In vitro and in silico strategies to identify OATP1B1 inhibitors and predict clinical drug-drug interactions

Probe substrates assay estimates the effect of polyphyllin H on the activity of cytochrome P450 enzymes in human liver microsomes

Cytochrome P450 enzymes (CYPs) play a crucial role in phase I metabolic reactions. The activity of CYPs would affect therapeutic efficacy and may even induce toxicity. Given the complex components of traditional Chinese medicine, it is important to understand the effect of active ingredients on CYPs activity to guide their prescription. This study aimed to evaluate the effect of polyphyllin H on the activity of CYPs major isoforms providing a reference for the clinical prescription of polyphyllin H and its source herbs. The effects of polyphyllin H were evaluated in pooled human liver microsomes using probe substrates of CYP1A2, 2A6, 2C8, 2C9, 2C19, 2D6, 2E1, and 3A4 to determine their activities. The Lineweaver-Burk was used to model the inhibition, and a time-dependent inhibition experiment was performed to understand the characteristics of the inhibition. Polyphyllin H significantly suppressed the activity of CYP1A2, 2D6, and 3A4 with IC50 values of 6.44, 13.88, and 4.52 μM, respectively. The inhibition of CYP1A2 and 2D6 was best fitted with a competitive model, yielding the inhibition constant (Ki) values of 3.18 and 6.77 μM, respectively. The inhibition of CYP3A4 was fitted with the non-competitive model with the Ki value of 2.38 μM. Moreover, the inhibition of CYP3A4 was revealed to be time-dependent with the inhibition parameters inhibition constant (KI) and inactivation rate constant (Kinact) values of 2.26 μM-1 and 0.045 min-1. Polyphyllin H acted as a competitive inhibitor of CYP1A2 and 2D6 and a non-competitive and time-dependent inhibitor of CYP3A4.

Pharmaceutical Quality by Design Approach to Develop High-Performance Nanoparticles for Magnetic Hyperthermia

Magnetic hyperthermia holds significant therapeutic potential, yet its clinical adoption faces challenges. One obstacle is the large-scale synthesis of high-quality superparamagnetic iron oxide nanoparticles (SPIONs) required for inducing hyperthermia. Robust and scalable manufacturing would ensure control over the key quality attributes of SPIONs, and facilitate clinical translation and regulatory approval. Therefore, we implemented a risk-based pharmaceutical quality by design (QbD) approach for SPION production using flame spray pyrolysis (FSP), a scalable technique with excellent batch-to-batch consistency. A design of experiments method enabled precise size control during manufacturing. Subsequent modeling linked the SPION size (6-30 nm) and composition to intrinsic loss power (ILP), a measure of hyperthermia performance. FSP successfully fine-tuned the SPION composition with dopants (Zn, Mn, Mg), at various concentrations. Hyperthermia performance showed a strong nonlinear relationship with SPION size and composition. Moreover, the ILP demonstrated a stronger correlation to coercivity and remanence than to the saturation magnetization of SPIONs. The optimal operating space identified the midsized (15-18 nm) Mn0.25Fe2.75O4 as the most promising nanoparticle for hyperthermia. The production of these nanoparticles on a pilot scale showed the feasibility of large-scale manufacturing, and cytotoxicity investigations in multiple cell lines confirmed their biocompatibility. In vitro hyperthermia studies with Caco-2 cells revealed that Mn0.25Fe2.75O4 nanoparticles induced 80% greater cell death than undoped SPIONs. The systematic QbD approach developed here incorporates process robustness, scalability, and predictability, thus, supporting the clinical translation of high-performance SPIONs for magnetic hyperthermia.

Identification of inositol monophosphatase as a broad-spectrum antiviral target of ivermectin

Ivermectin has broad-spectrum antiviral activities. Despite the failure in clinical application of COVID-19, it can serve as a lead compound for the development of more effective broad-spectrum antivirals, for which a better understanding of its antiviral mechanisms is essential. We thus searched for potential novel targets of ivermectin in host cells by label-free thermal proteomic profiling using Huh-7 cells. Inositol monophosphatase (IMPase) was found among the proteins with shifted thermal stability by ivermectin. Ivermectin could inhibit IMPase activity and reduce cellular myo-inositol and phosphatidylinositol-4-phosphate levels. On the other hand, inositol could impair the antiviral activity of ivermectin and lithium, an IMPase inhibitor with known antiviral activity. As phosphatidylinositol phosphate is crucial for the replication of many RNA viruses, inhibition of cellular myo-inositol biosynthesis may be an important antiviral mechanism of ivermectin. Hence, inhibition of IMPase could serve as a potential target for broad-spectrum antiviral development.

Screening oral drugs for their interactions with the intestinal transportome via porcine tissue explants and machine learning

In vitro systems that accurately model in vivo conditions in the gastrointestinal tract may aid the development of oral drugs with greater bioavailability. Here we show that the interaction profiles between drugs and intestinal drug transporters can be obtained by modulating transporter expression in intact porcine tissue explants via the ultrasound-mediated delivery of small interfering RNAs and that the interaction profiles can be classified via a random forest model trained on the drug-transporter relationships. For 24 drugs with well-characterized drug-transporter interactions, the model achieved 100% concordance. For 28 clinical drugs and 22 investigational drugs, the model identified 58 unknown drug-transporter interactions, 7 of which (out of 8 tested) corresponded to drug-pharmacokinetic measurements in mice. We also validated the model's predictions for interactions between doxycycline and four drugs (warfarin, tacrolimus, digoxin and levetiracetam) through an ex vivo perfusion assay and the analysis of pharmacologic data from patients. Screening drugs for their interactions with the intestinal transportome via tissue explants and machine learning may help to expedite drug development and the evaluation of drug safety.

Systems biology approaches to identify driver genes and drug combinations for treating COVID-19

Corona virus 19 (Covid-19) has caused many problems in public health, economic, and even cultural and social fields since the beginning of the epidemic. However, in order to provide therapeutic solutions, many researches have been conducted and various omics data have been published. But there is still no early diagnosis method and comprehensive treatment solution. In this manuscript, by collecting important genes related to COVID-19 and using centrality and controllability analysis in PPI networks and signaling pathways related to the disease; hub and driver genes have been identified in the formation and progression of the disease. Next, by analyzing the expression data, the obtained genes have been evaluated. The results show that in addition to the significant difference in the expression of most of these genes, their expression correlation pattern is also different in the two groups of COVID-19 and control. Finally, based on the drug-gene interaction, drugs affecting the identified genes are presented in the form of a bipartite graph, which can be used as the potential drug combinations.

Amino acid derivative of probenecid potentiates apoptosis-inducing effects of vinblastine by increasing oxidative stress in a cancer cell-specific manner

Many chemotherapeutic drugs suffer from multidrug resistance (MDR). Efflux transporters, namely ATP-binding cassettes (ABCs), that pump the drugs out of the cancer cells comprise one major reason behind MDR. Therefore, ABC inhibitors have been under development for ages, but unfortunately, without clinical success. In the present study, an l-type amino acid transporter 1 (LAT1)-utilizing derivative of probenecid (PRB) was developed as a cancer cell-targeted efflux inhibitor for P-glycoprotein (P-gp), breast cancer resistant protein (BCRP) and/or several multidrug resistant proteins (MRPs), and its ability to increase vinblastine (VBL) cellular accumulation and apoptosis-inducing effects were explored. The novel amino acid derivative of PRB (2) increased the VBL exposure in triple-negative human breast cancer cells (MDA-MB-231) and human glioma cells (U-87MG) by 10-68 -times and 2-5-times, respectively, but not in estrogen receptor-positive human breast cancer cells (MCF-7). However, the combination therapy had greater cytotoxic effects in MCF-7 compared to MDA-MB-231 cells due to the increased oxidative stress recorded in MCF-7 cells. The metabolomic study also revealed that compound 2, together with VBL, decreased the transport of those amino acids essential for the biosynthesis of endogenous anti-oxidant glutathione (GSH). Moreover, the metabolic differences between the outcomes of the studied breast cancer cell lines were explained by the distinct expression profiles of solute carriers (SLCs) that can be concomitantly inhibited. Therefore, attacking several SLCs simultaneously to change the nutrient environment of cancer cells can serve as an adjuvant therapy to other chemotherapeutics, offering an alternative to ABC inhibitors.

Establishment of UGT1A1-knockout human iPS-derived hepatic organoids for UGT1A1-specific kinetics and toxicity evaluation

Uridine diphosphate glucuronosyltransferases (UGTs) are highly expressed in the liver and are involved in the metabolism of many drugs. In particular, UGT1A1 has a genetic polymorphism that causes decreased activity, leading to drug-induced hepatotoxicity. Therefore, an in vitro evaluation system that accurately predicts the kinetics of drugs involving UGT1A1 is required. However, there is no such evaluation system because of the absence of the UGT1A1-selective inhibitor. Here, using human induced pluripotent stem (iPS) cells, genome editing technology, and organoid technology, we generated UGT1A1-knockout human iPS hepatocyte-derived liver organoids (UGT1A1-KO i-HOs) as a model for UGT1A1-specific kinetics and toxicity evaluation. i-HOs showed higher gene expression of many drug-metabolizing enzymes including UGT1A1 than human iPS cell-derived hepatocyte-like cells (iPS-HLCs), suggesting that hepatic organoid technology improves liver functions. Wild-type (WT) i-HOs showed similar levels of UGT1A1 activity to primary human (cryopreserved) hepatocytes, while UGT1A1-KO i-HOs completely lost the activity. Additionally, to evaluate whether this model can be used to predict drug-induced hepatotoxicity, UGT1A1-KO i-HOs were exposed to SN-38, the active metabolite of irinotecan, an anticancer drug, and acetaminophen and confirmed that these cells could predict UGT1A1-mediated toxicity. Thus, we succeeded in generating model cells that enable evaluation of UGT1A1-specific kinetics and toxicity.

Generation of a Cell Line Selectively Producing Functionally Active OATP1B1 Transporter

The solute carrier organic anion transporter family member, OATP1B1, is one of the most important transporter proteins, which mediate penetration of many endogenous substances and xenobiotics into hepatocytes. A model system providing expression of the functional protein is needed to assess interaction of OATP1B1 with various substances. Based on the HEK293 cells, we obtained the HEK293-OATP1B1 cell line, constitutively expressing the SLCO1B1 gene encoding the OATP1B1 transporter. Expression of the SLCO1B1 gene was confirmed by real-time PCR analysis and Western blotting. Functionality of the transporter was assessed by the transport of atorvastatin, which is a substrate of OATP1B1. Cells of the resulting cell line, which selectively express the functionally active recombinant OATP1B1 transporter, can be used to study functions of the protein and to test drugs for being substrates, inducers, and inhibitors of OATP1B1, and to assess the risks of drug interactions.

Power of Integrating PBPK with PBBM (PBPK-BM): A Single Model Predicting Food Effect, Gender Impact, Drug-Drug Interactions and Bioequivalence in Fasting & Fed Conditions

Over the past few years, PBPK and PBBM modeling have proven their significance in drug development. PBPK modeling is traditionally used to predict drug-drug interactions, exposures in special populations whereas PBBM modeling is a part of PBPK modeling that is used for a range of biopharmaceutics applications.Because of these differences in utilities, often PBPK and PBBM models are developed separately. When both models are combined, they serve multiple purposes through unified model. In the present case, an integrated PBPK-PBBM model for an IR product has been utilized for bioequivalence prediction in fasting & fed conditions, evaluating gender impact and food effect, prediction of drug-drug interactions.Model was built using physicochemical properties, enzymes and transporter kinetics, bio-predictive dissolution and has been validated with passing and failed pilot BE studies. The validated model predicted pivotal bioequivalence outcome in fasting & fed conditions accurately, predicted gender impact and food effect in line with literature. Drug-drug interactions arising from transporter and metabolizing enzymes were predicted accurately.Overall, this work demonstrates utility of combining PBPK and PBBM model that can yield a single model which can be used for multiple purposes, regulatory justifications and can reduce regulatory review timelines.

Mechanistic in vitro studies indicate that the clinical drug-drug interactions between protease inhibitors and rosuvastatin are driven by inhibition of intestinal BCRP and hepatic OATP1B1 with minimal contribution from OATP1B3, NTCP and OAT3

Previous use of a mechanistic static model to accurately quantify the increased rosuvastatin exposure due to drug-drug interaction (DDI) with coadministered atazanavir underpredicted the magnitude of area under the plasma concentration-time curve ratio (AUCR) based on inhibition of breast cancer resistance protein (BCRP) and organic anion transporting polypeptide (OATP) 1B1. To reconcile the disconnect between predicted and clinical AUCR, atazanavir and other protease inhibitors (darunavir, lopinavir and ritonavir) were evaluated as inhibitors of BCRP, OATP1B1, OATP1B3, sodium taurocholate cotransporting polypeptide (NTCP) and organic anion transporter (OAT) 3. None of the drugs inhibited OAT3, nor did darunavir and ritonavir inhibit OATP1B3 or NTCP. All drugs inhibited BCRP-mediated estrone 3-sulfate transport or OATP1B1-mediated estradiol 17β-D-glucuronide transport with the same rank order of inhibitory potency (lopinavir>ritonavir>atazanavir>>darunavir) and mean IC50 values ranging from 15.5 ± 2.80 μM to 143 ± 14.7 μM or 0.220 ± 0.0655 μM to 9.53 ± 2.50 μM, respectively. Atazanavir and lopinavir also inhibited OATP1B3- or NTCP-mediated transport with a mean IC50 of 1.86 ± 0.500 μM or 65.6 ± 10.7 μM and 5.04 ± 0.0950 μM or 20.3 ± 2.13 μM, respectively. Following integration of a combined hepatic transport component into the previous mechanistic static model using the in vitro inhibitory kinetic parameters determined above for atazanavir, the newly predicted rosuvastatin AUCR reconciled with the clinically observed AUCR confirming additional minor involvement of OATP1B3 and NTCP inhibition in its DDI. The predictions for the other protease inhibitors confirmed inhibition of intestinal BCRP and hepatic OATP1B1 as the principal pathways involved in their clinical DDI with rosuvastatin.

Machine Learning Models Identify New Inhibitors for Human OATP1B1

The uptake transporter OATP1B1 (SLC01B1) is largely localized to the sinusoidal membrane of hepatocytes and is a known victim of unwanted drug-drug interactions. Computational models are useful for identifying potential substrates and/or inhibitors of clinically relevant transporters. Our goal was to generate OATP1B1 in vitro inhibition data for [3H] estrone-3-sulfate (E3S) transport in CHO cells and use it to build machine learning models to facilitate a comparison of seven different classification models (Deep learning, Adaboosted decision trees, Bernoulli naïve bayes, k-nearest neighbors (knn), random forest, support vector classifier (SVC), logistic regression (lreg), and XGBoost (xgb)] using ECFP6 fingerprints to perform 5-fold, nested cross validation. In addition, we compared models using 3D pharmacophores, simple chemical descriptors alone or plus ECFP6, as well as ECFP4 and ECFP8 fingerprints. Several machine learning algorithms (SVC, lreg, xgb, and knn) had excellent nested cross validation statistics, particularly for accuracy, AUC, and specificity. An external test set containing 207 unique compounds not in the training set demonstrated that at every threshold SVC outperformed the other algorithms based on a rank normalized score. A prospective validation test set was chosen using prediction scores from the SVC models with ECFP fingerprints and were tested in vitro with 15 of 19 compounds (84% accuracy) predicted as active (≥20% inhibition) showed inhibition. Of these compounds, six (abamectin, asiaticoside, berbamine, doramectin, mobocertinib, and umbralisib) appear to be novel inhibitors of OATP1B1 not previously reported. These validated machine learning models can now be used to make predictions for drug-drug interactions for human OATP1B1 alongside other machine learning models for important drug transporters in our MegaTrans software.

Physiological Characterization of the Transporter-Mediated Uptake of the Reversible Male Contraceptive H2-Gamendazole Across the Blood-Testis Barrier

The blood-testis barrier (BTB) is formed by a tight network of Sertoli cells (SCs) to limit the movement of reproductive toxicants from the blood into the male genital tract. Transporters expressed at the basal membranes of SCs also influence the disposition of drugs across the BTB. The reversible, nonhormonal contraceptive, H2-gamendazole (H2-GMZ), is an indazole carboxylic acid analog that accumulates over 10 times more in the testes compared with other organs. However, the mechanism(s) by which H2-GMZ circumvents the BTB are unknown. This study describes the physiologic characteristics of the carrier-mediated process(es) that permit H2-GMZ and other analogs to penetrate SCs. Uptake studies were performed using an immortalized human SC line (hT-SerC) and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Uptake of H2-GMZ and four analogs followed Michaelis-Menten transport kinetics (one analog exhibited poor penetration). H2-GMZ uptake was strongly inhibited by indomethacin, diclofenac, MK-571, and several analogs. Moreover, H2-GMZ uptake was stimulated by an acidic extracellular pH, reduced at basic pHs, and independent of extracellular Na+, K+, or Cl- levels, which are intrinsic characteristics of OATP-mediated transport. Therefore, the characteristics of H2-GMZ transport suggest that one or more OATPs may be involved. However, endogenous transporter expression in wild-type Chinese hamster ovary (CHO), Madin-Darby canine kidney (MDCK), and human embryonic kidney-293 (HEK-293) cells limited the utility of heterologous transporter expression to identify a specific OATP transporter. Altogether, characterization of the transporters involved in the flux of H2-GMZ provides insight into the selectivity of drug disposition across the human BTB to understand and overcome the pharmacokinetic and pharmacodynamic difficulties presented by this barrier. SIGNIFICANCE STATEMENT: Despite major advancements in female contraceptives, male alternatives, including vasectomy, condom usage, and physical withdrawal, are antiquated and the widespread availability of nonhormonal, reversible chemical contraceptives is nonexistent. Indazole carboxylic acid analogs such as H2-GMZ are promising new reversible, antispermatogenic drugs that are highly effective in rodents. This study characterizes the carrier-mediated processes that permit H2-GMZ and other drugs to enter Sertoli cells and the observations made here will guide the development of drugs that effectively circumvent the BTB.

Use of selective substrates and inhibitors to rapidly characterise batches of cryopreserved primary human hepatocytes for assessment of active uptake liability in drug discovery and development

The use of hepatocytes to predict human hepatic metabolic clearance is the gold standard approach. However whilst enzymes are well characterised, knowledge gaps remain for transporters. Furthermore, methods to study specific transporter involvement are often complicated by overlapping substrate specificity. Selective substrates and inhibitors would aid investigations into clinically relevant pharmacokinetic effects. However, to date no consensus has been reached.This work defines selective hepatic uptake transporter substrates and inhibitors for the six main human hepatocyte transporters (OATP1B1, OATP1B3, OATP2B1, NTCP, OAT2 & OCT1), and demonstrates their use to rapidly characterise batches of human hepatocytes for uptake transporter activity. Hepatic uptake was determined across a range of substrate concentrations, allowing the definition of kinetic parameters and hence active and passive components. Systematic investigations identified a specific substrate and inhibitor for each transporter, with no overlap between the specificity of substrate and inhibitor for any given transporter.Early characterisation of compound interactions with uptake transporters will aid in early risk assessment and chemistry design. Hence, this work further highlights the feasibility of a refined methodology for rapid compound characterisation for the application of static and dynamic models, for early clinical risk assessment and guidance for the clinical development plan.

Computational studies reveal potential dolichyl-phosphate N-acetylglucosaminephosphotransferase inhibitors amidst existing drugs

Dolichyl-phosphate N-acetylglucosaminephosphotransferase (dpagt1) inhibition is reported to kill tumor cells whose growth progression requires increased branching of N-linked glycans. Available dpagt1 inhibitors are grossly limited and are faced with problems of heamolytic effect and aqueous solubility thereby necessitating the search for new, safe and effective dpagt1 inhibitors. We employed computational methods to screen a dataset of ∼1300 FDA approved drugs in order to obtain theoretical dpagt1 inhibitors which could be repurposed as chemotherapeutic drugs. Top six better performing drugs, binding affinity for dpagt1 at the range of -17.63 to -20.40 kcal/mol, than the reference ligand (tunicamycin; -14.86 kcal/mol) were obtained at the end of structure-based-pharmacophore- and virtual-screening and 'induced fit' docking calculations. Analysis of their binding poses identified essential pharmacophores involved in target-ligand complexation that could be targeted in chemical modification to develop more effective and safe dpagt1 inhibitors.Communicated by Ramaswamy H. Sarma.

Mechanistic Computational Models of Epithelial Cell Transporters-the Adorned Heroes of Pharmacokinetics

Epithelial membrane transporter kinetics portray an irrefutable role in solute transport in and out of cells. Mechanistic models are used to investigate the transport of solutes at the organ, tissue, cell or membrane scale. Here, we review the recent advancements in using computational models to investigate epithelial transport kinetics on the cell membrane. Various methods have been employed to develop transport phenomena models of solute flux across the epithelial cell membrane. Interestingly, we noted that many models used lumped parameters, such as the Michaelis-Menten kinetics, to simplify the transporter-mediated reaction term. Unfortunately, this assumption neglects transporter numbers or the fact that transport across the membrane may be affected by external cues. In contrast, more recent mechanistic transporter kinetics models account for the transporter number. By creating models closer to reality researchers can investigate the downstream effects of physical or chemical disturbances on the system. Evidently, there is a need to increase the complexity of mechanistic models investigating the solute flux across a membrane to gain more knowledge of transporter-solute interactions by assigning individual parameter values to the transporter kinetics and capturing their dependence on each other. This change results in better pharmacokinetic predictions in larger scale platforms. More reliable and efficient model predictions can be made by creating mechanistic computational models coupled with dedicated in vitro experiments. It is also vital to foster collaborative efforts among transporter kinetics researchers in the modeling, material science and biological fields.

Molecular Properties of Drugs Handled by Kidney OATs and Liver OATPs Revealed by Chemoinformatics and Machine Learning: Implications for Kidney and Liver Disease

In patients with liver or kidney disease, it is especially important to consider the routes of metabolism and elimination of small-molecule pharmaceuticals. Once in the blood, numerous drugs are taken up by the liver for metabolism and/or biliary elimination, or by the kidney for renal elimination. Many common drugs are organic anions. The major liver uptake transporters for organic anion drugs are organic anion transporter polypeptides (OATP1B1 or SLCO1B1; OATP1B3 or SLCO1B3), whereas in the kidney they are organic anion transporters (OAT1 or SLC22A6; OAT3 or SLC22A8). Since these particular OATPs are overwhelmingly found in the liver but not the kidney, and these OATs are overwhelmingly found in the kidney but not liver, it is possible to use chemoinformatics, machine learning (ML) and deep learning to analyze liver OATP-transported drugs versus kidney OAT-transported drugs. Our analysis of >30 quantitative physicochemical properties of OATP- and OAT-interacting drugs revealed eight properties that in combination, indicate a high propensity for interaction with "liver" transporters versus "kidney" ones based on machine learning (e.g., random forest, k-nearest neighbors) and deep-learning classification algorithms. Liver OATPs preferred drugs with greater hydrophobicity, higher complexity, and more ringed structures whereas kidney OATs preferred more polar drugs with more carboxyl groups. The results provide a strong molecular basis for tissue-specific targeting strategies, understanding drug-drug interactions as well as drug-metabolite interactions, and suggest a strategy for how drugs with comparable efficacy might be chosen in chronic liver or kidney disease (CKD) to minimize toxicity.

Is It Time to Use Modeling of Cellular Transporter Homeostasis to Inform Drug-Drug Interaction Studies: Theoretical Considerations

Mathematical modeling has been an important tool in pharmaceutical research for 50 + years and there is increased emphasis over the last decade on using modeling to improve the efficiency and effectiveness of drug development. In an earlier commentary, we applied a multiscale model linking 6 scales (whole body, tumor, vasculature, cell, spatial location, time), together with literature data on nanoparticle and tumor properties, to demonstrate the effects of nanoparticle particles on systemic disposition. The current commentary used a 4-scale model (cell membrane, intracellular organelles, spatial location, time) together with literature data on the intracellular processing of membrane receptors and transporters to demonstrate disruption of transporter homeostasis can lead to drug-drug interaction (DDI) between victim drug (VD) and perpetrator drug (PD), including changes in the area-under-concentration-time-curve of VD in cells that are considered significant by the US Food and Drug Administration (FDA). The model comprised 3 computational components: (a) intracellular transporter homeostasis, (b) pharmacokinetics of extracellular and intracellular VD/PD concentrations, and (c) pharmacodynamics of PD-induced stimulation or inhibition of an intracellular kinetic process. Model-based simulations showed that (a) among the five major endocytic processes, perturbation of transporter internalization or recycling led to the highest incidence and most extensive DDI, with minor DDI for perturbing transporter synthesis and early-to-late endosome and no DDI for perturbing transporter degradation and (b) three experimental conditions (spatial transporter distribution in cells, VD/PD co-incubation time, extracellular PD concentrations) were determinants of DDI detection. We propose modeling is a useful tool for hypothesis generation and for designing experiments to identify potential DDI; its application further aligns with the model-informed drug development paradigm advocated by FDA.

Data-Driven Ensemble Docking to Map Molecular Interactions of Steroid Analogs with Hepatic Organic Anion Transporting Polypeptides

Hepatic organic anion transporting polypeptides—OATP1B1, OATP1B3, and OATP2B1—are expressed at the basolateral membrane of hepatocytes, being responsible for the uptake of a wide range of natural substrates and structurally unrelated pharmaceuticals. Impaired function of hepatic OATPs has been linked to clinically relevant drug–drug interactions leading to altered pharmacokinetics of administered drugs. Therefore, understanding the commonalities and differences across the three transporters represents useful knowledge to guide the drug discovery process at an early stage. Unfortunately, such efforts remain challenging because of the lack of experimentally resolved protein structures for any member of the OATP family. In this study, we established a rigorous computational protocol to generate and validate structural models for hepatic OATPs. The multistep procedure is based on the systematic exploration of available protein structures with shared protein folding using normal-mode analysis, the calculation of multiple template backbones from elastic network models, the utilization of multiple template conformations to generate OATP structural models with various degrees of conformational flexibility, and the prioritization of models on the basis of enrichment docking. We employed the resulting OATP models of OATP1B1, OATP1B3, and OATP2B1 to elucidate binding modes of steroid analogs in the three transporters. Steroid conjugates have been recognized as endogenous substrates of these transporters. Thus, investigating this data set delivers insights into mechanisms of substrate recognition. In silico predictions were complemented with in vitro studies measuring the bioactivity of a compound set on OATP expressing cell lines. Important structural determinants conferring shared and distinct binding patterns of steroid analogs in the three transporters have been identified. Overall, this comparative study provides novel insights into hepatic OATP-ligand interactions and selectivity. Furthermore, the integrative computational workflow for structure-based modeling can be leveraged for other pharmaceutical targets of interest.

Assessment of Statin Interactions With the Human NTCP Transporter Using a Novel Fluorescence Assay

Sodium taurocholate cotransporting polypeptide (NTCP), which is highly expressed in the sinusoidal membrane of hepatocytes, maintains bile acid homeostasis and participates in the hepatic disposition of a variety of endogenous substances as well as xenobiotics. Manifested by the involvement of organic anion-transporting polypeptides 1B1 and 1B3 (OATP1B1 and OATP1B3) in the hepatic uptake of statin drugs, sinusoidal membrane transporters play an important role in the pharmacokinetics and pharmacodynamics of these agents. It has been speculated that NTCP may function as an alternative pathway for statin hepatic uptake, complementary to OATP1B1 and OATP1B3. In the current study, we produced stable NTCP-expressing human embryonic kidney 293 (HEK293) cells and developed a fluorescence-based assay using flow cytometry for measuring NTCP transport with chenodeoxycholyl-(Nε-7-nitrobenz-2-oxa-1,3-diazole)-lysine (CDCA-NBD) as the substrate. NTCP-mediated CDCA-NBD transport was time-dependent and exhibited typical Michaelis-Menten kinetics, with a K _m of 6.12 µM. Compounds known to interact with NTCP, including chenodeoxycholic acid and taurocholic acid, displayed concentration-dependent inhibition of NTCP-mediated CDCA-NBD transport. We report here a systematic evaluation of the interaction between statins and the NTCP transporter. Utilizing this system, several statins were either found to inhibit NTCP-dependent transport or act as substrates. We find a good correlation between the reported lipophilicity of statins and their ability to inhibit NTCP. The objective was to develop a higher-throughput system to evaluate potential inhibitors such as the statins. The in vitro assays using CDCA-NBD as fluorescent substrate are convenient, rapid, and have utility in screening drug candidates for potential drug-NTCP interactions.

A Tribute to Professor Per Artursson - Scientist, Explorer, Mentor, Innovator, and Giant in Pharmaceutical Research

This issue of the Journal of Pharmaceutical Sciences is dedicated to Professor Per Artursson and the groundbreaking contributions he has made and continues to make in the Pharmaceutical Sciences. Per is one of the most cited researchers in his field, with more than 30,000 citations and an h-index of 95 as of September 2020. Importantly, these citations are distributed over the numerous fields he has explored, clearly showing the high impact the research has had on the discipline. We provide a short portrait of Per, with emphasis on his personality, driving forces and the inspirational sources that shaped his career as a world-leading scientist in the field. He is a curious scientist who deftly moves between disciplines and has continued to innovate, expand boundaries, and profoundly impact the pharmaceutical sciences throughout his career. He has developed new tools and provided insights that have significantly contributed to today's molecular and mechanistic approaches to research in the fields of intestinal absorption, cellular disposition, and exposure-efficacy relationships of pharmaceutical drugs. We want to celebrate these important contributions in this special issue of the Journal of Pharmaceutical Sciences in Per's honor.

Targeting Protein Folding: A Novel Approach for the Treatment of Pathogenic Bacteria

Infectious diseases are a major cause of morbidity and mortality worldwide, exacerbated by increasing antibiotic resistance in many bacterial species. The development of drugs with new modes of action is essential. A leading strategy is antivirulence, with the aim to target bacterial proteins that are important in disease causation and progression but do not affect growth, resulting in reduced selective pressure for resistance. Immunophilins, a superfamily of peptidyl-prolyl cis-trans isomerase (PPIase) enzymes have been shown to be important for virulence in a broad-spectrum of pathogenic bacteria. This Perspective will provide an overview of the recent advances made in understanding the role of each immunophilin family, cyclophilins, FK506 binding proteins (FKBPs), and parvulins in bacteria. Inhibitor design and medicinal chemistry strategies for development of novel drugs against bacterial FKBPs will be discussed. Furthermore, drugs against human cyclophilins and parvulins will be reviewed in their current indication as antiviral and anticancer therapies.

An Informatics-based Approach to Identify Key Pharmacological Components in Drug-Drug Interactions

Drug-drug interactions (DDI) can cause severe adverse drug reactions and pose a major challenge to medication therapy. Recently, informatics-based approaches are emerging for DDI studies. In this paper, we aim to identify key pharmacological components in DDI based on large-scale data from DrugBank, a comprehensive DDI database. With pharmacological components as features, logistic regression is used to perform DDI classification with a focus on searching for most predictive features, a process of identifying key pharmacological components. Using univariate feature selection with chi-squared statistic as the ranking criteria, our study reveals that top 10% features can achieve comparable classification performance compared to that using all features. The top 10% features are identified to be key pharmacological components. Furthermore, their importance is quantified by feature coefficients in the classifier, which measures the DDI potential and provides a novel perspective to evaluate pharmacological components.

Acamprosate Is a Substrate of the Human Organic Anion Transporter (OAT) 1 without OAT3 Inhibitory Properties: Implications for Renal Acamprosate Secretion and Drug-Drug Interactions

Acamprosate is an anionic drug substance widely used in treating symptoms of alcohol withdrawal. It was recently shown that oral acamprosate absorption is likely due to paracellular transport. In contrast, little is known about the eliminating mechanism clearing acamprosate from the blood in the kidneys, despite the fact that studies have shown renal secretion of acamprosate. The hypothesis of the present study was therefore that renal organic anion transporters (OATs) facilitate the renal excretion of acamprosate in humans. The aim of the present study was to establish and apply OAT1 (gene product of SLC22A6) and OAT3 (gene product of SLC22A8) expressing cell lines to investigate whether acamprosate is a substrate or inhibitor of OAT1 and/or OAT3. The studies were performed in HEK293-Flp-In cells stably transfected with SLC22A6 or SLC22A8. Protein and functional data showed that the established cell lines are useful for studying OAT1- and OAT3-mediated transport in bi-laboratory studies. Acamprosate inhibited OAT1-mediated p-aminohippuric acid (PAH) uptake but did not inhibit substrate uptake via OAT3 expressing cells, neither when applied concomitantly nor after a 3 h preincubation with acamprosate. The uptake of PAH via OAT1 was inhibited in a competitive manner by acamprosate and cellular uptake studies showed that acamprosate is a substrate for OAT1 with a K_m-value of approximately 700 µM. Probenecid inhibited OAT1-mediated acamprosate uptake with a K_i-value of approximately 13 µM, which may translate into an estimated clinically significant DDI index. In conclusion, acamprosate was identified as a substrate of OAT1 but not OAT3.

Roles of Hepatic Drug Transporters in Drug Disposition and Liver Toxicity

Hepatic drug transporters are mainly distributed in parenchymal liver cells (hepatocytes), contributing to drug's liver disposition and elimination. According to their functions, hepatic transporters can be roughly divided into influx and efflux transporters, translocating specific molecules from blood into hepatic cytosol and mediating the excretion of drugs and metabolites from hepatic cytosol to blood or bile, respectively. The function of hepatic transport systems can be affected by interspecies differences and inter-individual variability (polymorphism). In addition, some drugs and disease can redistribute transporters from the cell surface to the intracellular compartments, leading to the changes in the expression and function of transporters. Hepatic drug transporters have been associated with the hepatic toxicity of drugs. Gene polymorphism of transporters and altered transporter expressions and functions due to diseases are found to be susceptible factors for drug-induced liver injury (DILI). In this chapter, the localization of hepatic drug transporters, their regulatory factors, physiological roles, and their roles in drug's liver disposition and DILI are reviewed.

Current Advances in Studying Clinically Relevant Transporters of the Solute Carrier (SLC) Family by Connecting Computational Modeling and Data Science

Organic anion and cation transporting proteins (OATs, OATPs, and OCTs), as well as the Multidrug and Toxin Extrusion (MATE) transporters of the Solute Carrier (SLC) family are playing a pivotal role in the discovery and development of new drugs due to their involvement in drug disposition, drug-drug interactions, adverse drug effects and related toxicity. Computational methods to understand and predict clinically relevant transporter interactions can provide useful guidance at early stages in drug discovery and design, especially if they include contemporary data science approaches. In this review, we summarize the current state-of-the-art of computational approaches for exploring ligand interactions and selectivity for these drug (uptake) transporters. The computational methods discussed here by highlighting interesting examples from the current literature are ranging from semiautomatic data mining and integration, to ligand-based methods (such as quantitative structure-activity relationships, and combinatorial pharmacophore modeling), and finally structure-based methods (such as comparative modeling, molecular docking, and molecular dynamics simulations). We are focusing on promising computational techniques such as fold-recognition methods, proteochemometric modeling or techniques for enhanced sampling of protein conformations used in the context of these ADMET-relevant SLC transporters with a special focus on methods useful for studying ligand selectivity.

Organic solute transporter OSTα/β is overexpressed in nonalcoholic steatohepatitis and modulated by drugs associated with liver injury

The heteromeric steroid transporter organic solute transporter α/β (OSTα/β, SLC51A/B) was discovered over a decade ago, but its physiological significance in the liver remains uncertain. A major challenge has been the lack of suitable models expressing OSTα/β. Based on observations first reported here that hepatic OSTα/β is upregulated in nonalcoholic steatohepatitis, the aim of this research was to develop an in vitro model to evaluate OSTα/β function and interaction with drugs and bile acids. OSTα/β expression in human liver tissue was analyzed by quantitative RT-PCR, Western blotting, and immunofluorescence. Radiolabeled compounds were used to determine OSTα/β-mediated transport in the established in vitro model. The effect of bile acids and drugs, including those associated with cholestatic drug-induced liver injury, on OSTα/β-mediated transport was evaluated. Expression of OSTα/β was elevated in the liver of patients with nonalcoholic steatohepatitis and primary biliary cholangitis, whereas hepatocyte expression of OSTα/β was low in control liver tissue. Studies in the novel cell-based system showed rapid and linear OSTα/β-mediated transport for all tested compounds: dehydroepiandrosterone sulfate, digoxin, estrone sulfate, and taurocholate. The interaction study with 26 compounds revealed novel OSTα/β inhibitors: a biomarker for cholestasis, glycochenodeoxycholic acid; the major metabolite of troglitazone, troglitazone sulfate; and a macrocyclic antibiotic, fidaxomicin. Additionally, some drugs (e.g., digoxin) consistently stimulated taurocholate uptake in OSTα/β-overexpressing cells. Our findings demonstrate that OSTα/β is an important transporter in liver disease and imply a role for this transporter in bile acid-bile acid and drug-bile acid interactions, as well as cholestatic drug-induced liver injury. NEW & NOTEWORTHY The organic solute transporter OSTα/β is highly expressed in hepatocytes of liver tissue obtained from patients with nonalcoholic steatohepatitis and primary biliary cholangitis. OSTα/β substrates exhibit rapid, linear, and concentration-driven transport in an OSTα/β-overexpressing cell line. Drugs associated with hepatotoxicity modulate OSTα/β-mediated taurocholate transport. These data suggest that hepatic OSTα/β plays an essential role in patients with cholestasis and may have important clinical implications for bile acid and drug disposition.

Drug interactions of meglitinide antidiabetics involving CYP enzymes and OATP1B1 transporter

Meglitinides such as repaglinide and nateglinide are useful to treat type 2 diabetes patients who follow a flexible lifestyle. They are short-acting insulin secretagogues and are associated with less risk of hypoglycemia, weight gain and chronic hyperinsulinemia compared with sulfonylureas. Meglitinides are the substrates of cytochrome P450 (CYP) enzymes and organic anion transporting polypeptide 1B1 (OATP1B1 transporter) and the coadministration of the drugs affecting them will result in pharmacokinetic drug interactions. This article focuses on the drug interactions of meglitinides involving CYP enzymes and OATP1B1 transporter. To prevent the risk of hypoglycemic episodes, prescribers and pharmacists must be aware of the adverse drug interactions of meglitinides.

Hepatobiliary Clearance Prediction: Species Scaling From Monkey, Dog, and Rat, and In Vitro-In Vivo Extrapolation of Sandwich-Cultured Human Hepatocytes Using 17 Drugs

Hepatobiliary elimination can be a major clearance pathway dictating the pharmacokinetics of drugs. Here, we first compared the dose eliminated in bile in preclinical species (monkey, dog, and rat) with that in human and further evaluated single-species scaling (SSS) to predict human hepatobiliary clearance. Six compounds dosed in bile duct-cannulated (BDC) monkeys showed biliary excretion comparable to human; and the SSS of hepatobiliary clearance with plasma fraction unbound correction yielded reasonable predictions (within 3-fold). Although dog SSS also showed reasonable predictions, rat overpredicted hepatobiliary clearance for 13 of 24 compounds. Second, we evaluated the translatability of in vitro sandwich-cultured human hepatocytes (SCHHs) to predict human hepatobiliary clearance for 17 drugs. For drugs with no significant active uptake in SCHH studies (i.e., with or without rifamycin SV), measured intrinsic biliary clearance was directly scalable with good predictability (absolute average fold error [AAFE] = 1.6). Drugs showing significant active uptake in SCHH, however, showed improved predictability when scaled based on extended clearance term (AAFE = 2.0), which incorporated sinusoidal uptake along with a global scaling factor for active uptake and the canalicular efflux clearance. In conclusion, SCHH is a useful tool to predict human hepatobiliary clearance, whereas BDC monkey model may provide further confidence in the prospective predictions.

Investigating Transporter-Mediated Drug-Drug Interactions Using a Physiologically Based Pharmacokinetic Model of Rosuvastatin

Rosuvastatin is a frequently used probe in transporter-mediated drug-drug interaction (DDI) studies. This report describes the development of a physiologically based pharmacokinetic (PBPK) model of rosuvastatin for prediction of pharmacokinetic (PK) DDIs. The rosuvastatin model predicted the observed single (i.v. and oral) and multiple dose PK profiles, as well as the impact of coadministration with transporter inhibitors. The predicted effects of rifampin and cyclosporine (6.58-fold and 5.07-fold increase in rosuvastatin area under the curve (AUC), respectively) were mediated primarily via inhibition of hepatic organic anion-transporting polypeptide (OATP)1B1 (Inhibition constant (K_i ) ∼1.1 and 0.014 µM, respectively) and OATP1B3 (K_i ∼0.3 and 0.007 µM, respectively), with cyclosporine also inhibiting intestinal breast cancer resistance protein (BCRP; K_i ∼0.07 µM). The predicted effects of gemfibrozil and its metabolite were moderate (1.88-fold increase in rosuvastatin AUC) and mediated primarily via inhibition of hepatic OATP1B1 and renal organic cation transporter 3. This model of rosuvastatin will be useful in prospectively predicting transporter-mediated DDIs with novel pharmaceutical agents in development.

Intracellular drug bioavailability: a new predictor of system dependent drug disposition

Intracellular drug exposure is influenced by cell- and tissue-dependent expression of drug-transporting proteins and metabolizing enzymes. Here, we introduce the concept of intracellular bioavailability (F_ic) as the fraction of extracellular drug available to bind intracellular targets, and we assess how F_ic is affected by cellular drug disposition processes. We first investigated the impact of two essential drug transporters separately, one influx transporter (OATP1B1; SLCO1B1) and one efflux transporter (P-gp; ABCB1), in cells overexpressing these proteins. We showed that OATP1B1 increased F_ic of its substrates, while P-gp decreased F_ic. We then investigated the impact of the concerted action of multiple transporters and metabolizing enzymes in freshly-isolated human hepatocytes in culture configurations with different levels of expression and activity of these proteins. We observed that F_ic was up to 35-fold lower in the configuration with high expression of drug-eliminating transporters and enzymes. We conclude that F_ic provides a measurement of the net impact of all cellular drug disposition processes on intracellular bioavailable drug levels. Importantly, no prior knowledge of the involved drug distribution pathways is required, allowing for high-throughput determination of drug access to intracellular targets in highly defined cell systems (e.g., single-transporter transfectants) or in complex ones (including primary human cells).

Linking organic anion transporting polypeptide 1B1 and 1B3 (OATP1B1 and OATP1B3) interaction profiles to hepatotoxicity - The hyperbilirubinemia use case

Hyperbilirubinemia is a pathological condition of excessive accumulation of conjugated or unconjugated bilirubin in blood. It has been associated with neurotoxicity and non-neural organ dysfunctions, while it can also be a warning of liver side effects. Hyperbilirubinemia can either be a result of overproduction of bilirubin due to hemolysis or dyserythropoiesis, or the outcome of impaired bilirubin elimination due to liver transporter malfunction or inhibition. There are several reports in literature that inhibition of organic anion transporting polypeptides 1B1 and 1B3 (OATP1B1 and OATP1B3) might lead to hyperbilirubinemia. In this study we created a set of classification models for hyperbilirubinemia, which, besides physicochemical descriptors, also include the output of classification models of human OATP1B1 and 1B3 inhibition. Models were based on either human data derived from public toxicity reports or animal data extracted from the eTOX database VITIC. The generated models showed satisfactory accuracy (68%) and area under the curve (AUC) for human data and 71% accuracy and 70% AUC for animal data. However, our results did not indicate strong association between OATP inhibition and hyperbilirubinemia, neither for humans nor for animals.

Organic Anion Transporter 2: An Enigmatic Human Solute Carrier

As a member of the solute carrier 22A (SLC22A) family, organic anion transporter 2 (OAT2; SLC22A7) is emerging as an important drug transporter because of its expression in both the liver and kidney, two major eliminating organs, and its ability to transport not only a wide variety of xenobiotics but also numerous physiologically important endogenous compounds, like creatinine and cGMP. However, OAT2 has received relatively little attention compared with other OATs and solute carriers (SLCs), like organic cation transporters, sodium-dependent taurocholate cotransporting polypeptide, multidrug and toxin extrusion proteins, and organic anion-transporting polypeptides. Overall, the literature describing OAT2 is rapidly evolving, with numerous publications contradicting each other regarding the transport mechanism, tissue distribution, and transport of creatinine and cGMP, two important endogenous OAT2 substrates. Despite its status as a liver and kidney SLC, tools for assessing its activity and inhibition are lacking, and its role in drug disposition and elimination remains to be defined. The current review focuses on the available and emerging literature describing OAT2. We envision that OAT2 will gain more prominence as its expression, substrate, and inhibitor profile is investigated further and compared with other SLCs.

The role of organic anion transporting polypeptides in drug absorption, distribution, excretion and drug-drug interactions

INTRODUCTION

The in vivo fate and effectiveness of a drug depends highly on its absorption, distribution, metabolism, excretion and toxicity (ADME-Tox). Organic anion transporting polypeptides (OATPs) are membrane proteins involved in the cellular uptake of various organic compounds, including clinically used drugs. Since OATPs are significant players in drug absorption and distribution, modulation of OATP function via pharmacotherapy with OATP substrates/inhibitors, or modulation of their expression, affects drug pharmacokinetics. Given their cancer-specific expression, OATPs may also be considered anticancer drug targets. Areas covered: We describe the human OATP family, discussing clinically relevant consequences of altered OATP function. We offer a critical analysis of published data on the role of OATPs in ADME and in drug-drug interactions, especially focusing on OATP1A2, 1B1, 1B3 and 2B1. Expert opinion: Four members of the OATP family, 1A2, 1B1, 1B3 and 2B1, have been characterized in detail. As biochemical and pharmacological knowledge on the other OATPs is lacking, it seems timely to direct research efforts towards developing the experimental framework needed to investigate the transport mechanism and substrate specificity of the poorly described OATPs. In addition, elucidating the role of OATPs in tumor development and therapy response are critical avenues for further research.

Clustering drug-drug interaction networks with energy model layouts: community analysis and drug repurposing

Analyzing drug-drug interactions may unravel previously unknown drug action patterns, leading to the development of new drug discovery tools. We present a new approach to analyzing drug-drug interaction networks, based on clustering and topological community detection techniques that are specific to complex network science. Our methodology uncovers functional drug categories along with the intricate relationships between them. Using modularity-based and energy-model layout community detection algorithms, we link the network clusters to 9 relevant pharmacological properties. Out of the 1141 drugs from the DrugBank 4.1 database, our extensive literature survey and cross-checking with other databases such as Drugs.com, RxList, and DrugBank 4.3 confirm the predicted properties for 85% of the drugs. As such, we argue that network analysis offers a high-level grasp on a wide area of pharmacological aspects, indicating possible unaccounted interactions and missing pharmacological properties that can lead to drug repositioning for the 15% drugs which seem to be inconsistent with the predicted property. Also, by using network centralities, we can rank drugs according to their interaction potential for both simple and complex multi-pathology therapies. Moreover, our clustering approach can be extended for applications such as analyzing drug-target interactions or phenotyping patients in personalized medicine applications.

Role of gemfibrozil as an inhibitor of CYP2C8 and membrane transporters

INTRODUCTION

Cytochrome P450 (CYP) 2C8 is a drug metabolizing enzyme of major importance. The lipid-lowering drug gemfibrozil has been identified as a strong inhibitor of CYP2C8 in vivo. This effect is due to mechanism-based inhibition of CYP2C8 by gemfibrozil 1-O-β-glucuronide. In vivo, gemfibrozil is a fairly selective CYP2C8 inhibitor, which lacks significant inhibitory effect on other CYP enzymes. Gemfibrozil can, however, have a smaller but clinically meaningful inhibitory effect on membrane transporters, such as organic anion transporting polypeptide 1B1 and organic anion transporter 3. Areas covered: This review describes the inhibitory effects of gemfibrozil on CYP enzymes and membrane transporters. The clinical drug interactions caused by gemfibrozil and the different mechanisms contributing to the interactions are reviewed in detail. Expert opinion: Gemfibrozil is a useful probe inhibitor of CYP2C8 in vivo, but its effect on membrane transporters has to be taken into account in study design and interpretation. Moreover, gemfibrozil could be used to boost the pharmacokinetics of CYP2C8 substrate drugs. Identification of gemfibrozil 1-O-β-glucuronide as a potent mechanism-based inhibitor of CYP2C8 has led to recognition of glucuronide metabolites as perpetrators of drug-drug interactions. Recently, also acyl glucuronide metabolites of clopidogrel and deleobuvir have been shown to strongly inhibit CYP2C8.

Development of a high-throughput mass spectrometry based analytical method to support an in vitro OATP1B1 inhibition screening assay

RATIONALE

It is well known that the organic anion transporting polypeptide 1B1 (OATP1B1) plays a major role in the hepatic uptake of a range of drugs. To this end, it is pivotal that the potential for new molecular entities (NMEs) to inhibit OATP1B1 activity be assessed during early drug discovery. The work reported herein describes the development of a high-throughput analytical method to measure the clinically relevant probe substrate, pitavastatin, for the in vitro assessment of OATP1B1 inhibition.

METHODS

Development of an analytical method capable of very fast throughput was crucial for the success of this assay and was accomplished using a system which combines direct, on-line solid-phase extraction (SPE) with highly sensitive, label-free tandem mass spectrometry (MS/MS)-based detection. Mass spectrometry analysis of pitavastatin, along with the stable isotopically labeled internal standard d5-pitavastatin, was conducted using positive electrospray ionization (ESI) in selected reaction monitoring (SRM) mode.

RESULTS

The on-line SPE-MS/MS platform demonstrated similar sensitivity, selectivity, reproducibility, linearity and robustness to existing methodologies while achieving analytical cycle times of 10.4 seconds per well. Sensitivity exceeded what was necessary for our assay conditions, with a determined lower limit of quantification (LLOQ) for pitavastatin of 10 pM (picomolar) in assay matrix. Furthermore, the potency of multiple reference compounds was shown to be within 2-fold of IC50 values generated from liquid chromatography (LC)/MS/MS-based literature values.

CONCLUSIONS

A very fast and robust analytical method was successfully developed for the measurement of the clinically relevant OATP1B1 substrate, pitavastatin. The successful development and implementation of this very important early liability screen has helped to facilitate judicious lead candidate progression and will ultimately help build a greater understanding of OATP1B1-NME interactions, in general. Copyright © 2016 John Wiley & Sons, Ltd.

Effect of OATP-binding on the prediction of biliary excretion

1. Biliary excretion of compounds is dependant on several transporter proteins for the active uptake of compounds from the blood into the hepatocytes. Organic anion-transporting polypeptides (OATPs) are some of the most abundant transporter proteins in the sinusoidal membrane and have been shown to have substrate specificity similar to the structural characteristics of cholephilic compounds. 2. In this study, we sought to use measures of OATP binding as predictors of biliary excretion in conjunction with molecular descriptors in a quantitative structure-activity relationship (QSAR) study. Percentage inhibitions of three subtypes of OATPs were used as surrogate indicators of OATP substrates. Several statistical modelling techniques were incorporated including classification and regression trees, boosted trees, random forest and multivariate adaptive regression splines (MARS) in order to first develop QSARs for the prediction of OATP inhibition of compounds. The predicted OATP percentage inhibition using selected models were then used as features of the QSAR models for the prediction of biliary excretion of compounds in rat. 3. The results indicated that incorporation of predicted OATP inhibition improves accuracy of biliary excretion models. The best result was obtained from a simple regression tree that used predicted OATP1B1 percentage inhibition at the root node of the tree.

Oligonucleotide-based theranostic nanoparticles in cancer therapy

Theranostic approaches, combining the functionality of both therapy and imaging, have shown potential in cancer nanomedicine. Oligonucleotides such as small interfering RNA and microRNA, which are powerful therapeutic agents, have been effectively employed in theranostic systems against various cancers. Nanoparticles are used to deliver oligonucleotides into tumors by passive or active targeting while protecting the oligonucleotides from nucleases in the extracellular environment. The use of quantum dots, iron oxide nanoparticles and gold nanoparticles and tagging with contrast agents, like fluorescent dyes, optical or magnetic agents and various radioisotopes, has facilitated early detection of tumors and evaluation of therapeutic efficacy. In this article, we review the advantages of theranostic applications in cancer therapy and imaging, with special attention to oligonucleotide-based therapeutics.

Disruption of BSEP Function in HepaRG Cells Alters Bile Acid Disposition and Is a Susceptive Factor to Drug-Induced Cholestatic Injury

In the present study, we characterized in vitro biosynthesis and disposition of bile acids (BAs) as well as hepatic transporter expression followed by ABCB11 (BSEP) gene knockout in HepaRG cells (HepaRG-KO cells). BSEP KO in HepaRG cells led to time-dependent BA accumulation, resulting in reduced biosynthesis of BAs and altered BA disposition. In HepaRG-KO cells, the expression of NTCP, OATP1B1, OATP2B1, BCRP, P-gp, and MRP2 were reduced, whereas MRP3 and OCT1 were up-regulated. As a result, BSEP KO altered the disposition of BAs and subsequently underwent adaptive regulations of BA synthesis and homeostasis to enable healthy growth of the cells. Although BSEP inhibitors caused no or slight increase of BAs in HepaRG wild type cells (HepaRG-WT cells), excessive intracellular accumulation of BAs was observed in HepaRG-KO cells exposed to bosentan and troglitazone, but not dipyridamole. LDH release in the medium was remarkably increased in HepaRG-KO cultures exposed to troglitazone (50 μM), suggesting drug-induced cellular injury. The results revealed that functional impairment of BSEP predisposes the cells to altered BA disposition and is a susceptive factor to drug-induced cholestatic injury. In total, BSEP inhibition might trigger the processes but is not a sole determinant of cholestatic cellular injury. As intracellular BA accumulation is determined by BSEP function and the subsequent adaptive gene regulation, assessment of intracellular BA accumulation in HepaRG-KO cells could be a useful approach to evaluate drug-induced liver injury (DILI) potentials of drugs that could disrupt other BA homeostasis pathways beyond BSEP inhibition.