Hepatic uptake transporters [solute carriers (SLCs)], including organic anion transporting polypeptide (OATP) 1B1, OATP1B3, OATP2B1, sodium-dependent taurocholate cotransporting polypeptide (NTCP), and organic anion (OAT2) and organic cation (OCT1) transporters, play a key role in determining the systemic and liver exposure of chemically diverse drugs. Here, we established a phenotyping approach to quantify the contribution of the six SLCs, and passive diffusion, to the overall uptake using plated human hepatocytes (PHHs). First, selective inhibitor conditions were identified by screening about 20 inhibitors across the six SLCs using single-transfected human embryonic kidney 293 cells. Data implied rifamycin SV (20 mM) inhibits three OATPs, while rifampicin (5 mM) inhibits OATP1B1/1B3 only. Further, hepatitis B virus myristoylated-preS1 peptide (0.1 mM), quinidine (100 mM), and ketoprofen (100-300 mM) are relatively selective against NTCP, OCT1, and OAT2, respectively. Second, using these inhibitory conditions, the fraction transported (f t) by the individual SLCs was characterized for 20 substrates with PHH. Generally, extended clearance classification system class 1A/3A (e.g., warfarin) and 1B/3B compounds (e.g., statins) showed predominant OAT2 and OATP1B1/1B3 contribution, respectively. OCT1mediated uptake was prominent for class 2/4 compounds (e.g., metformin). Third, in vitro f t values were corrected using quantitative proteomics data to obtain "scaled f t ." Fourth, in vitro-in vivo extrapolation of the scaled OATP1B1/1B3 f t was assessed, leveraging statin clinical drug-drug interaction data with rifampicin as the perpetrator. Finally, we outlined a novel stepwise strategy to implement phenotypic characterization of SLC-mediated hepatic uptake for new molecular entities and drugs in a drug discovery and development setting.

The hepatic risk matrix (HRM) was developed and used to differentiate lead clinical and back-up drug candidates against competitor/ marketed drugs within the same pharmaceutical class for their potential to cause human drug-induced liver injury (DILI). The hybrid HRM scoring system blends physicochemical properties (Rule of Two Model: dose and lipophilicity or Partition Model: dose, ionization state, lipophilicity, and fractional carbon bond saturation) with common toxicity mechanisms (cytotoxicity, mitochondrial dysfunction, and bile salt export pump (BSEP) inhibition) that promote DILI. HRM scores are based on bracketed safety margins (<1, 1−10, 10−100, and >100× clinical C max,total ). On the basis of well-established clinical safety experience of marketed/withdrawn drug candidates, the background analysis consists of 200 drugs from the Liver Toxicity Knowledge Base annotated as Most-DILI-(79), Less-DILI-(56), No-DILI-(47), and Ambiguous-DILI-concern (18) drugs. Scores were generated for over 21 internal and 7 external drug candidates discontinued for unacceptable incidence/magnitude of liver transaminase elevations during clinical trials or withdrawn for liver injury severity. Both hybrid scoring systems identified 70−80% Most-DILI-concern drugs, but more importantly, stratified successful/unsuccessful drug candidates for liver safety (incidence/severity of transaminase elevations and approved drug labels). Incorporating other mechanisms (reactive metabolite and cytotoxic metabolite generation and hepatic efflux transport inhibition, other than BSEP) to the HRM had minimal beneficial impact in DILI prediction/stratification. As is, the hybrid scoring system was positioned for portfolio assessments to contrast DILI risk potential of small molecule drug candidates in early clinical development. This stratified approach for DILI prediction aided decisions regarding drug candidate progression, follow-up mechanistic work, back-up selection, clinical dose selection, and due diligence assessments in favor of compounds with less implied clinical hepatotoxicity risk.

The aim of this study was to investigate the sensitivity and specificity of endogenous glycochenodeoxycholate and glycodeoxycholate 3-O-glucuronides (GCDCA-3G and GDCA-3G) as substrates for organic anion transporting polypeptide 1B1 (OATP1B1) in humans. We measured fasting levels of plasma GCDCA-3G and GDCA-3G using liquid chromatography-tandem mass spectrometry in 356 healthy volunteers. The mean plasma levels of both compounds were ~ 50% lower in women than in men (P = 2.25 × 10 −18 and P = 4.73 × 10 −9). In a microarray-based genome-wide association study, the SLCO1B1 rs4149056 (c.521T>C, p.Val174Ala) variation showed the strongest association with the plasma GCDCA-3G (P = 3.09 × 10 −30) and GDCA-3G (P = 1.60 × 10 −17) concentrations. The mean plasma concentration of GCDCA-3G was 9.2-fold (P = 8.77 × 10 −31) and that of GDCA-3G was 6.4fold (P = 2.45x10 −13) higher in individuals with the SLCO1B1 c.521C/C genotype than in those with the c.521T/T genotype. No other variants showed independent genome-wide significant associations with GCDCA-3G or GDCA-3G. GCDCA-3G was highly efficacious in detecting the SLCO1B1 c.521C/C genotype with an area under the receiver operating characteristic curve of 0.996 (P < 0.0001). The sensitivity (98-99%) and specificity (100%) peaked at a cutoff value of 180 ng/mL for men and 90 ng/mL for women. In a haplotype-based analysis, SLCO1B1*5 and *15 were associated with reduced, and SLCO1B1*1B, *14, and *35 with increased OATP1B1 function. In vitro, both GCDCA-3G and GDCA-3G showed at least 6 times higher uptake by OATP1B1 than OATP1B3 or OATP2B1. These data indicate that the hepatic uptake of GCDCA-3G and GDCA-3G is predominantly mediated by OATP1B1. GCDCA-3G, in particular, is a highly sensitive and specific OATP1B1 biomarker in humans.

Transporter-mediated hepatic uptake is proven to be the rate-determining step in the systemic clearance of several drugs. Therefore, accurate measurement of active and passive uptake clearances in vitro is critical to facilitate pharmacokinetics and drug-drug interaction predictions. Here, we evaluated the plated human hepatocytes (PHH) and studied the effect of incubation temperature and inhibitor concentration on uptake measurements, in order to reliably estimate hepatic uptake components. Uptake rates measured using PHH, at 37°C without and with rifamycin SV, were comparable with those obtained from suspension hepatocytes and sandwich-cultured hepatocytes for a set of 10-13 compounds. Apparent permeability across monolayers of low-efflux Madin-Darby canine kidney cells was measured at 4, 10, and 37°C. Of the 23 compounds evaluated, 13 compounds showed >2-fold reduction in passive permeability at 4°C compared to 37°C, inferring that low-temperature incubations may underestimate passive uptake. Inhibition studies using transporter-transfected cells suggested that ∼20 μM rifamycin SV completely inhibited organic anion-transporting polypeptides (OATPs), while no significant inhibition was noted for other hepatic uptake transporters. On the basis of inhibition profiles, the contribution of active versus passive and OATP versus non-OATP transport to the PHH uptake was discerned for various endogenous substrates and statins. With the exception of fluvastatin, the statins studied were predominantly transported by OATPs in PHH and the non-OATP transporters, such as Na-taurocholate co-transporting polypeptide, played a minimal role. In conclusion, PHH is useful for uptake measurements, and rifamycin SV employed at different concentrations can reliably estimate active and passive uptake and characterize OATP-dependent active uptake.

Physiologically‐based pharmacokinetic (PBPK) modeling is a powerful tool to quantitatively describe drug disposition profiles in vivo, thereby providing an alternative to predict drug–drug interactions (DDIs) that have not been tested clinically. This study aimed to predict effects of rifampin‐mediated intestinal P‐glycoprotein (Pgp) induction on pharmacokinetics of Pgp substrates via PBPK modeling. First, we selected four Pgp substrates (digoxin, talinolol, quinidine, and dabigatran etexilate) to derive in vitro to in vivo scaling factors for intestinal Pgp kinetics. Assuming unbound Michaelis‐Menten constant (Km) to be intrinsic, we focused on the scaling factors for maximal efflux rate (Jmax) to adequately recover clinically observed results. Next, we predicted rifampin‐mediated fold increases in intestinal Pgp abundances to reasonably recover clinically observed DDI results. The modeling results suggested that threefold to fourfold increases in intestinal Pgp abundances could sufficiently reproduce the DDI results of these Pgp substrates with rifampin. Hence, the obtained fold increases can potentially be applicable to DDI prediction with other Pgp substrates.