Evaluation of 14 PFAS for permeability and organic anion transporter interactions: Implications for renal clearance in humans

Per- and polyfluoroalkyl substances (PFAS) encompass a diverse group of synthetic fluorinated chemicals known to elicit adverse health effects in animals and humans. However, only a few studies investigated the mechanisms underlying clearance of PFAS. Herein, the relevance of human renal transporters and permeability to clearance and bioaccumulation for 14 PFAS containing three to eleven perfluorinated carbon atoms (ηpfc = 3-11) and several functional head-groups was investigated. Apparent permeabilities and interactions with human transporters were measured using in vitro cell-based assays, including the MDCK-LE cell line, and HEK293 stable transfected cell lines expressing organic anion transporter (OAT) 1-4 and organic cation transporter (OCT) 2. The results generated align with the Extended Clearance Classification System (ECCS), affirming that permeability, molecular weight, and ionization serve as robust predictors of clearance and renal transporter engagement. Notably, PFAS with low permeability (ECCS 3A and 3B) exhibited substantial substrate activity for OAT1 and OAT3, indicative of active renal secretion. Furthermore, we highlight the potential contribution of OAT4-mediated reabsorption to the renal clearance of PFAS with short ηpfc, such as perfluorohexane sulfonate (PFHxS). Our data advance our mechanistic understanding of renal clearance of PFAS in humans, provide useful input parameters for toxicokinetic models, and have broad implications for toxicological evaluation and regulatory considerations.

hERG, Plasmodium Life Cycle, and Cross Resistance Profiling of New Azabenzimidazole Analogues of Astemizole

Toward addressing the cardiotoxicity liability associated with the antimalarial drug astemizole (AST, hERG IC50 = 0.0042 μM) and its derivatives, we designed and synthesized analogues based on compound 1 (Pf NF54 IC50 = 0.012 μM; hERG IC50 = 0.63 μM), our previously identified 3-trifluoromethyl-1,2,4-oxadiazole AST analogue. Compound 11 retained in vitro multistage antiplasmodium activity (ABS PfNF54 IC50 = 0.017 μM; gametocytes PfiGc/PfLGc IC50 = 1.24/1.39 μM, and liver-stage PbHepG2 IC50 = 2.30 μM), good microsomal metabolic stability (MLM CLint < 11 μL·min-1·mg-1, EH < 0.33), and solubility (150 μM). It shows a ∼6-fold and >6000-fold higher selectivity against human ether-á-go-go-related gene higher selectively potential over hERG relative to 1 and AST, respectively. Despite the excellent in vitro antiplasmodium activity profile, in vivo efficacy in the Plasmodium berghei mouse infection model was diminished, attributable to suboptimal oral bioavailability (F = 14.9%) at 10 mg·kg-1 resulting from poor permeability (log D7.4 = -0.82). No cross-resistance was observed against 44 common Pf mutant lines, suggesting activity via a novel mechanism of action.

Plasma Protein Binding Refinement of the Extended Clearance Classification System: Subclasses for Predicting Hepatic Uptake or Renal Clearance for Classes 1B and 3B

BACKGROUND AND OBJECTIVES

The Extended Clearance Classification System (ECCS) was established to facilitate the timely anticipation of clearance rate determination according to the physicochemical characteristics of a given compound and in vitro passive membrane permeability. Unfortunately, distinguishing between renal and hepatic uptake clearance mechanisms using ECCS class 3B is not possible. We determined the effects of plasma protein binding (PPB) on major hepatic organic anion transporting polypeptide (OATP) and renal organic anion transporter (OAT) substrates. A modified ECCS could predict when renal or hepatic uptake mechanisms were the main clearance rate determinants (accounting for ≥ 70% of total clearance).

METHODS

A dataset of 66 human OATP and 41 OAT substrates was analyzed to determine the effect of PPB. A total of 63 acidic and zwitterionic, and high-molecular-weight (MW > 400 Da) compounds, including 50 drugs in ECCS classes 1B and 3B, were reanalyzed considering their PPB.

RESULTS

Statistical analyses revealed that hepatic uptake transporter (OATP1B1 and OATP1B3) substrates possess a high PPB rate of ≥ 90%, whereas OAT1 and/or OAT3 substrates possess low PPB rates of < 90%. By analyzing the 63 drugs on the basis of their PPB, the active hepatic uptakes of acids and zwitterions were determined to be the main clearance mechanisms, with PPB ≥ 90%, whereas renally eliminated drugs exhibited limited PPB (< 90%).

CONCLUSIONS

Therefore, PPB is an effective parameter for defining clearance rate determination for acidic and zwitterionic drugs with high MWs. Using PPB as an additional parameter in ECCS, clearance mechanisms for class 1B and 3B compounds can be predicted, and OATP and OAT substrates may be readily distinguished.

First-in-human study to investigate the safety and pharmacokinetics of salvianolic acid A and pharmacokinetic simulation using a physiologically based pharmacokinetic model

Salvianolic acid A (SAA) is a water-soluble phenolic acid component from Salvia miltiorrhiza Bunge currently under development for myocardial protection treatment for coronary heart disease (CHD). We investigated the safety, tolerability, and pharmacokinetics of single and multiple ascending doses of SAA. Additionally, a physiologically based pharmacokinetic (PBPK) model was developed to simulate the pharmacokinetics of SAA. This was a first-in-human (FIH), randomized, double-blind, placebo-controlled, single, and multiple-dose study in 116 healthy Chinese subjects with the range of 10-300 mg and 60-200 mg SAA, respectively. SAA was well tolerated at all dose levels, following both single and multiple doses, with a low overall incidence of treatment-emergent adverse events (TEAEs) which appeared to be no dose-related. The main pharmacokinetic parameter of SAA, assessed by the power model, was the lack of proportionality with the dose range after single dosing. The 90% CIs of the slope β of Cmax (1.214 [1.150-1.278]) and AUC0-t (1.222 [1.156-1.288]) were not within the predefined acceptance range, and the direction of the deviation was higher than expected. PBPK modeling suggested the transfer ability saturation of hepatic organic anion-transporting polypeptide 1B1 (OATP1B1) and P-glycoprotein (P-gp) might result in a relatively low distribution rate at higher doses. Clinical plasma concentrations observed were in good agreement with PBPK prediction. SAA showed well-characterized pharmacokinetics and was generally well tolerated in the dose range investigated. The PBPK model provides valuable pharmacokinetic knowledge for further clinical development.

Trends in small molecule drug properties: A developability molecule assessment perspective

Developability molecule assessment is a key interfacial capability across the biopharmaceutical industry, screening and staging molecules discovered by medicinal chemists for successful chemistry manufacturing controls (CMC) development and launch. The breadth of responsibility and expertise such teams possess puts them in a unique position to understand the impact of the physicochemical properties of a drug during its initial discovery and subsequent development. However, most of the publications describing trends in physicochemical properties are written from a medicinal chemistry perspective with the aim to identify molecules with better ADMET profiles that are either lead-like or drug-like, failing to describe the impact these properties have on CMC development. To systematically uncover knowledge obtained from recent trends in physicochemical properties and the corresponding impact on CMC development, a comprehensive analysis was conducted on molecules in the drug repurposing hub dataset. The only physicochemical property that seems to have been preserved in FDA-approved oral molecules over the decades (1900-2020) is a constant H-bond donor count, highlighting the importance this property has on cell permeability and lattice energy. Pharmaceutical attrition analysis suggests that partition-distribution coefficient, H-bond acceptors, polar surface area and the fraction of sp³ carbons are properties that are associated with compound attrition. Looking at pharmaceutical attrition asynchronously with the temporal analysis of FDA-approved oral molecules highlights the opposing trends, risks and diminishing effects some of these physiochemical properties (cLogP, cLogD and Fsp3) have on describing compound attrition during the past decade. Trellising the dataset by target class suggests that certain formulation and drug delivery strategies can be anticipated or put into place based on target class of a molecule. For example, molecules binding to nuclear hormone receptors are amenable to lipid-based drug delivery systems with proven commercial success. Although the poor solubility of kinase inhibitors is a combination of hydrophobicity (due to aromaticity) required to bind to its target and high lattice energy (melting point), they are a challenging target class to formulate. The influence of drug targets on physicochemical properties and the temporal nature of these properties is highlighted when comparing molecules in the drug repurposing dataset to those developed at Amgen. An improved understanding of the impact of molecular properties on performance attributes can accelerate decisions and facilitate risk assessments during candidate selection and development.

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.

Identification and Strategies to Mitigate High Total Clearance of Benzylamine-Substituted Biphenyl Ring Systems

For most oral small-molecule projects within drug discovery, the extent and duration of the effect are influenced by the total clearance of the compound; hence, designing compounds with low clearance remains a key focus to help enable sufficient protein target engagement. Comprehensive understanding and accurate prediction of animal clearance and pharmacokinetics provides confidence that the same can be observed for human. During a MERTK inhibitor lead optimization project, a series containing a biphenyl ring system with benzylamine meta-substitution on one phenyl and nitrogen inclusion as the meta atom on the other ring demonstrated multiple routes of compound elimination in rats. Here, we describe the identification of a structural pharmacophore involving two key interactions observed for both the MERTK program and an additional internal project. Four strategies to mitigate these clearance liabilities were identified and systematically investigated. We provide evidence that disruption of at least one of the interactions led to a significant reduction in CL that was subsequently predicted from rat hepatocytes using in vitro/in vivo extrapolation and the well-stirred scaling method. These tactics will likely be of general utility to the medicinal chemistry and DMPK community during compound optimization when similar issues are encountered for biphenyl benzylamines.

Oxadiazepinone HBV capsid assembly modulators

The HBV core protein serves multiple essential functions in the viral life cycle that enable chronic HBV infection to persist, and as such, represents a promising drug target. Modulation of the HBV capsid assembly has shown efficacy in early clinical trials through use of small molecule capsid assembly modulators (CAMs). Herein is described the evolution and SAR of a novel pyrazolo piperidine lead series into advanced oxadiazepinone HBV CAMs.

1,3-Diarylpyrazolyl-acylsulfonamides as Potent Anti-tuberculosis Agents Targeting Cell Wall Biosynthesis in Mycobacterium tuberculosis

Phenotypic whole cell high-throughput screening of a ∼150,000 diverse set of compounds against Mycobacterium tuberculosis (Mtb) in cholesterol-containing media identified 1,3-diarylpyrazolyl-acylsulfonamide 1 as a moderately active hit. Structure-activity relationship (SAR) studies demonstrated a clear scope to improve whole cell potency to MIC values of <0.5 μM, and a plausible pharmacophore model was developed to describe the chemical space of active compounds. Compounds are bactericidal in vitro against replicating Mtb and retained activity against multidrug-resistant clinical isolates. Initial biology triage assays indicated cell wall biosynthesis as a plausible mode-of-action for the series. However, no cross-resistance with known cell wall targets such as MmpL3, DprE1, InhA, and EthA was detected, suggesting a potentially novel mode-of-action or inhibition. The in vitro and in vivo drug metabolism and pharmacokinetics profiles of several active compounds from the series were established leading to the identification of a compound for in vivo efficacy proof-of-concept studies.

Examination of Urinary Excretion of Unchanged Drug in Humans and Preclinical Animal Models: Increasing the Predictability of Poor Metabolism in Humans

PURPOSE

A dataset of fraction excreted unchanged in the urine (fe) values was developed and used to evaluate the ability of preclinical animal species to predict high urinary excretion, and corresponding poor metabolism, in humans.

METHODS

A literature review of fe values in rats, dogs, and monkeys was conducted for all Biopharmaceutics Drug Disposition Classification System (BDDCS) Class 3 and 4 drugs (n=352) and a set of Class 1 and 2 drugs (n=80). The final dataset consisted of 202 total fe values for 135 unique drugs. Human and animal data were compared through correlations, two-fold analysis, and binary classifications of high (fe ≥30%) versus low (<30%) urinary excretion in humans. Receiver Operating Characteristic curves were plotted to optimize animal fe thresholds.

RESULTS

Significant correlations were found between fe values for each animal species and human fe (p<0.05). Sixty-five percent of all fe values were within two-fold of human fe with animals more likely to underpredict human urinary excretion as opposed to overpredict. Dogs were the most reliable predictors of human fe of the three animal species examined with 72% of fe values within two-fold of human fe and the greatest accuracy in predicting human fe ≥30%. ROC determined thresholds of ≥25% in rats, ≥19% in dogs, and ≥10% in monkeys had improved accuracies in predicting human fe of ≥30%.

CONCLUSIONS

Drugs with high urinary excretion in animals are likely to have high urinary excretion in humans. Animal models tend to underpredict the urinary excretion of unchanged drug in humans.

Intestinal Excretion, Intestinal Recirculation, and Renal Tubule Reabsorption Are Underappreciated Mechanisms That Drive the Distribution and Pharmacokinetic Behavior of Small Molecule Drugs

Drug reabsorption following biliary excretion is well-known as enterohepatic recirculation (EHR). Renal tubular reabsorption (RTR) following renal excretion is also common but not easily assessed. Intestinal excretion (IE) and enteroenteric recirculation (EER) have not been recognized as common disposition mechanisms for metabolically stable and permeable drugs. IE and intestinal reabsorption (IR:EHR/EER), as well as RTR, are governed by dug concentration gradients, passive diffusion, active transport, and metabolism, and together they markedly impact disposition and pharmacokinetics (PK) of small molecule drugs. Disruption of IE, IR, or RTR through applications of active charcoal (AC), transporter knockout (KO), and transporter inhibitors can lead to changes in PK parameters. The impacts of intestinal and renal reabsorption on PK are under-appreciated. Although IE and EER/RTR can be an intrinsic drug property, there is no apparent strategy to optimize compounds based on this property. This review seeks to improve understanding and applications of IE, IR, and RTR mechanisms.

Antimalarial Benzimidazole Derivatives Incorporating Phenolic Mannich Base Side Chains Inhibit Microtubule and Hemozoin Formation: Structure-Activity Relationship and In Vivo Oral Efficacy Studies

A novel series of antimalarial benzimidazole derivatives incorporating phenolic Mannich base side chains at the C2 position, which possess dual asexual blood and sexual stage activities, is presented. Structure-activity relationship studies revealed that the 1-benzylbenzimidazole analogues possessed submicromolar asexual blood and sexual stage activities in contrast to the 1H-benzimidazole analogues, which were only active against asexual blood stage (ABS) parasites. Further, the former demonstrated microtubule inhibitory activity in ABS parasites but more significantly in stage II/III gametocytes. In addition to being bona fide inhibitors of hemozoin formation, the 1H-benzimidazole analogues also showed inhibitory effects on microtubules. In vivo efficacy studies in Plasmodium berghei-infected mice revealed that the frontrunner compound 41 exhibited high efficacy (98% reduction in parasitemia) when dosed orally at 4 × 50 mg/kg. Generally, the compounds were noncytotoxic to mammalian cells.

Novel testing strategy for prediction of rat biliary excretion of intravenously administered estradiol-17β glucuronide

The aim of the present study was to develop a generic rat physiologically based kinetic (PBK) model that includes a novel testing strategy where active biliary excretion is incorporated using estradiol-17β glucuronide (E217βG) as the model substance. A major challenge was the definition of the scaling factor for the in vitro to in vivo conversion of the PBK-model parameter Vmax. In vitro values for the Vmax and Km for transport of E217βG were found in the literature in four different studies based on experiments with primary rat hepatocytes. The required scaling factor was defined based on fitting the PBK model-based predicted values to reported experimental data on E217βG blood levels and cumulative biliary E217βG excretion. This resulted in a scaling factor of 129 mg protein/g liver. With this scaling factor the PBK model predicted the in vivo data for blood and cumulative biliary E217βG levels with on average of less than 1.8-fold deviation. The study provides a proof of principle on how biliary excretion can be included in a generic PBK model using primary hepatocytes to define the kinetic parameters that describe the biliary excretion.

Predicting the Human Hepatic Clearance of Acidic and Zwitterionic Drugs

Prospective predictions of human hepatic clearance for anionic/zwitterionic compounds, which are oftentimes subjected to transporter-mediated uptake, are challenging in drug discovery. We evaluated the utility of preclinical species, rats and cynomolgus monkeys [nonhuman primates (NHPs)], to predict the human hepatic clearance using a diverse set of acidic/zwitterionic drugs. Preclinical clearance data were generated following intravenous dosing in rats/NHPs and compared to the human clearance data (n = 18/27). Single-species scaling of NHP clearance with an allometric exponent of 0.50 allowed for good prediction of human clearance (fold error ∼2.1, bias ∼1.0), with ∼86% predictions within 3-fold. In comparison, rats underpredicted the clearance of lipophilic acids, while overprediction was noted for hydrophilic acids. Finally, an in vitro clearance assay based on human hepatocytes, which is routinely used in discovery setting, markedly underpredicted human clearance (bias ∼0.12). Collectively, this study provides insights into the usefulness of the preclinical models in enabling pharmacokinetic optimization for acid/zwitterionic drug candidates.

Clearance prediction for Amgen molecules against Extended Clearance Classification System (ECCS) and future directions

Early prediction of elimination pathways for new chemical entities can have a profound impact on drug discovery programs. The recently proposed Extended Clearance Classification System (ECCS) is a step in the right direction, providing a framework to help identify the major elimination pathway of a drug. A list of 42 Amgen small molecules was evaluated against the ECCS framework to assess its performance in retrospectively predicting their major elimination pathway. Here, we present a critical analysis of the chemical space defined by the ECCS framework with the aim of identifying its applicability and constraints. This evaluation highlights the critical need for periodic review and revision of ECCS, given that target constraints are moving molecules away from the traditional 'drug-like' physicochemical space.

Optimizing the Benefit/Risk of Acetyl-CoA Carboxylase Inhibitors through Liver Targeting

Preclinical and clinical data suggest that acetyl-CoA carboxylase (ACC) inhibitors have the potential to rebalance disordered lipid metabolism, leading to improvements in nonalcoholic steatohepatitis (NASH). Consistent with these observations, first-in-human clinical trials with our ACC inhibitor PF-05175157 led to robust reduction of de novo lipogenesis (DNL), albeit with concomitant reductions in platelet count, which were attributed to the inhibition of fatty acid synthesis within bone marrow. Herein, we describe the design, synthesis, and evaluation of carboxylic acid-based ACC inhibitors with organic anion transporting polypeptide (OATP) substrate properties, which facilitated selective distribution of the compounds at the therapeutic site of action (liver) relative to the periphery. These efforts led to the discovery of clinical candidate PF-05221304 (12), which selectively inhibits liver DNL in animals, while demonstrating considerable safety margins against platelet reduction in a nonhuman primate model.

Discovery of potent liver-selective stearoyl-CoA desaturase-1 (SCD1) inhibitors, thiazole-4-acetic acid derivatives, for the treatment of diabetes, hepatic steatosis, and obesity

SCD1 is a rate-limiting enzyme in the conversion of saturated fatty acids to monounsaturated fatty acids. SCD1 inhibitors have potential effects on obesity, diabetes, acne, and cancer, but the adverse effects associated with SCD1 inhibition in the skin and eyelids are impediments to clinical development. To avoid mechanism-based adverse effects, we explored the compounds that selectively inhibit SCD1 in the liver in an ex vivo assay. Starting from a systemically active lead compound, we focused on the physicochemical properties tPSA and cLogP to minimize exposure in the off-target tissues. This effort led to the discovery of thiazole-4-acetic acid analog 48 as a potent and liver-selective SCD1 inhibitor. Compound 48 exhibited significant effects in rodent models of diabetes, hepatic steatosis, and obesity, with sufficient safety margins in a rat toxicology study with repeated dosing.

Molecular properties associated with transporter-mediated drug disposition

Membrane transporters play a key role in the absorption, distribution, clearance, elimination, and transport of drugs. Understanding the drug properties and structure activity relationships (SAR) for affinity to membrane transporters is critical to optimize clearance and pharmacokinetics during drug design. To facilitate the early identification of clearance mechanism, a framework named the extended clearance classification system (ECCS) was recently introduced. Using in vitro and physicochemical properties that are readily available in early drug discovery, ECCS has been successfully applied to identify major clearance mechanism and to implicate the role of membrane transporters in determining pharmacokinetics. While the crystal structures for most of the drug transporters are currently not available, ligand-based modeling approaches that use information obtained from the structure and molecular properties of the ligands have been applied to associate the drug-related properties and transporter-mediated disposition. The approach allows prospective prediction of transporter both substrate and/or inhibitor affinity and build quantitative structure-activity relationship (QSAR) to enable early optimization of pharmacokinetics, tissue distribution and drug-drug interaction risk. Drug design applications can be further improved through uncovering transporter protein crystal structure and generation of quality data to refine and develop viable predictive models.

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.

Unmasking the Role of Uptake Transporters for Digoxin Uptake Across the Barriers of the Central Nervous System in Rat

The role of uptake transporter (organic anion–transporting polypeptide [Oatp]) in the disposition of a P-glycoprotein (P-gp) substrate (digoxin) at the barriers of central nervous system, namely, the blood-brain barrier (BBB), blood-spinal cord barrier (BSCB), and brain-cerebrospinal fluid barrier (BCSFB), was studied using rat as a preclinical species. In vivo chemical inhibition of P-gp and Oatp was achieved using elacridar and rifampicin, respectively. Our findings show that (1) digoxin had a low brain-to-plasma concentration ratio (B/P) (0.07) in rat; (2) in the presence of elacridar, the B/P of digoxin increased by about 12-fold; (3) rifampicin administration alone did not change the digoxin B/P significantly when compared with digoxin B/P alone; (4) rifampicin administration along with elacridar resulted only in 6-fold increase in the B/P of digoxin; (5) similar fold changes and trends were seen with the spinal cord-to-plasma concentration ratio of digoxin, indicating the similarity between BBB and the BSCB; and (6) unlike BBB and BSCB, the presence of rifampicin further increased the cerebrospinal fluid-to-plasma concentration ratio (CSF/P) for digoxin, suggesting a differential orientation of the uptake transporters at the BCSFB (CSF to blood) compared with the BBB (blood to brain). The observations for digoxin uptake, at least at the BBB and the BSCB, advocate the importance of uptake transporters (Oatps). However, the activity of such uptake transporters became evident only after inhibition of the efflux transporter (P-gp).

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.

New IVIVE method for the prediction of total human clearance and relative elimination pathway contributions from in vitro hepatocyte and microsome data

Total human clearance is a key determinant for the pharmacokinetic behavior of drug candidates. Our group recently introduced the Extended Clearance Model (ECM) as an accurate in vitro-in vivo extrapolation (IVIVE) method for the prediction of hepatic clearance. Yet, knowledge about relative elimination pathway contributions is needed in order to predict the total human clearance of drug candidates. In the present work, a training set of 18 drug compounds was used to describe the affiliations between in vitro sinusoidal uptake clearance and the fractional contributions of hepatic (metabolic and biliary) or renal clearance to overall in vivo elimination. By means of these quantitative relationships and using a validation set of 10 diverse drug molecules covering different (sub)classes of the Extended Clearance Concept Classification System (ECCCS), the relative contributions of elimination pathways were calculated and demonstrated to well correlate with human reference data. Likewise, ECM- and pathway-based predictions of total clearances from both data sets demonstrated a strong correlation with the observed clinical values with 26 out of 28 compounds within a three-fold deviation. Hence, total human clearance and relative contributions of elimination pathways were successfully predicted by the presented method using solely hepatocyte and microsome in vitro data.

A new paradigm for navigating compound property related drug attrition

Improving the efficiency of drug discovery remains a major focus for the pharmaceutical industry. Toxicity accounts for 90% of withdrawals and major early-stage terminations relate to suboptimal efficacy and safety. Traditional oral drug space is well defined with respect to physicochemical properties and ADMET risks but increased focus on ligand-lipophilicity efficiency, maximizing enthalpy contributions and new target classes challenge this paradigm. A hybrid space has been identified that combines physical properties and key interactions attributable to drug transporters. A novel algorithm is proposed that incorporates drug-transporter interactions and its utility evaluated against popular ligand efficiency indices. Simply reducing the bulk properties of compounds can exchange one problem for another and creates high-risk areas that challenge the successful delivery from a balanced portfolio.

Characterisation of liver-specific distribution of a novel 1-benzyl-4-aminoindole-based thyroid hormone receptor β agonist, SKL-13784: comparison with GC-1

1. SKL-13784, a novel series of 1-benzyl-4-aminoindole-based thyroid hormone receptor β (TRβ)-selective agonists, showed higher liver selectivity than GC-1 and was poorly distributed in the heart and brain. We aimed to clarify the mechanism of liver selectivity of SKL-13784 through a comparative study with GC-1. 2. Media-loss assays using fresh rat hepatocytes showed that the Oatp family may have been involved in liver uptake for both compounds and that SKL-13784 was more efficiently taken up than GC-1. 3. In addition, the media-loss assay results showed that hepatic uptake was important in eliminating both compounds in rats. 4. The low passive permeability of SKL-13784 on the parallel artificial membrane permeability assay (PAMPA) contributed to the limited distribution of SKL-13784 into extrahepatocytes. 5. Biliary extraction was a major route of SKL-13784 and GC-1 disposition. SKL-13784 was excreted into bile unchanged and in its glucuronide form, whereas almost all GC-1 in bile was in its glucuronide form. In bile duct-cannulated rats, a 4.3-fold decrease in t1/2 of SKL-13784 was observed, implicating enterohepatic biliary recirculation. 6. The selective distribution of SKL-13784 in the liver was largely due to efficient uptake via hepatic transporters.

Predicting the extent of metabolism using in vitro permeability rate measurements and in silico permeability rate predictions

The Biopharmaceutics Drug Disposition Classification System (BDDCS) can be utilized to predict drug disposition, including interactions with other drugs and transporter or metabolizing enzyme effects based on the extent of metabolism and solubility of a drug. However, defining the extent of metabolism relies upon clinical data. Drugs exhibiting high passive intestinal permeability rates are extensively metabolized. Therefore, we aimed to determine if in vitro measures of permeability rate or in silico permeability rate predictions could predict the extent of metabolism, to determine a reference compound representing the permeability rate above which compounds would be expected to be extensively metabolized, and to predict the major route of elimination of compounds in a two-tier approach utilizing permeability rate and a previously published model predicting the major route of elimination of parent drug. Twenty-two in vitro permeability rate measurement data sets in Caco-2 and MDCK cell lines and PAMPA were collected from the literature, while in silico permeability rate predictions were calculated using ADMET Predictor or VolSurf+. The potential for permeability rate to differentiate between extensively and poorly metabolized compounds was analyzed with receiver operating characteristic curves. Compounds that yielded the highest sensitivity-specificity average were selected as permeability rate reference standards. The major route of elimination of poorly permeable drugs was predicted by our previously published model, and the accuracies and predictive values were calculated. The areas under the receiver operating curves were >0.90 for in vitro measures of permeability rate and >0.80 for the VolSurf+ model of permeability rate, indicating they were able to predict the extent of metabolism of compounds. Labetalol and zidovudine predicted greater than 80% of extensively metabolized drugs correctly and greater than 80% of poorly metabolized drugs correctly in Caco-2 and MDCK, respectively, while theophylline predicted greater than 80% of extensively and poorly metabolized drugs correctly in PAMPA. A two-tier approach predicting elimination route predicts 72 ± 9%, 49 ± 10%, and 66 ± 7% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is predicted in silico and 74 ± 7%, 85 ± 2%, and 73 ± 8% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is determined in vitro.

Predicting when biliary excretion of parent drug is a major route of elimination in humans

Biliary excretion is an important route of elimination for many drugs, yet measuring the extent of biliary elimination is difficult, invasive, and variable. Biliary elimination has been quantified for few drugs with a limited number of subjects, who are often diseased patients. An accurate prediction of which drugs or new molecular entities are significantly eliminated in the bile may predict potential drug-drug interactions, pharmacokinetics, and toxicities. The Biopharmaceutics Drug Disposition Classification System (BDDCS) characterizes significant routes of drug elimination, identifies potential transporter effects, and is useful in understanding drug-drug interactions. Class 1 and 2 drugs are primarily eliminated in humans via metabolism and will not exhibit significant biliary excretion of parent compound. In contrast, class 3 and 4 drugs are primarily excreted unchanged in the urine or bile. Here, we characterize the significant elimination route of 105 orally administered class 3 and 4 drugs. We introduce and validate a novel model, predicting significant biliary elimination using a simple classification scheme. The model is accurate for 83% of 30 drugs collected after model development. The model corroborates the observation that biliarily eliminated drugs have high molecular weights, while demonstrating the necessity of considering route of administration and extent of metabolism when predicting biliary excretion. Interestingly, a predictor of potential metabolism significantly improves predictions of major elimination routes of poorly metabolized drugs. This model successfully predicts the major elimination route for poorly permeable/poorly metabolized drugs and may be applied prior to human dosing.

Estimation of biliary excretion of foreign compounds using properties of molecular structure

Biliary excretion is one of the main elimination pathways for drugs and/or their metabolites. Therefore, an insight into the structural profile of cholephilic compounds through accurate modelling of the biliary excretion is important for the estimation of clinical pharmacokinetics in early stages of drug discovery. The aim of this study was to develop quantitative structure-activity relationships as computational tools for the estimation of biliary excretion and identification of the molecular properties controlling this process. The study used percentage of dose excreted intact into bile measured in vivo in rat for a diverse dataset of 217 compounds. Statistical techniques were multiple linear regression analysis, regression trees, random forest and boosted trees. A simple regression tree model generated using the CART algorithm was the most accurate in the estimation of the percentage of bile excretion of compounds, and this outperformed the more sophisticated boosted trees and random forest techniques. Analysis of the outliers indicated that the models perform best when lipophilicity is not too extreme (log P < 5.35) and for compounds with molecular weight above 280 Da. Molecular descriptors selected by all these models including the top ten incorporated in boosted trees and random forest indicated a higher biliary excretion for relatively hydrophilic compounds especially if they are anionic or cationic, and have a large molecular size. A statistically validated molecular weight threshold for potentially significant biliary excretion was above 348 Da.

A perspective on the prediction of drug pharmacokinetics and disposition in drug research and development

Prediction of human pharmacokinetics of new drugs, as well as other disposition attributes, has become a routine practice in drug research and development. Prior to the 1990s, drug disposition science was used in a mostly descriptive manner in the drug development phase. With the advent of in vitro methods and availability of human-derived reagents for in vitro studies, drug-disposition scientists became engaged in the compound design phase of drug discovery to optimize and predict human disposition properties prior to nomination of candidate compounds into the drug development phase. This has reaped benefits in that the attrition rate of new drug candidates in drug development for reasons of unacceptable pharmacokinetics has greatly decreased. Attributes that are predicted include clearance, volume of distribution, half-life, absorption, and drug-drug interactions. In this article, we offer our experience-based perspectives on the tools and methods of predicting human drug disposition using in vitro and animal data.