and time-dependent (KI= 216 ± 41µM and kinact= 0.0179 ± 0.001 min(-1)) inhibitor of CYP3A4-catalyzed midazolam-1'-hydroxylase activity in human liver microsomes. FA demonstrated inhibition of multidrug resistant protein 1-mediated digoxin transport with an IC50 value of 157 ± 1.0µM and was devoid of breast cancer resistance protein inhibition (IC50> 500µM). In contrast, FA showed potent inhibition of OATP1B1- and OATP1B3-specific rosuvastatin transport with IC50 values of 1.59µM and 2.47µM, respectively. Furthermore, coadministration of oral rosuvastatin and FA to rats led to an approximately 19.3-fold and 24.6-fold increase in the rosuvastatin maximum plasma concentration and area under the plasma concentration-time curve, respectively, which could be potentially mediated through inhibitory effects of FA on rat Oatp1a4 (IC50= 2.26µM) and Oatp1b2 (IC50= 4.38µM) transporters, which are responsible for rosuvastatin uptake in rat liver. The potent inhibition of human OATP1B1/OATP1B3 by FA could attenuate hepatic uptake of statins, resulting in increased blood and tissue concentrations, potentially manifesting in musculoskeletal toxicity.

Cyclic Penta- and Hexaleucine Peptides without N-Methylation Are Orally Absorbed.

Development of peptide-based drugs has been severely limited by lack of oral bioavailability with less than a handful of peptides being truly orally bioavailable, mainly cyclic peptides with N-methyl amino acids and few hydrogen bond donors. Here we report that cyclic penta- and hexa-leucine peptides, with no N-methylation and five or six amide NH protons, exhibit some degree of oral bioavailability (4-17%) approaching that of the heavily N-methylated drug cyclosporine (22%) under the same conditions. These simple cyclic peptides demonstrate that oral bioavailability is achievable for peptides that fall outside of rule-of-five guidelines without the need for N-methylation or modified amino acids.

Improving on nature: making a cyclic heptapeptide orally bioavailable.

The use of peptides in medicine is limited by low membrane permeability, metabolic instability, high clearance, and negligible oral bioavailability. The prediction of oral bioavailability of drugs relies on physicochemical properties that favor passive permeability and oxidative metabolic stability, but these may not be useful for peptides. Here we investigate effects of heterocyclic constraints, intramolecular hydrogen bonds, and side chains on the oral bioavailability of cyclic heptapeptides. NMR-derived structures, amide H-D exchange rates, and temperature-dependent chemical shifts showed that the combination of rigidification, stronger hydrogen bonds, and solvent shielding by branched side chains enhances the oral bioavailability of cyclic heptapeptides in rats without the need for N-methylation.

Toward a unified model of passive drug permeation II: the physiochemical determinants of unbound tissue distribution with applications to the design of hepatoselective glucokinase activators.

In this work, we leverage a mathematical model of the underlying physiochemical properties of tissues and physicochemical properties of molecules to support the development of hepatoselective glucokinase activators. Passive distribution is modeled via a Fick-Nernst-Planck approach, using in vitro experimental data to estimate the permeability of both ionized and neutral species. The model accounts for pH and electrochemical potential across cellular membranes, ionization according to Henderson-Hasselbalch, passive permeation of the neutral species using Fick's law, and passive permeation of the ionized species using the Nernst-Planck equation. The mathematical model of the physiochemical system allows derivation of a single set of parameters governing the distribution of drug molecules across multiple conditions both in vitro and in vivo. A case study using this approach in the development of hepatoselective glucokinase activators via organic anion-transporting polypeptide-mediated hepatic uptake and impaired passive distribution to the pancreas is described. The results for these molecules indicate the permeability penalty of the ionized form is offset by its relative abundance, leading to passive pancreatic exclusion according to the Nernst-Planck extension of Fickian passive permeation. Generally, this model serves as a useful construct for drug discovery scientists to understand subcellular exposure of acids or bases using specific physiochemical properties.

Mechanism-based pharmacokinetic modeling to evaluate transporter-enzyme interplay in drug interactions and pharmacogenetics of glyburide.

The purpose of this study is to characterize the involvement of hepato-biliary transport and cytochrome-P450 (CYP)-mediated metabolism in the disposition of glyburide and predict its pharmacokinetic variability due to drug interactions and genetic variations. Comprehensive in vitro studies suggested that glyburide is a highly permeable drug with substrate affinity to multiple efflux pumps and to organic anion transporting polypeptide (OATP)1B1 and OATP2B1. Active hepatic uptake was found to be significantly higher than the passive uptake clearance (15.8 versus 5.3 µL/min/10(6)-hepatocytes), using the sandwich-cultured hepatocyte model. In vitro, glyburide is metabolized (intrinsic clearance, 52.9 µL/min/mg-microsomal protein) by CYP3A4, CYP2C9, and CYP2C8 with fraction metabolism of 0.53, 0.36, and 0.11, respectively. Using these in vitro data, physiologically based pharmacokinetic models, assuming rapid-equilibrium between blood and liver compartments or permeability-limited hepatic disposition, were built to describe pharmacokinetics and evaluate drug interactions. Permeability-limited model successfully predicted glyburide interactions with rifampicin and other perpetrator drugs. Conversely, model assuming rapid-equilibrium mispredicted glyburide interactions, overall, suggesting hepatic uptake as the primary rate-determining process in the systemic clearance of glyburide. Further modeling and simulations indicated that the impairment of CYP2C9 function has a minimal effect on the systemic exposure, implying discrepancy in the contribution of CYP2C9 to glyburide clearance.

Discovery of an intravenous hepatoselective glucokinase activator for the treatment of inpatient hyperglycemia.

Glucokinase (hexokinase IV) continues to be a compelling target for the treatment of type 2 diabetes given the wealth of supporting human genetics data and numerous reports of robust clinical glucose lowering in patients treated with small molecule allosteric activators. Recent work has demonstrated the ability of hepatoselective activators to deliver glucose lowering efficacy with minimal risk of hypoglycemia. While orally administered agents require a considerable degree of passive permeability to promote suitable exposures, there is no such restriction on intravenously delivered drugs. Therefore, minimization of membrane diffusion in the context of an intravenously agent should ensure optimal hepatic targeting and therapeutic index. This work details the identification a hepatoselective GKA exhibiting the aforementioned properties.

Quantitative assessment of the contribution of sodium-dependent taurocholate co-transporting polypeptide (NTCP) to the hepatic uptake of rosuvastatin, pitavastatin and fluvastatin.

Hepatic uptake transport is often the rate-determining step in the systemic clearance of drugs. The ability to predict uptake clearance and to determine the contribution of individual transporters to overall hepatic uptake is therefore critical in assessing the potential pharmacokinetic and pharmacodynamic variability associated with drug-drug interactions and pharmacogenetics. The present study revisited the interaction of statin drugs, including pitavastatin, fluvastatin and rosuvastatin, with the sodium-dependent taurocholate co-transporting polypeptide (NTCP) using gene transfected cell models. In addition, the uptake clearance and the contribution of NTCP to the overall hepatic uptake were assessed using in vitro hepatocyte models. Then NTCP protein expression was measured by a targeted proteomics transporter quantification method to confirm the presence and stability of NTCP expression in suspended and cultured hepatocyte models. It was concluded that NTCP-mediated uptake contributed significantly to active hepatic uptake in hepatocyte models for all three statins. However, the contribution of NTCP-mediated uptake to the overall active hepatic uptake was compound-dependent and varied from about 24% to 45%. Understanding the contribution of individual transporter proteins to the overall hepatic uptake and its functional variability when other active hepatic uptake pathways are interrupted could improve the current prediction practice used to assess the pharmacokinetic variability due to drug-drug interactions, pharmacogenetics and physiopathological conditions in humans.

Quantitative prediction of renal transporter-mediated clinical drug-drug interactions.

Kidney plays a critical role in the elimination of xenobiotics. Drug-drug interactions (DDIs) via inhibition of renal organic anion (OAT) and organic cation (OCT) transporters have been observed in the clinic. This study examined the quantitative predictability of renal transporter-mediated clinical DDIs based on basic and mechanistic models. In vitro transport and clinical pharmacokinetics parameters were used to quantitatively predict DDIs of victim drugs when coadministrated with OAT or OCT inhibitors, probenecid and cimetidine, respectively. The predicted changes in renal clearance (CLr) and area under the plasma concentration-time curve (AUC) were comparable to that observed in clinical studies. With probenecid, basic modeling predicted 61% cases within 25% and 94% cases within 50% of the observed CLr changes in clinic. With cimetidine, basic modeling predicted 61% cases within 25% and 92% cases within 50% of the observed CLr changes in clinic. Additionally, the mechanistic model predicted 54% cases within 25% and 92% cases within 50% of the observed AUC changes with probenecid. Notably, the magnitude of AUC changes attributable to the renal DDIs is generally less than 2-fold, unlike the DDIs associated with inhibition of CYPs and/or hepatic uptake transporters. The models were further used to evaluate the renal DDIs of Pfizer clinical candidates/drugs, and the overall predictability demonstrates their utility in the drug discovery and development settings.

Elucidation of the biochemical basis for a clinical drug-drug interaction between atorvastatin and 5-(N-(4-((4-ethylbenzyl)thio)phenyl)sulfamoyl)-2-methyl benzoic acid (CP-778875), a subtype selective agonist of the peroxisome proliferator-activated receptor alpha.

1. 5-(N-(4-((4-ethylbenzyl)thio)phenyl)sulfamoyl)-2-methyl benzoic acid (CP-778875), an agonist of the peroxisome proliferator-activated receptor alpha, has been evaluated in the clinic to treat dyslipidemia and type 2 diabetes mellitus. Herein, we investigate the effect of CP-778875 on the pharmacokinetics of atorvastatin acid and its metabolites in humans. 2. The study incorporated a fixed-sequence design conducted in two groups. Group A was designed to estimate the effects of multiple doses of CP-778875 on the single dose pharmacokinetics of atorvastatin. Subjects in group A (n = 26) received atorvastatin (40 mg) on days 1 and 9 and CP-778875 (1.0 mg QD) on days 5-12. Group B was designed to examine the effects of multiple doses of atorvastatin on the single dose pharmacokinetics of CP-778875. Subjects in group B (n = 29) received CP-778875 (0.3 mg) on days 1 and 9 and atorvastatin (40 mg QD) on days 5-12. 3. Mean maximum serum concentration (Cmax) and area under the curve of atorvastatin were increased by 45% and 20%, respectively, upon co-administration with CP-778875. Statistically significant increases in the systemic exposure of ortho- and para-hydroxyatorvastatin were also observed upon concomitant dosing with CP-778875. CP-778875 pharmacokinetics, however, were not impacted upon concomitant dosing with atorvastatin. 4. Inhibition of organic anion transporting polypeptide 1B1 by CP-778875 (IC50 = 2.14 ± 0.40 µM) could be the dominant cause of the pharmacokinetic interaction as CP-778875 did not exhibit significant inhibition of cytochrome P450 3A4/3A5, multidrug resistant protein 1 or breast cancer resistant protein, which are also involved in the hepatobiliary disposition of atorvastatin.

Development and evaluation of novel solid nanodispersion system for oral delivery of poorly water-soluble drugs.

The aim of the present study was to develop and evaluate a novel drug solubilization platform (so-called solid nanodispersion) prepared by a simple co-grinding and solvent-free process. Using structurally diverse model compounds from the Pfizer drug library, including ingliforib, furosemide and celecoxib, we successfully prepared stable solid nanodispersions (SNDs) without the use of solvent or heat. Stable colloidal particles (<350 nm) containing drug, polyvinylpyrrolidone (PVP) K12 and sodium dodecyl sulfate (SDS) in 1:2.75:0.25 ratio were produced after 2 h of co-grinding. The composition and particle size of SNDs were optimized by varying the grinding media size, powder-to-grinding media ratio, milling speed and milling time. The resulting formulations contained crystalline drug and were stable at room temperature for over one month. Greater than 80% of the drug was released from the SND in less than 30 min, with sustained supersaturation over 4 h. Using furosemide (BCS class IV compound) as a model compound, we conducted transport studies with Madin-Darby canine kidney cells transfected with human MDR1 gene (MDCK/MDR1), followed by pharmacokinetics studies in rats. Results showed that the SND formulation enhanced the absorptive flux of furosemide by more than 3-fold. In the pharmacokinetics studies, the SND formulation increased C(max) and AUC of furosemide by 36.6 and 43.2 fold respectively, relative to Methocel formulation. Interestingly, physical mixture containing furosemide, PVP K12 and SDS produced a similar level of oral exposure as the SNDs, albeit with a longer T(max) than the SND formulation. The results suggest that PVP K12 and SDS were able to increase the furosemide free fraction available for oral absorption. Low solubility, poor permeability, and high first-pass effect of furosemide may also have produced the effect that small improvements in solubilization resulted in significant potentiation of the oral exposure of the physical mixture. However the use of a physical mixture of drug, polymer and surfactant, to increase drug bioavailability cannot be generalized to all drugs. There are only a few reported cases of such phenomenon. While SNDs may not be the only option to solubilize compounds in every case, SNDs are expected to be applicable to a broader chemical space of pharmaceutical compounds compared to a physical mixture. Ultimately, the formulation scientist will have to exercise judgment in choosing the appropriate formulation strategy for the compound of interest. SNDs represent a significant improvement over current enabling technologies such as nanocrystal and spray-dried dispersion technologies, in that SNDs are simple, do not require solvent or heat, are applicable to a structurally diverse chemical space, and are readily amenable to the development of solid dosage forms.

High specificity in response of the sodium-dependent multivitamin transporter to derivatives of pantothenic acid.

Essential nutrients are attractive targets for the transport of biologically active agents across cell membranes, since many are substrates for active cellular importation pathways. The sodium-dependent multivitamin transporter (SMVT) is among the best characterized of these, and biotin derivatives have been its most popular targets. We have surveyed 45 derivatives of pantothenic acid, another substrate of SMVT, long known as a competitive inhibitor of biotin transport. Variations of the ß-alanyl fragment of pantothenate were uniformly rejected by the transporter, including derivatives with very similar steric and acidic characteristics to the natural substrate. The secondary hydroxyl of the 2,2-dimethyl-1,3-propanediol (pantoyl) fragment was the only position at which potential linkers could be attached while retaining activity as an inhibitor of biotin uptake and a substrate for sodium-dependent transport. However, triazole conjugates to several drug-like cargo motifs were not accepted as substrates by human SMVT in cell culture. Two compounds were observed which did not inhibit biotin uptake but were themselves transported in a sodium-dependent fashion, suggesting more complex behavior than expected. These studies represent the most extensive examination to date of pantothenate as an anchor for SMVT-mediated drug delivery, showing that this route requires further investigation before being judged promising.

Quantitative prediction of repaglinide-rifampicin complex drug interactions using dynamic and static mechanistic models: delineating differential CYP3A4 induction and OATP1B1 inhibition potential of rifampicin.

Repaglinide is mainly metabolized by cytochrome P450 enzymes CYP2C8 and CYP3A4, and it is also a substrate to a hepatic uptake transporter, organic anion transporting polypeptide (OATP)1B1. The purpose of this study is to predict the dosing time-dependent pharmacokinetic interactions of repaglinide with rifampicin, using mechanistic models. In vitro hepatic transport of repaglinide, characterized using sandwich-cultured human hepatocytes, and intrinsic metabolic parameters were used to build a dynamic whole-body physiologically-based pharmacokinetic (PBPK) model. The PBPK model adequately described repaglinide plasma concentration-time profiles and successfully predicted area under the plasma concentration-time curve ratios of repaglinide (within ± 25% error), dosed (staggered 0-24 hours) after rifampicin treatment when primarily considering induction of CYP3A4 and reversible inhibition of OATP1B1 by rifampicin. Further, a static mechanistic "extended net-effect" model incorporating transport and metabolic disposition parameters of repaglinide and interaction potency of rifampicin was devised. Predictions based on the static model are similar to those observed in the clinic (average error ∼19%) and to those based on the PBPK model. Both the models suggested that the combined effect of increased gut extraction and decreased hepatic uptake caused minimal repaglinide systemic exposure change when repaglinide is dosed simultaneously or 1 hour after the rifampicin dose. On the other hand, isolated induction effect as a result of temporal separation of the two drugs translated to an approximate 5-fold reduction in repaglinide systemic exposure. In conclusion, both dynamic and static mechanistic models are instrumental in delineating the quantitative contribution of transport and metabolism in the dosing time-dependent repaglinide-rifampicin interactions.

Optimizing PK properties of cyclic peptides: the effect of side chain substitutions on permeability and clearance().

A series of cyclic peptides were designed and prepared to investigate the physicochemical properties that affect oral bioavailabilty of this chemotype in rats. In particular, the ionization state of the peptide was examined by the incorporation of naturally occurring amino acid residues that are charged in differing regions of the gut. In addition, data was generated in a variety of in vitro assays and the usefulness of this data in predicting the subsequent oral bioavailability observed in the rat is discussed.

pH-Dependent solubility and permeability criteria for provisional biopharmaceutics classification (BCS and BDDCS) in early drug discovery.

The Biopharmaceutics Classification System (BCS) is a scientific framework that provides a basis for predicting the oral absorption of drugs. These concepts have been extended in the Biopharmaceutics Drug Disposition Classification System (BDDCS) to explain the potential mechanism of drug clearance and understand the effects of uptake and efflux transporters on absorption, distribution, metabolism, and elimination. The objective of present work is to establish criteria for provisional biopharmaceutics classification using pH-dependent passive permeability and aqueous solubility data generated from high throughput screening methodologies in drug discovery settings. The apparent permeability across monolayers of clonal cell line of Madin-Darby canine kidney cells, selected for low endogenous efflux transporter expression, was measured for a set of 105 drugs, with known BCS and BDDCS class. The permeability at apical pH 6.5 for acidic drugs and at pH 7.4 for nonacidic drugs showed a good correlation with the fraction absorbed in human (Fa). Receiver operating characteristic (ROC) curve analysis was utilized to define the permeability class boundary. At permeability ≥ 5 × 10(-6) cm/s, the accuracy of predicting Fa of ≥ 0.90 was 87%. Also, this cutoff showed more than 80% sensitivity and specificity in predicting the literature permeability classes (BCS), and the metabolism classes (BDDCS). The equilibrium solubility of a subset of 49 drugs was measured in pH 1.2 medium, pH 6.5 phosphate buffer, and in FaSSIF medium (pH 6.5). Although dose was not considered, good concordance of the measured solubility with BCS and BDDCS solubility class was achieved, when solubility at pH 1.2 was used for acidic compounds and FaSSIF solubility was used for basic, neutral, and zwitterionic compounds. Using a cutoff of 200 µg/mL, the data set suggested a 93% sensitivity and 86% specificity in predicting both the BCS and BDDCS solubility classes. In conclusion, this study identified pH-dependent permeability and solubility criteria that can be used to assign provisional biopharmaceutics class at early stage of the drug discovery process. Additionally, such a classification system will enable discovery scientists to assess the potential limiting factors to oral absorption, as well as help predict the drug disposition mechanisms and potential drug-drug interactions.