In Vitro–In Vivo Extrapolation of Metabolism- and Transporter-Mediated Drug–Drug Interactions—Overview of Basic Prediction Methods

Evaluation of the Clinical Drug-Drug Interaction Potential of Pritelivir on Transporters and CYP450 Enzymes Using a Cocktail Approach

Pritelivir is a novel viral helicase-primase inhibitor active against herpes simplex virus. In vitro drug-drug interaction studies indicated that pritelivir has the potential for clinically relevant interactions on the cytochrome P450 (CYP) enzymes 2C8, 2C9, 3A4, and 2B6, and intestinal uptake transporter organic anion transporting polypeptide (OATP) 2B1 and efflux transporter breast cancer resistance protein (BCRP). This was evaluated in 2 clinical trials. In 1 trial the substrates flurbiprofen (CYP2C9), bupropion (CYP2B6), and midazolam (CYP3A4) were administered simultaneously as part of the Geneva cocktail, while the substrate celiprolol (OAPT2B1) was administered separately. In another trial, the substrates repaglinide (CYP2C8) and rosuvastatin (BCRP) were administered separately. Exposure parameters of the substrates and their metabolites (flurbiprofen and bupropion only) were compared after administration with or without pritelivir under therapeutic concentrations. The results of these trials indicated that pritelivir has no clinically relevant effect on the exposure of substrates for the intestinal uptake transporter OATP2B1 and the CYP enzymes 3A4, 2B6, 2C9, and 2C8, and has a weak inhibitory effect on the intestinal efflux transporter BCRP. In summary, the results suggest that pritelivir has a low drug-drug interaction potential.

Utilising Endogenous Biomarkers in Drug Development to Streamline the Assessment of Drug-Drug Interactions Mediated by Renal Transporters: A Pharmaceutical Industry Perspective

The renal secretion of many drugs is facilitated by membrane transporters, including organic cation transporter 2, multidrug and toxin extrusion protein 1/2-K and organic anion transporters 1 and 3. Inhibition of these transporters can reduce renal excretion of drugs and thereby pose a safety risk. Assessing the risk of inhibition of these membrane transporters by investigational drugs remains a key focus in the evaluation of drug-drug interactions (DDIs). Current methods to predict DDI risk are based on generating in vitro data followed by a clinical assessment using a recommended exogenous probe substrate for the individual drug transporter. More recently, monitoring plasma-based and urine-based endogenous biomarkers to predict transporter-mediated DDIs in early phase I studies represents a promising approach to facilitate, improve and potentially avoid conventional clinical DDI studies. This perspective reviews the evidence for use of these endogenous biomarkers in the assessment of renal transporter-mediated DDI, evaluates how endogenous biomarkers may help to expand the DDI assessment toolkit and offers some potential knowledge gaps. A conceptual framework for assessment that may complement the current paradigm of predicting the potential for renal transporter-mediated DDIs is outlined.

A genetic algorithm-based approach for the prediction of metabolic drug-drug interactions involving CYP2C8 or CYP2B6

BACKGROUND AND OBJECTIVES

A genetic algorithm (GA) approach was developed to predict drug-drug interactions (DDIs) caused by cytochrome P450 2C8 (CYP2C8) inhibition or cytochrome P450 2B6 (CYP2B6) inhibition or induction. Nighty-eight DDIs, obtained from published in vivo studies in healthy volunteers, have been considered using the area under the plasma drug concentration-time curve (AUC) ratios (i.e., ratios of AUC of the drug substrate administered in combination with a DDI perpetrator to AUC of the drug substrate administered alone) to describe the extent of DDI.

METHODS

The following parameters were estimated in this approach: the contribution ratios (CRCYP2B6 and CRCYP2C8, i.e., the fraction of the dose metabolized via CYP2B6 or CYP2C8, respectively) and the inhibitory or inducing potency of the perpetrator drug (IRCYP2B6, IRCYP2C8 and ICCYP2B6, for inhibition of CYP2B6 and CYP2C8, and induction of CYP2B6, respectively). The workflow consisted of three main phases. First, the initial estimates of the parameters were estimated through GA. Then, the model was validated using an external validation. Finally, the parameter values were refined via a Bayesian orthogonal regression using all data.

RESULTS

The AUC ratios of 5 substrates, 11 inhibitors and 19 inducers of CYP2B6, and the AUC ratios of 19 substrates and 23 inhibitors of CYP2C8 were successfully predicted by the developed methodology within 50-200% of observed values.

CONCLUSIONS

The approach proposed in this work may represent a useful tool for evaluating the suitable doses of a CYP2C8 or CYP2B6 substrates co-administered with perpetrators.

Membrane transporters in drug development and as determinants of precision medicine

The effect of membrane transporters on drug disposition, efficacy and safety is now well recognized. Since the initial publication from the International Transporter Consortium, significant progress has been made in understanding the roles and functions of transporters, as well as in the development of tools and models to assess and predict transporter-mediated activity, toxicity and drug-drug interactions (DDIs). Notable advances include an increased understanding of the effects of intrinsic and extrinsic factors on transporter activity, the application of physiologically based pharmacokinetic modelling in predicting transporter-mediated drug disposition, the identification of endogenous biomarkers to assess transporter-mediated DDIs and the determination of the cryogenic electron microscopy structures of SLC and ABC transporters. This article provides an overview of these key developments, highlighting unanswered questions, regulatory considerations and future directions.

Identification and characterization of endogenous biomarkers for hepatic vectorial transport (OATP1B3-P-gp) function using metabolomics with serum pharmacology

The organic anion-transporting polypeptide 1B3 and P-glycoprotein (P-gp) provide efficient directional transport (OATP1B3-P-gp) from the blood to the bile that serves as a key determinant of hepatic disposition of the drug. Unfortunately, there is still a lack of effective means to evaluate the disposal ability mediated by transporters. The present study was designed to identify a suitable endogenous biomarker for the assessment of OATP1B3-P-gp function in the liver. We established stably transfected HEK293T-OATP1B3 and HEK293T-P-gp cell lines. Results showed that azelaic acid (AzA) was an endogenous substrate for OATP1B3 and P-gp using serum pharmacology combined with metabolomics. There is a good correlation between the serum concentration of AzA and probe drugs of rOATP1B3 and rP-gp when rats were treated with their inhibitors. Importantly, after 5-fluorouracil-induced rat liver injury, the relative mRNA level and expression of rOATP1B3 and rP-gp were markedly down-regulated in the liver, and the serum concentration of AzA was significantly increased. These observations suggest that AzA is an endogenous substrate of both OATP1B3 and P-gp, and may serve as a potential endogenous biomarker for the assessment of the function of OATP1B3-P-gp for the prediction of changes in the pharmacokinetics of drugs transported by OATP1B3-P-gp in liver disease states.

A Review of CYP-Mediated Drug Interactions: Mechanisms and In Vitro Drug-Drug Interaction Assessment

Drug metabolism is a major determinant of drug concentrations in the body. Drug-drug interactions (DDIs) caused by the co-administration of multiple drugs can lead to alteration in the exposure of the victim drug, raising safety or effectiveness concerns. Assessment of the DDI potential starts with in vitro experiments to determine kinetic parameters and identify risks associated with the use of comedication that can inform future clinical studies. The diverse range of experimental models and techniques has significantly contributed to the examination of potential DDIs. Cytochrome P450 (CYP) enzymes are responsible for the biotransformation of many drugs on the market, making them frequently implicated in drug metabolism and DDIs. Consequently, there has been a growing focus on the assessment of DDI risk for CYPs. This review article provides mechanistic insights underlying CYP inhibition/induction and an overview of the in vitro assessment of CYP-mediated DDIs.

Drug-Drug Interaction Potential of Remimazolam: CYP 450, Transporters, and Protein Binding

BACKGROUND

The ultra-short-acting benzodiazepine, remimazolam, is a new treatment modality for procedural sedation and general anesthesia. Its activity is terminated by carboxylesterase 1 (CES1).

OBJECTIVE

The objective of this study was to determine the drug-drug interaction (DDI) potential of remimazolam through mechanisms unrelated to its metabolizing enzyme, CES1.

METHODS

Conventional in vitro co-exposure experiments were conducted to study possible interactions of remimazolam and its primary metabolite, CNS7054, mediated by competitive binding to plasma protein or reactions with cytochrome P450 isoforms or drug transporters.

RESULTS

No relevant interactions of remimazolam or its metabolite with cytochrome P450 (CYP) isoforms at clinically relevant concentrations were identified. Likewise, standard experiments revealed no clinically relevant interactions with drug transporters and plasma proteins.

CONCLUSION

The present data and analyses suggest a very low potential of remimazolam for pharmacokinetic DDIs mediated by CYP isoforms, drug transporters, and protein binding.

Development of 4-Pyridoxic Acid PBPK Model to Support Biomarker-Informed Evaluation of OAT1/3 Inhibition and Effect of Chronic Kidney Disease

Monitoring endogenous biomarkers is increasingly used to evaluate transporter-mediated drug-drug interactions (DDIs) in early drug development and may be applied to elucidate changes in transporter activity in disease. 4-pyridoxic acid (PDA) has been identified as the most sensitive plasma endogenous biomarker of renal organic anion transporters (OAT1/3). Increase in PDA baseline concentrations was observed after administration of probenecid, a strong clinical inhibitor of OAT1/3 and also in patients with chronic kidney disease (CKD). The aim of this study was to develop and verify a physiologically-based pharmacokinetic (PBPK) model of PDA, to predict the magnitude of probenecid DDI and predict the CKD-related changes in PDA baseline. The PBPK model for PDA was first developed in healthy population, building on from previous population pharmacokinetic modeling, and incorporating a mechanistic kidney model to consider OAT1/3-mediated renal secretion. Probenecid PBPK model was adapted from the Simcyp database and re-verified to capture its dose-dependent pharmacokinetics (n = 9 studies). The PBPK model successfully predicted the PDA plasma concentrations, area under the curve, and renal clearance in healthy subjects at baseline and after single/multiple probenecid doses. Prospective simulations in severe CKD predicted successfully the increase in PDA plasma concentration relative to healthy (within 2-fold of observed data) after accounting for 60% increase in fraction unbound in plasma and additional 50% decline in OAT1/3 activity beyond the decrease in glomerular filtration rate. The verified PDA PBPK model supports future robust evaluation of OAT1/3 DDI in drug development and increases our confidence in predicting exposure and renal secretion in patients with CKD.

Use of In Vivo Imaging and Physiologically-Based Kinetic Modelling to Predict Hepatic Transporter Mediated Drug-Drug Interactions in Rats

Gadoxetate, a magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 and multidrug resistance-associated protein 2. Six drugs, with varying degrees of transporter inhibition, were used to assess gadoxetate dynamic contrast enhanced MRI biomarkers for transporter inhibition in rats. Prospective prediction of changes in gadoxetate systemic and liver AUC (AUCR), resulting from transporter modulation, were performed by physiologically-based pharmacokinetic (PBPK) modelling. A tracer-kinetic model was used to estimate rate constants for hepatic uptake (khe), and biliary excretion (kbh). The observed median fold-decreases in gadoxetate liver AUC were 3.8- and 1.5-fold for ciclosporin and rifampicin, respectively. Ketoconazole unexpectedly decreased systemic and liver gadoxetate AUCs; the remaining drugs investigated (asunaprevir, bosentan, and pioglitazone) caused marginal changes. Ciclosporin decreased gadoxetate khe and kbh by 3.78 and 0.09 mL/min/mL, while decreases for rifampicin were 7.20 and 0.07 mL/min/mL, respectively. The relative decrease in khe (e.g., 96% for ciclosporin) was similar to PBPK-predicted inhibition of uptake (97-98%). PBPK modelling correctly predicted changes in gadoxetate systemic AUCR, whereas underprediction of decreases in liver AUCs was evident. The current study illustrates the modelling framework and integration of liver imaging data, PBPK, and tracer-kinetic models for prospective quantification of hepatic transporter-mediated DDI in humans.

Transporters in Regulatory Science: Notable Contributions from Dr. Giacomini in the Past Two Decades

Transporters govern the access of molecules to cells or their exit from cells, thereby controlling the overall distribution of drugs to their intracellular site of action. Clinically relevant drug-drug interactions mediated by transporters are of increasing interest in drug development. Drug transporters, acting alone or in concert with drug metabolizing enzymes, can play an important role in modulating drug absorption, distribution, metabolism, and excretion, thus affecting the pharmacokinetics and/or pharmacodynamics of a drug. Dr. Kathy Giacomini from the University of California, San Francisco is one of the world leaders in transporters and pharmacogenetics with key contributions to transporter science. Her contributions to transporter science are noteworthy. This review paper will summarize Dr. Giacomini's key contributions and influence on transporters in regulatory science in the past two decades. Regulatory science research highlighted in this review covers various aspects of transporter science including understanding the effect of renal impairment on transporters, transporter ontogeny, biomarkers for transporters, and interactions of excipients with transporters affecting drug absorption. Significance Statement This review paper highlights Dr. Giacomini's key contributions and influence on transporters in regulatory science in the past two decades. She has been at the cutting edge of science pertaining to drug transport, drug disposition, and regulatory science, leading to new era of translational sciences pertaining to drug disposition and transporter biology. Her research has and will continue to bring enormous impact on gaining new knowledge in guiding drug development and inspire scientists from all sectors in the field.

Physiologically based pharmacokinetic combined JAK2 occupancy modelling to simulate PK and PD of baricitinib with kidney transporter inhibitors and in patients with hepatic/renal impairment

PURPOSE

Our aim is to build a physiologically based pharmacokinetic and JAK2 occupancy model (PBPK-JO) to simultaneously predict pharmacokinetic (PK) and pharmacodynamic (PD) changes of baricitinib (BAR) in healthy humans when co-administrated with kidney transporters OAT3 and MATE2-K inhibitors, and in patients with hepatic and renal impairment.

METHODS

Probenecid and vandetanib were selected as OAT3 and MATE2-K competitive inhibitors, respectively. The PBPK-JO model was built using physicochemical and biochemical properties of BAR, and then verified by observed clinical PK. Finally, the model was applied to determine optimal dosing regimens in various clinical situations.

RESULTS

Here, we have successfully simulated PK and JAK2 occupancy profiles in humans by PBPK-JO model. Moreover, this modelling reproduced every observed PK data, and every mean relative deviation (MRD) was below 2. The simulation suggested that PK of BAR had a significant change (2.22-fold increase), however PD only had a slight increase of 1.14-fold. Additionally, the simulation also suggested that vandetanib was almost unlikely to affect the PK and PD of BAR. In simulations of hepatic and renal impairment patients, the predictions suggested that significant changes in the PK and PD of BAR occurred. However, there was a lower fold increase in JAK2 occupancy than in PK in patients relative to healthy individuals.

CONCLUSION

Administration dose adjustment of BAR when co-administrated with OAT3 inhibitors or in patients with hepatic or renal impairment should combine PK and PD changes of BAR, instead of only considering PK alteration.

Recent advances in the translation of drug metabolism and pharmacokinetics science for drug discovery and development

Drug metabolism and pharmacokinetics (DMPK) is an important branch of pharmaceutical sciences. The nature of ADME (absorption, distribution, metabolism, excretion) and PK (pharmacokinetics) inquiries during drug discovery and development has evolved in recent years from being largely descriptive to seeking a more quantitative and mechanistic understanding of the fate of drug candidates in biological systems. Tremendous progress has been made in the past decade, not only in the characterization of physiochemical properties of drugs that influence their ADME, target organ exposure, and toxicity, but also in the identification of design principles that can minimize drug-drug interaction (DDI) potentials and reduce the attritions. The importance of membrane transporters in drug disposition, efficacy, and safety, as well as the interplay with metabolic processes, has been increasingly recognized. Dramatic increases in investments on new modalities beyond traditional small and large molecule drugs, such as peptides, oligonucleotides, and antibody-drug conjugates, necessitated further innovations in bioanalytical and experimental tools for the characterization of their ADME properties. In this review, we highlight some of the most notable advances in the last decade, and provide future perspectives on potential major breakthroughs and innovations in the translation of DMPK science in various stages of drug discovery and development.

Inhibition of Cytochrome P450s by Strobilanthes crispus Sub-Fraction (F3): Implication for Herb-Drug Interaction

BACKGROUND AND OBJECTIVE

Strobilanthes crispus Blume sub-fraction (F3) has been reported to be cytotoxic against cancer cells and to cause murine mammary tumor regression. Potential utilization of F3 as an adjuvant in breast cancer treatment to alleviate chemotherapeutic drug resistance is currently hampered by potential cytochrome P450 (CYP)-mediated herb-drug interactions (HDIs). The current study assessed the inhibitory potency of F3 towards five CYP enzymes involved in tamoxifen metabolism.

METHODS

Potential CYP inhibition by F3 was first determined using fluorescence assays, using known CYP inhibitors as reference. To further ascertain the inhibitory potency and mode of inhibition, high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis of specific metabolites of a CYP probe substrate was conducted.

RESULTS

The half-maximal inhibitory concentration (IC₅₀) values indicate that F3 exhibited relatively weak inhibition on CYP2B6, CYP2C19, CYP2D6, and CYP3A4. Highest susceptibility to inhibition by F3 was observed for CYP2C9, where the IC₅₀ value from fluorescence-based assay was 35-fold higher than control. Further analysis by HPLC-MS/MS revealed relatively weak mixed-type inhibition of F3 on CYP2C9, as indicated by IC₅₀ and inhibition constant (K_I) values. The risk of clinically significant CYP2C9 inhibition by F3 was then predicted based on the attained K_I value and the presumed amount of F3 absorbed from S. crispus leaves following consumption. The calculated maximum plasma concentration to inhibition constant C_max/K_I) ratio suggests that F3 consumption could potentially result in clinically significant drug interactions with medications metabolized by CYP2C9.

CONCLUSION

Taken together, the results revealed a low probability of inhibition by F3 on CYP enzymes involved in tamoxifen metabolism. However, further in vivo investigation is necessary for potential F3 interaction with CYP2C9. The utility of a preliminary in vitro approach in the assessment of potential HDI was demonstrated in this study.

Physiologically Based Pharmacokinetic Modeling of Transporter-Mediated Hepatic Disposition of Imaging Biomarker Gadoxetate in Rats

Physiologically based pharmacokinetic (PBPK) models are increasingly used in drug development to simulate changes in both systemic and tissue exposures that arise as a result of changes in enzyme and/or transporter activity. Verification of these model-based simulations of tissue exposure is challenging in the case of transporter-mediated drug–drug interactions (tDDI), in particular as these may lead to differential effects on substrate exposure in plasma and tissues/organs of interest. Gadoxetate, a promising magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 (OATP1B1) and multidrug resistance-associated protein 2 (MRP2). In this study, we developed a gadoxetate PBPK model and explored the use of liver-imaging data to achieve and refine in vitro–in vivo extrapolation (IVIVE) of gadoxetate hepatic transporter kinetic data. In addition, PBPK modeling was used to investigate gadoxetate hepatic tDDI with rifampicin i.v. 10 mg/kg. In vivo dynamic contrast-enhanced (DCE) MRI data of gadoxetate in rat blood, spleen, and liver were used in this analysis. Gadoxetate in vitro uptake kinetic data were generated in plated rat hepatocytes. Mean (%CV) in vitro hepatocyte uptake unbound Michaelis–Menten constant (K_m,u) of gadoxetate was 106 μM (17%) (n = 4 rats), and active saturable uptake accounted for 94% of total uptake into hepatocytes. PBPK–IVIVE of these data (bottom-up approach) captured reasonably systemic exposure, but underestimated the in vivo gadoxetate DCE–MRI profiles and elimination from the liver. Therefore, in vivo rat DCE–MRI liver data were subsequently used to refine gadoxetate transporter kinetic parameters in the PBPK model (top-down approach). Active uptake into the hepatocytes refined by the liver-imaging data was one order of magnitude higher than the one predicted by the IVIVE approach. Finally, the PBPK model was fitted to the gadoxetate DCE–MRI data (blood, spleen, and liver) obtained with and without coadministered rifampicin. Rifampicin was estimated to inhibit active uptake transport of gadoxetate into the liver by 96%. The current analysis highlighted the importance of gadoxetate liver data for PBPK model refinement, which was not feasible when using the blood data alone, as is common in PBPK modeling applications. The results of our study demonstrate the utility of organ-imaging data in evaluating and refining PBPK transporter IVIVE to support the subsequent model use for quantitative evaluation of hepatic tDDI.

Quantitative prediction of P-glycoprotein-mediated drug-drug interactions and intestinal absorption using humanized mice

BACKGROUND AND PURPOSE

P-glycoprotein (P-gp) exhibits a broad substrate specificity and affects pharmacokinetics, especially intestinal absorption. However, prediction, in vivo, of P-gp-mediated drug-drug interaction (DDI) and non-linear absorption at the preclinical stage, is challenging. Here we evaluate the use of human MDR1 mouse artificial chromosome (hMDR1-MAC) mice carrying human P-gp and lacking their own murine P-gp to quantitatively predict human P-gp-mediated DDI and non-linear absorption.

EXPERIMENTAL APPROACH

The P-gp substrates (aliskiren, betrixaban, celiprolol, digoxin, fexofenadine and talinolol) were administered orally to wild-type, Mdr1a/b-knockout (KO) and hMDR1-MAC mice, and their plasma concentrations were measured. We calculated the ratio of area under the curve (AUCR) in mice (AUC_Mdr1a/b-KO /AUC_wild-type or AUC_Mdr1a/b-KO /AUC_hMDR1-MAC ) estimated as attributable to complete P-gp inhibition and the human AUCR with and without P-gp inhibitor administration. The correlations of AUCR_human with AUCR_wild-type and AUCR_hMDR1-MAC were investigated. For aliskiren, betrixaban and celiprolol, the K_m and V_max values for P-gp in hMDR1-MAC mice and humans were optimized from different dosing studies using GastroPlus. The correlations of K_m and V_max for P-gp between human and hMDR1-MAC mice were investigated.

KEY RESULTS

A better correlation between AUCR_human and AUCR_hMDR1-MAC (R²  = 0.88) was observed. Moreover, good relationships of K_m (R²  = 1.00) and V_max (R²  = 0.98) for P-gp between humans and hMDR1-MAC mice were observed.

CONCLUSIONS AND IMPLICATIONS

These results suggest that P-gp-mediated DDI and non-linear absorption can be predicted using hMDR1-MAC mice. These mice are a useful in vivo tool for quantitatively predicting P-gp-mediated disposition in drug discovery and development.

UPLC-MS/MS method for the simultaneous quantification of pravastatin, fexofenadine, rosuvastatin, and methotrexate in a hepatic uptake model and its application to the possible drug-drug interaction study of triptolide

A rapid and specific UPLC-MS/MS method with a total run time of 3.5 min was developed for the determination of pravastatin, fexofenadine, rosuvastatin, and methotrexate in rat primary hepatocytes. After protein precipitation with 70% acetonitrile (containing 30% H2 O), these four analytes were separated under gradient conditions with a mobile phase consisting of 0.03% acetic acid (v/v) and methanol at a flow rate of 0.50 mL/min. The linearity, recovery, matrix effect, accuracy, precision, and stability of the method were well validated. We evaluated drug-drug interactions based on these four compounds in freshly suspended hepatocytes. The hepatic uptake of pravastatin, fexofenadine, rosuvastatin, and methotrexate at 4°C was significantly lower than that at 37°C, and the hepatocytes were saturable with increased substrate concentration and culture time, suggesting that the rat primary hepatocyte model was successfully established. Triptolide showed a significant inhibitory effect on the hepatic uptake of these four compounds. In conclusion, this method was successfully employed for the quantification of pravastatin, fexofenadine, rosuvastatin, and methotrexate and was used to verify the rat primary hepatocyte model for Oatp1, Oatp2, Oatp4, and Oat2 transporter studies. Then, we applied this model to explore the effect of triptolide on these four transporters.

Population pharmacokinetic modeling and simulation to support qualification of pyridoxic acid as endogenous biomarker of OAT1/3 renal transporters

Renal clearance of many drugs is mediated by renal organic anion transporters OAT1/3 and inhibition of these transporters may lead to drug‐drug interactions (DDIs). Pyridoxic acid (PDA) and homovanillic acid (HVA) were indicated as potential biomarkers of OAT1/3. The objective of this study was to develop a population pharmacokinetic model for PDA and HVA to support biomarker qualification. Simultaneous fitting of biomarker plasma and urine data in the presence and absence of potent OAT1/3 inhibitor (probenecid, 500 mg every 6 h) was performed. The impact of study design (multiple vs. single dose of OAT1/3 inhibitor) and ability to detect interactions in the presence of weak/moderate OAT1/3 inhibitors was investigated, together with corresponding power calculations. The population models developed successfully described biomarker baseline and PDA/HVA OAT1/3‐mediated interaction data. No prominent effect of circadian rhythm on PDA and HVA individual baseline levels was evident. Renal elimination contributed greater than 80% to total clearance of both endogenous biomarkers investigated. Estimated probenecid unbound in vivo OAT inhibitory constant was up to 6.4‐fold lower than in vitro values obtained with PDA as a probe. The PDA model was successfully verified against independent literature reported datasets. No significant difference in power of DDI detection was found between multiple and single dose study design when using the same total daily dose of 2000 mg probenecid. Model‐based simulations and power calculations confirmed sensitivity and robustness of plasma PDA data to identify weak, moderate, and strong OAT1/3 inhibitors in an adequately powered clinical study to support optimal design of prospective clinical OAT1/3 interaction studies.

In vitro evaluations for pharmacokinetic drug-drug interactions of a novel serotonin-dopamine activity modulator, brexpiprazole

Brexpiprazole, a serotonin-dopamine activity modulator, is indicated for the treatment of schizophrenia and also adjunctive therapy to antidepressants for the treatment of Major Depressive Disorder. To determine the drug-drug interaction risk for cytochrome P450, and SLC and ABC transporters, brexpiprazole and its metabolite, DM-3411 were assessed in this in vitro investigation.Brexpiprazole exhibited weak inhibitory effects (IC₅₀ >13 μmol/L) on CYP2C9, CYP2C19, CYP2D6 and CYP3A4 activities, but had moderate inhibitor activity on CYP2B6 (IC₅₀ 8.19 μmol/L). The ratio of systemic unbound concentration (3.8 nmol/L) to the K_i value was sufficiently low. DM-3411 had comparable inhibitory potentials with brexpiprazole only for CYP2D6 and CYP3A4. The mRNA expressions of CYP1A2, CYP2B6 and CYP3A4 were not changed by the exposure of brexpiprazole to human hepatocytes.Brexpiprazole and DM-3411 exhibited weak or no inhibitory effects for hepatic and renal transporters (OATPs, OATs, OCTs, MATE1, and BSEP), except for MATE-2K (0.156 μmol/L of DM-3411), even for which the ratio to systemic unbound concentration (5.3 nmol/L) was sufficiently low.Brexpiprazole effected the functions of P-gp and BCRP with IC₅₀ values of 6.31 and 1.16 μmol/L, respectively, however, the pharmacokinetic alteration was not observed in the clinical concomitant study on P-gp and BCRP substrates.These in vitro data suggest that brexpiprazole is unlikely to cause clinically relevant drug interactions resulting from the effects on CYPs or transporters mediating the absorption, metabolism, and/or disposition of co-administered drugs.

Innovation in bioanalytical strategies and in vitro drug-drug interaction study approaches in drug discovery

Failure to evaluate actual toxicities of investigational molecules in drug discovery is majorly due to inadequate evaluation of their pharmacokinetics. Limitation of conventional drug metabolism profiling procedure demands advancement of existing approaches. Various techniques such as 3D cell culture system, bio microfluidic OoC model, sandwich culture model is in pipeline to be employed at their full potential in drug discovery phase. Although they outweigh the conventional techniques in various aspects, a more detailed exploration of applicability in terms of automation and high throughput analysis is required. This review extensively discusses various ongoing innovations in bioanalytical techniques. The review also proposed various scientific strategies to be adopted for prior assessment of interaction possibilities in translational drug discovery research.

Pharmacokinetic Estimation Models-based Approach to Predict Clinical Implications for CYP Induction by Calcitriol in Human Cryopreserved Hepatocytes and HepaRG Cells

Calcitriol, a vitamin D₃ metabolite, is approved for various indications because it is the bioactive form of vitamin D in the body. The purpose of this study was to predict the clinical significance of cytochrome P450 (CYP) induction by calcitriol using in vitro human cryopreserved hepatocytes, HepaRG experimental systems, and various pharmacokinetic estimation models. CYP2B6, 3A4, 2C8, and 2C9 mRNA levels increased in a concentration-dependent manner in the presence of calcitriol in human cryopreserved hepatocytes and HepaRG cells. Using the half maximal effective concentration (EC₅₀) and maximum induction effect (E_max) obtained from the in vitro study, a basic kinetic model was applied, suggesting clinical relevance. In addition, a static mechanistic model showed the improbability of a clinically significant effect; however, the calculated area under the plasma concentration-time curve ratio (AUCR) was marginal for CYP3A4 in HepaRG cells. To clarify the effect of CYP3A4 in vivo, physiologically based pharmacokinetic (PBPK) modeling was applied as a dynamic mechanistic model, revealing a low clinically significant effect of CYP3A4 induction by calcitriol. Therefore, we conclude that CYP induction by calcitriol treatment would not be clinically significant under typical clinical conditions.

Evaluation of Pharmacokinetic Drug-Drug Interactions: A Review of the Mechanisms, In Vitro and In Silico Approaches

Pharmacokinetic drug–drug interactions (DDIs) occur when a drug alters the absorption, transport, distribution, metabolism or excretion of a co-administered agent. The occurrence of pharmacokinetic DDIs may result in the increase or the decrease of drug concentrations, which can significantly affect the drug efficacy and safety in patients. Enzyme-mediated DDIs are of primary concern, while the transporter-mediated DDIs are less understood but also important. In this review, we presented an overview of the different mechanisms leading to DDIs, the in vitro experimental tools for capturing the factors affecting DDIs, and in silico methods for quantitative predictions of DDIs. We also emphasized the power and strategy of physiologically based pharmacokinetic (PBPK) models for the assessment of DDIs, which can integrate relevant in vitro data to simulate potential drug interaction in vivo. Lastly, we pointed out the future directions and challenges for the evaluation of pharmacokinetic DDIs.

Identification of potential therapeutic target of naringenin in breast cancer stem cells inhibition by bioinformatics and in vitro studies

Cancer therapy is a strategic measure in inhibiting breast cancer stem cell (BCSC) pathways. Naringenin, a citrus flavonoid, was found to increase breast cancer cells' sensitivity to chemotherapeutic agents. Bioinformatics study and 3D tumorsphere in vitro modeling in breast cancer (mammosphere) were used in this study, which aims to explore the potential therapeutic targets of naringenin (PTTNs) in inhibiting BCSCs. Bioinformatic analyses identified direct target proteins (DTPs), indirect target proteins (ITPs), naringenin-mediated proteins (NMPs), BCSC regulatory genes, and PTTNs. The PTTNs were further analyzed for gene ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, protein-protein interaction (PPI) networks, and hub protein selection. Mammospheres were cultured in serum-free media. The effects of naringenin were measured by MTT-based cytotoxicity, mammosphere forming potential (MFP), colony formation, scratch wound-healing assay, and flow cytometry-based cell cycle analyses and apoptosis assays. Gene expression analysis was performed using real-time quantitative polymerase chain reaction (q-RT PCR). Bioinformatics analysis revealed p53 and estrogen receptor alpha (ERα) as PTTNs, and KEGG pathway enrichment analysis revealed that TGF-ß and Wnt/ß-catenin pathways are regulated by PTTNs. Naringenin demonstrated cytotoxicity and inhibited mammosphere and colony formation, migration, and epithelial to mesenchymal transition in the mammosphere. The mRNA of tumor suppressors P53 and ERα were downregulated in the mammosphere, but were significantly upregulated upon naringenin treatment. By modulating the P53 and ERα mRNA, naringenin has the potential of inhibiting BCSCs. Further studies on the molecular mechanism and formulation of naringenin in BCSCs would be beneficial for its development as a BCSC-targeting drug.

Multifaceted Factors Causing Conflicting Outcomes in Herb-Drug Interactions

Metabolic enzyme and/or transporter-mediated pharmacokinetic (PK) changes in a drug caused by concomitant herbal products have been a primary issue of herb and drug interactions (HDIs), because PK changes of a drug may result in the alternation of efficacy and toxicity. Studies on HDIs have been carried out by predictive in vitro and in vivo preclinical studies, and clinical trials. Nevertheless, the discrepancies between predictive data and the clinical significance on HDIs still exist, and different reports of HDIs add to rather than clarify the confusion regarding the use of herbal products and drug combinations. Here, we briefly review the underlying mechanisms causing PK-based HDIs, and more importantly summarize challenging issues, such as dose and treatment period effects, to be considered in study designs and interpretations of HDI evaluations.

Multi-factorial pharmacokinetic interactions: unraveling complexities in precision drug therapy

Introduction: Precision drug therapy requires accounting for pertinent factors in pharmacokinetic (PK) inter-individual variability (i.e., pharmacogenetics, diseases, polypharmacy, and natural product use) that can cause sub-therapeutic or adverse effects. Although each of these individual factors can alter victim drug PK, multi-factorial interactions can cause additive, synergistic, or opposing effects. Determining the magnitude and direction of these complex multi-factorial effects requires understanding the rate-limiting redundant and/or sequential PK processes for each drug.Areas covered: Perturbations in drug-metabolizing enzymes and/or transporters are integral to single- and multi-factorial PK interactions. Examples of single factor PK interactions presented include gene-drug (pharmacogenetic), disease-drug, drug-drug, and natural product-drug interactions. Examples of multi-factorial PK interactions presented include drug-gene-drug, natural product-gene-drug, gene-gene-drug, disease-natural product-drug, and disease-gene-drug interactions. Clear interpretation of multi-factorial interactions can be complicated by study design, complexity in victim drug PK, and incomplete mechanistic understanding of victim drug PK.Expert opinion: Incorporation of complex multi-factorial PK interactions into precision drug therapy requires advances in clinical decision tools, intentional PK study designs, drug-metabolizing enzyme and transporter fractional contribution determinations, systems and computational approaches (e.g., physiologically-based pharmacokinetic modeling), and PK phenotyping of progressive diseases.

Predicting Metabolism-Related Drug-Drug Interactions Using a Microphysiological Multitissue System

Drug-drug interactions (DDIs) occur when the pharmacological activity of one drug is altered by a second drug. As multimorbidity and polypharmacotherapy are becoming more common due to the increasing age of the population, the risk of DDIs is massively increasing. Therefore, in vitro testing methods are needed to capture such multiorgan events. Here, a scalable, gravity-driven microfluidic system featuring 3D microtissues (MTs) that represent different organs for the prediction of drug-drug interactions is used. Human liver microtissues (hLiMTs) are combined with tumor microtissues (TuMTs) and treated with drug combinations that are known to cause DDIs in vivo. The testing system is able to capture and quantify DDIs upon co-administration of the anticancer prodrugs cyclophosphamide or ifosfamide with the antiretroviral drug ritonavir. Dosage of ritonavir inhibits hepatic metabolization of the two prodrugs to different extents and decreases their efficacy in acting on TuMTs. The flexible MT compartment design of the system, the use of polystyrene as chip material, and the assembly of several chips in stackable plates offer the potential to significantly advance preclinical substance testing. The possibility of testing a broad variety of drug combinations to identify possible DDIs will improve the drug development process and increase patient safety.

Identification of Appropriate Endogenous Biomarker for Risk Assessment of Multidrug and Toxin Extrusion Protein-Mediated Drug-Drug Interactions in Healthy Volunteers

Endogenous biomarkers are emerging to advance clinical drug‐drug interaction (DDI) risk assessment in drug development. Twelve healthy subjects received a multidrug and toxin exclusion protein (MATE) inhibitor (pyrimethamine, 10, 25, and 75 mg) in a crossover fashion to identify an appropriate endogenous biomarker to assess MATE1/2‐K‐mediated DDI in the kidneys. Metformin (500 mg) was also given as reference probe drug for MATE1/2‐K. In addition to the previously reported endogenous biomarker candidates (creatinine and N¹‐methylnicotinamide (1‐NMN)), N¹‐methyladenosine (m¹A) was included as novel biomarkers. 1‐NMN and m¹A presented as superior MATE1/2‐K biomarkers since changes in their renal clearance (CL_r) along with pyrimethamine dose were well‐correlated with metformin CL_r changes. The CL_r of creatinine was reduced by pyrimethamine, however, its changes poorly correlated with metformin CL_r changes. Nonlinear regression analysis (CL_r vs. mean total concentration of pyrimethamine in plasma) yielded an estimate of the inhibition constant (K_i) of pyrimethamine and the fraction of the clearance pathway sensitive to pyrimethamine. The in vivoK_i value thus obtained was further converted to unbound Ki using plasma unbound fraction of pyrimethamine, which was comparable to the in vitroK_i for MATE1 (1‐NMN) and MATE2‐K (1‐NMN and m¹A). It is concluded that 1‐NMN and m¹A CL_r can be leveraged as quantitative MATE1/2‐K biomarkers for DDI risk assessment in healthy volunteers.

Predicting the effect of tea polyphenols on ticagrelor by incorporating transporter-enzyme interplay mechanism

This study aimed at exploring the potential mechanism of decreased in vivo exposure of the antiplatelet agent, ticagrelor and its active metabolite, AR-C124910XX, mediated by tea polyphenols, which was first revealed by our previous study, as well as predicting the in vivo drug-drug interaction (DDI) potential utilizing an in vitro to in vivo extrapolation (IVIVE) approach. The bidirectional transport and uptake kinetics of ticagrelor were determined using Caco-2 cells. Inhibition potency of major components of tea polyphenols, epigallocatechin gallate (EGCG) and epigallocatechin (EGC) were obtained from Caco-2 cells, human intestinal and hepatic microsomes (HIMs and HLMs) in vitro. A mean efflux ratio of 2.28 ± 0.38 and active uptake behavior of ticagrelor were observed in Caco-2 cell studies. Further investigation showed that the IC₅₀ values of EGCG and EGC on the uptake of ticagrelor were 42.0 ± 5.1 μM (95% CI 31.9-54.8 μM) and 161 ± 13 μM (95% CI 136-191 μM), respectively. EGCG and EGC also displayed moderate to weak reversible inhibition on the formation of AR-C124910XX and the inactive metabolite, AR-C133913XX in HIMs and HLMs, while no clinically significant time-dependent inhibition was observed for either compound. IVIVE indicated a significant inhibition effect of EGCG on the uptake process of ticagrelor, while no potential DDI risk was found based on microsomal data. A 45% decrease in ticagrelor in vivo exposure was mechanistically predicted by incorporating intestinal and hepatic metabolism as well as intestinal absorption. This dual inhibition of tea polyphenols on ticagrelor revealed the underlying potential of transporter-enzyme interplay, in which the altered uptake process was more critical.

A Novel Physiologically Based Model of Creatinine Renal Disposition to Integrate Current Knowledge of Systems Parameters and Clinical Observations

Creatinine is the most common clinical biomarker of renal function. As a substrate for renal transporters, its secretion is susceptible to inhibition by drugs, resulting in transient increase in serum creatinine and false impression of damage to kidney. Novel physiologically based models for creatinine were developed here and (dis)qualified in a stepwise manner until consistency with clinical data. Data from a matrix of studies were integrated, including systems data (common to all models), proteomics-informed in vitro-in vivo extrapolation of all relevant transporter clearances, exogenous administration of creatinine (to estimate endogenous synthesis rate), and inhibition of different renal transporters (11 perpetrator drugs considered for qualification during creatinine model development and verification on independent data sets). The proteomics-informed bottom-up approach resulted in the underprediction of creatinine renal secretion. Subsequently, creatinine-trimethoprim clinical data were used to inform key model parameters in a reverse translation manner, highlighting best practices and challenges for middle-out optimization of mechanistic models.

Interpretation of Drug Interaction Using Systemic and Local Tissue Exposure Changes

Systemic exposure of a drug is generally associated with its pharmacodynamic (PD) effect (e.g., efficacy and toxicity). In this regard, the change in area under the plasma concentration-time curve (AUC) of a drug, representing its systemic exposure, has been mainly considered in evaluation of drug-drug interactions (DDIs). Besides the systemic exposure, the drug concentration in the tissues has emerged as a factor to alter the PD effects. In this review, the status of systemic exposure, and/or tissue exposure changes in DDIs, were discussed based on the recent reports dealing with transporters and/or metabolic enzymes mediating DDIs. Particularly, the tissue concentration in the intestine, liver and kidney were referred to as important factors of PK-based DDIs.

Mechanistic Models as Framework for Understanding Biomarker Disposition: Prediction of Creatinine-Drug Interactions

Creatinine is widely used as a biomarker of glomerular filtration, and, hence, renal function. However, transporter-mediated secretion also contributes to its renal clearance, albeit to a lesser degree. Inhibition of these transporters causes transient serum creatinine elevation, which can be mistaken as impaired renal function. The current study developed mechanistic models of creatinine kinetics within physiologically based framework accounting for multiple transporters involved in creatinine renal elimination, assuming either unidirectional or bidirectional-OCT2 transport (driven by electrochemical gradient). Robustness of creatinine models was assessed by predicting creatinine-drug interactions with 10 perpetrators; performance evaluation accounted for 5% intra-individual variability in serum creatinine. Models showed comparable predictive performances of the maximum steady-state effect regardless of OCT2 directionality assumptions. However, only the bidirectional-OCT2 model successfully predicted the minimal effect of ranitidine. The dynamic nature of models provides clear advantage to static approaches and most advanced framework for evaluating interplay between multiple processes in creatinine renal disposition.

Evaluation of drug-drug interactions in drug metabolism: Differences and harmonization in guidance/guidelines

The U.S. Drugs and Food Administration (FDA) and the Ministry of Health, Labor and Welfare of Japan (MHLW) issued the drastically revised draft guidance and final guideline on drug-drug interactions (DDI) in 2017 and 2018, respectively. One of the most drastic changes for the evaluation of inhibition potential of drug metabolizing enzymes in the liver using a basic model in these guidance and guideline are represented by the concept to use the unbound maximum concentration in the systemic circulation as the investigational drug concentration instead of the total maximum concentration and the corresponding cutoff values are applied in harmonization with the current DDI guideline of Europe. In this review, the current DDI guidance and guidelines of the three regions are compared and the points which are in common are described. In addition, several issues to be considered and/or clarified such as a criterion for the metabolites to be evaluated as perpetrator drugs, details of in vitro study design etc. are also briefly summarized. Based on further accumulation of data and information, and their continuous international scientific discussion, these issues are expected to be solved to make the current DDI guidance and guidelines be much more harmonized and practically available standards.

Clinical Studies on Drug-Drug Interactions Involving Metabolism and Transport: Methodology, Pitfalls, and Interpretation

Many drug-drug interactions (DDIs) are based on alterations of the plasma concentrations of a victim drug due to another drug causing inhibition and/or induction of the metabolism or transporter-mediated disposition of the victim drug. In the worst case, such interactions cause more than tenfold increases or decreases in victim drug exposure, with potentially life-threatening consequences. There has been tremendous progress in the predictability and modeling of DDIs. Accordingly, the combination of modeling approaches and clinical studies is the current mainstay in evaluation of the pharmacokinetic DDI risks of drugs. In this paper, we focus on the methodology of clinical studies on DDIs involving drug metabolism or transport. We specifically present considerations related to general DDI study designs, recommended enzyme and transporter index substrates and inhibitors, pharmacogenetic perspectives, index drug cocktails, endogenous substrates, limited sampling strategies, physiologically-based pharmacokinetic modeling, complex DDIs, methodological pitfalls, and interpretation of DDI information.

Emerging Role of Organ-on-a-Chip Technologies in Quantitative Clinical Pharmacology Evaluation

The recently enacted Prescription Drug User Fee Act (PDUFA) VI includes in its performance goals "enhancing regulatory science and expediting drug development." The key elements in "enhancing regulatory decision tools to support drug development and review" include "advancing model-informed drug development (MIDD)." This paper describes (i) the US Food and Drug Administration (FDA) Office of Clinical Pharmacology's continuing efforts in developing quantitative clinical pharmacology models (disease, drug, and clinical trial models) to advance MIDD, (ii) how emerging novel tools, such as organ-on-a-chip technologies or microphysiological systems, can provide new insights into physiology and disease mechanisms, biomarker identification and evaluation, and elucidation of mechanisms of adverse drug reactions, and (iii) how the single organ or linked organ microphysiological systems can provide critical system parameters for improved physiologically-based pharmacokinetic and pharmacodynamic evaluations. Continuous public-private partnerships are critical to advance this field and in the application of these new technologies in drug development and regulatory review.

Hepatic Organic Anion Transporting Polypeptide-Mediated Clearance in the Beagle Dog: Assessing In Vitro-In Vivo Relationships and Applying Cross-Species Empirical Scaling Factors to Improve Prediction of Human Clearance

In the present study, the beagle dog was evaluated as a preclinical model to investigate organic anion transporting polypeptide (OATP)-mediated hepatic clearance. In vitro studies were performed with nine OATP substrates in three lots of plated male dog hepatocytes ± OATP inhibitor cocktail to determine total uptake clearance (CL_uptake) and total and unbound cell-to-medium concentration ratio (Kp_uu). In vivo intrinsic hepatic clearances (CL_int,H) were determined following intravenous drug administration (0.1 mg/kg) in male beagle dogs. The in vitro parameters were compared with those previously reported in plated human, monkey, and rat hepatocytes; the ability of cross-species scaling factors to improve prediction of human in vivo clearance was assessed. CL_uptake in dog hepatocytes ranged from 9.4 to 135 µl/min/10⁶ cells for fexofenadine and telmisartan, respectively. Active process contributed >75% to CL_uptake for 5/9 drugs. Rosuvastatin and valsartan showed Kp_uu > 10, whereas cerivastatin, pitavastatin, repaglinide, and telmisartan had Kp_uu < 5. The extent of hepatocellular binding in dog was consistent with other preclinical species and humans. The bias (2.73-fold) obtained from comparison of predicted versus in vivo dog CL_int,H was applied as an average empirical scaling factor (ESF_av) for in vitro-in vivo extrapolation of human CL_int,H The ESF_av based on dog reduced underprediction of human CL_int,H for the same data set (geometric mean fold error = 2.1), highlighting its utility as a preclinical model to investigate OATP-mediated uptake. The ESF_av from all preclinical species resulted in comparable improvement of human clearance prediction, in contrast to drug-specific empirical scalars, rationalized by species differences in expression and/or relative contribution of particular transporters to drug hepatic uptake.

Mechanistic kinetic modeling generates system-independent P-glycoprotein mediated transport elementary rate constants for inhibition and, in combination with 3D SIM microscopy, elucidates the importance of microvilli morphology on P-glycoprotein mediated efflux activity

INTRODUCTION

In vitro transporter kinetics are typically analyzed by steady-state Michaelis-Menten approximations. However, no clear evidence exists that these approximations, applied to multiple transporters in biological membranes, yield system-independent mechanistic parameters needed for reliable in vivo hypothesis generation and testing. Areas covered: The classical mass action model has been developed for P-glycoprotein (P-gp) mediated transport across confluent polarized cell monolayers. Numerical integration of the mass action equations for transport using a stable global optimization program yields fitted elementary rate constants that are system-independent. The efflux active P-gp was defined by the rate at which P-gp delivers drugs to the apical chamber, since as much as 90% of drugs effluxed by P-gp partition back into nearby microvilli prior to reaching the apical chamber. The efflux active P-gp concentration was 10-fold smaller than the total expressed P-gp for Caco-2 cells, due to their microvilli membrane morphology. The mechanistic insights from this analysis are readily extrapolated to P-gp mediated transport in vivo. Expert opinion: In vitro system-independent elementary rate constants for transporters are essential for the generation and validation of robust mechanistic PBPK models. Our modeling approach and programs have broad application potential. They can be used for any drug transporter with minor adaptations.

A multiplex HRMS assay for quantifying selected human plasma bile acids as candidate OATP biomarkers

Aim: Selected bile acids (BAs) in plasma have been proposed as endogenous probes for assessing drug–drug interactions involving hepatic drug transporters such as the organic anion-transporting polypeptides (OATP1B1 and OATP1B3). Materials & methods: Plasma extracts were analyzed for selected BAs using a triple TOF API6600 high-resolution mass spectrometer. Results: Glycodeoxycholic acid 3-sulfate, glycochenodeoxycholic acid 3-sulfate, glycodeoxycholic acid 3-O-β-glucuronide and glycochenodeoxycholic acid 3-O-β-glucuronide are presented as potential OATP1B1/3 biomarkers.Conclusion: Six BAs are quantified in human plasma using a multiplexed high-resolution mass spectrometry method. Glycodeoxycholic acid 3-sulfate and glycodeoxycholic acid 3-O-β-glucuronide are proposed as potential biomarkers based on observed four- to fivefold increase in plasma AUC (vs placebo), following administration of a compound known to present as an OATP1B1/3 inhibitor in vitro.

A fully automated and validated human plasma LC–MS/MS assay for endogenous OATP biomarkers coproporphyrin-I and coproporphyrin-III

Aim: A validated LC–MS/MS assay for the quantitation of coproporphyrin-I and -III (CP-I, CP-III) in human plasma has been developed to understand the utility of both as possible endogenous biomarkers for organic anion-transporting polypeptides (OATP)-mediated drug–drug interactions (DDIs). Materials and Methods: Human plasma extracts were analyzed for CP-I and CP-III using a Sciex API 6500+ mass spectrometer. Results: The assay was utilized for plasma samples from a clinical DDI study involving a new chemical entity that presented as an OATP inhibitor in vitro. A formal DDI study, with a probe drug (atorvastatin), was also included as part of the clinical study. Conclusion: Changes in CP-I area under the plasma concentration versus time curve (AUC0–48 h) were observed, which were similar to the AUC ratio obtained with atorvastatin. These results support the idea that plasma CP-I may have utility in Phase I by supporting the rapid assessment of OATP inhibition risk.

In Vitro-In Vivo Extrapolation of OATP1B-Mediated Drug-Drug Interactions in Cynomolgus Monkey

Hepatic organic anion-transporting polypeptides (OATP) 1B1 and 1B3 are clinically relevant transporters associated with significant drug-drug interactions (DDIs) and safety concerns. Given that OATP1Bs in cynomolgus monkey share >90% degree of gene and amino acid sequence homology with human orthologs, we evaluated the in vitro-in vivo translation of OATP1B-mediated DDI risk using this preclinical model. In vitro studies using plated cynomolgus monkey hepatocytes showed active uptake K_m values of 2.0 and 3.9 µM for OATP1B probe substrates, pitavastatin and rosuvastatin, respectively. Rifampicin inhibited pitavastatin and rosuvastatin active uptake in monkey hepatocytes with IC₅₀ values of 3.0 and 0.54 µM, respectively, following preincubation with the inhibitor. Intravenous pharmacokinetics of ²H₄-pitavastatin and ²H₆-rosuvastatin (0.2 mg/kg) and the oral pharmacokinetics of cold probes (2 mg/kg) were studied in cynomolgus monkeys (n = 4) without or with coadministration of single oral ascending doses of rifampicin (1, 3, 10, and 30 mg/kg). A rifampicin dose-dependent reduction in i.v. clearance of statins was observed. Additionally, oral pitavastatin and rosuvastatin plasma exposure increased up to 19- and 15-fold at the highest dose of rifampicin, respectively. Use of in vitro IC₅₀ obtained following 1 hour preincubation with rifampicin (0.54 µM) predicted correctly the change in mean i.v. clearance and oral exposure of statins as a function of mean unbound maximum plasma concentration of rifampicin. This study demonstrates quantitative translation of in vitro OATP1B IC₅₀ to predict DDIs using cynomolgus monkey as a preclinical model and provides further confidence in application of in vitro hepatocyte data for the prediction of clinical OATP1B-mediated DDIs.

Why Drugs Fail in Late Stages of Development: Case Study Analyses from the Last Decade and Recommendations

New drug development is both resource and time intensive, where later clinical stages result in significant costs. We analyze recent late-stage failures to identify drugs where failures result from inadequate scientific advances as well as drugs where we believe pitfalls could have been avoided. These can be broadly classified into two categories: 1) where science is mature and the failures can be avoided through rigorous and prospectively determined decision-making criteria, scientific curiosity, and discipline to follow up on emerging findings; and 2) where problems encountered in Phase 3 failures cannot be explained at this time, as the science is not sufficiently advanced and companies/investigators need to recognize the possibility of deficiency of our knowledge. Through these case studies, key themes critical for successful drug development emerge-understanding the therapeutic pathway including receptor and signaling biology, pharmacological responses related to safety and efficacy, pharmacokinetics of the drug and exposure at target site, optimum dose, and dosing regimen; and identification of patient sub-populations likely to respond and will have a favorable benefit-risk profile, design of clinical trials, and a quantitative framework that can guide data-driven decision making. It is essential that the right studies are conducted early in the development process to answer the key questions, with the emphasis on learning in the early stages of development, whereas Phase 3 should be reserved for confirming the safety and efficacy. Utilization of innovative technology in identifying patients based on molecular signature of their disease, rapid assessment of pharmacological response, mechanistic modeling of emerging data, seamless operational processes to reduce start-up and wind-down time for clinical trials through use of electronic health records and data mining, and development of novel and objective clinical efficacy endpoints are some concepts for improving the success rate.

A regulatory science viewpoint on botanical-drug interactions

There is a continued predisposition of concurrent use of drugs and botanical products. Consumers often self-administer botanical products without informing their health care providers. The perceived safety of botanical products with lack of knowledge of the interaction potential poses a challenge for providers and both efficacy and safety concerns for patients. Botanical–drug combinations can produce untoward effects when botanical constituents modulate drug metabolizing enzymes and/or transporters impacting the systemic or tissue exposure of concomitant drugs. Examples of pertinent scientific literature evaluating the interaction potential of commonly used botanicals in the US are discussed. Current methodologies that can be applied to advance our efforts in predicting drug interaction liability is presented. This review also highlights the regulatory science viewpoint on botanical–drug interactions and labeling implications.

Organic anion transporter 1 (OAT1/SLC22A6) enhances bioluminescence based on d-luciferin-luciferase reaction in living cells by facilitating the intracellular accumulation of d-luciferin

Bioluminescence (BL) imaging based on d-luciferin (d-luc)-luciferase reaction allows noninvasive and real-time monitoring of luciferase-expressing cells. Because BL intensity depends on photons generated through the d-luc-luciferase reaction, an approach to increase intracellular levels of d-luc could improve the detection sensitivity. In the present study, we showed that organic anion transporter 1 (OAT1) is useful, as a d-luc transporter, in boosting the BL intensity in luciferase-expressing cells. Functional screening of several transporters showed that the expression of OAT1 in HEK293 cells stably expressing Pyrearinus termitilluminans luciferase (HEK293/eLuc) markedly enhanced BL intensity in the presence of d-luc. When OAT1 was transiently expressed in HEK293 cells, intracellular accumulation of d-luc was higher than that in control cells, and the specific d-luc uptake mediated by OAT1 was saturable with a Michaelis constant (K_m) of 0.23 μM. The interaction between OAT1 and d-luc was verified using 6-carboxyfluorescein, a typical substrate of OAT1, which showed that d-luc inhibited the uptake of 6-carboxyfluorescein mediated by OAT1. BL intensity was concentration-dependent at steady states in HEK293/eLuc cells stably expressing OAT1, and followed Michaelis-Menten kinetics with an apparent K_m of 0.36 μM. In addition, the enhanced BL was significantly inhibited by OAT1-specific inhibitors. Thus, OAT1-mediated transport of d-luc could be a rate-limiting step in the d-luc-luciferase reaction. Furthermore, we found that expressing OAT1 in HEK293/eLuc cells implanted subcutaneously in mice also significantly increased the BL after intraperitoneal injection of d-luc. Our findings suggest that because OAT1 is capable of transporting d-luc, it can also be used to improve visualization and monitoring of luciferase-expressing cells.

A highly selective and sensitive LC–MS/HRMS assay for quantifying coproporphyrins as organic anion-transporting peptide biomarkers

Aim: Coproporphyrin-I (CP-I) and coproporphyrin-III (CP-III) in plasma and urine have been proposed as biomarkers for assessing drug–drug interactions involving hepatic drug transporters such as organic anion-transporting peptides (OATP), 1B1 and 1B3. Materials & methods: Plasma and urine extracts were analyzed for CP-I/CP-III using a TripleTOF API6600 mass spectrometer. Results: Previously unreported, CP-I/CP-III doubly charged ions (m/z 328.14) were used as precursor ions to improve the assay sensitivity and selectivity over the singly charged precursor ions (m/z 655.28). Levels of CP-I and CP-III measured ranged 0.45–1.1 and 0.050–0.50 ng/ml in plasma and 5–35 and 1–35 ng/ml in urine, respectively. Conclusion: The described highly selective and sensitive CP-I/CP-III LC–HRMS assay offers options for earlier characterization and clinical safety projections for OATP1B1/3-mediated drug–drug interactions along with pharmacokinetic analyses of a new chemical entity as part of first-in-human clinical studies.