Sinusoidal Organic Anion-Transporting Polypeptide 1B1/1B3 and Bile Canalicular Multidrug Resistance-Associated Protein 2 Play an Essential Role in the Hepatobiliary Disposition of a Synthetic Cyclic Dinucleotide (STING Agonist).

The liver is central to the elimination of many drugs from the body involving multiple processes and understanding of these processes is important to quantitively assess hepatic clearance of drugs. The synthetic STING (STimulator of INterferon Genes protein) agonist is a new class of drugs currently being evaluated in clinical trials as a potential anticancer therapy. In this study, we used ML00960317 (synthetic STING agonist) to investigate the hepatobiliary disposition of this novel molecular entity. A bile-duct cannulated (BDC) rat study indicated that biliary excretion is the major route of elimination for ML00960317 (84% of parent dose in bile). The human biliary clearance using in vitro sandwich cultured human hepatocyte model predicted significant biliary excretion of ML00960317 (biliary excretion index (BEI) of 47%). Moreover, the transport studies using transporter expressing cell lines, hepatocytes, and membrane vesicles indicated that ML00960317 is a robust substrate of OATP1B1, OATP1B3, and MRP2. Using relative expression factor approach, the combined contribution of OATP1B1 (fraction transported (ft) = 0.62) and OATP1B3 (ft = 0.31) was found to be 93% of the active uptake clearance of ML00960317 into the liver. Furthermore, OATP1B1 and OATP1B3-mediated uptake of ML00960317 was inhibited by rifampicin with IC50 of 6.5 and 2.3 µM, respectively indicating an in vivo DDI risk (R value of 1.5 and 2.5 for OATP1B1 and OATP1B3, respectively). These results highlighted an important role of OATP1B1, OATP1B3, and MRP2 in the hepatobiliary disposition of ML00960317. These pathways may act as rate-determining steps in the hepatic clearance of ML00960317 thus presenting clinical DDI risk.

Sinusoidal Uptake Determines the Hepatic Clearance of Pevonedistat (TAK-924) as Explained by Extended Clearance Model.

Quantitative assessment of hepatic clearance (CLH) of drugs is critical to accurately predict human dose and drug-drug interaction (DDI) liabilities. This is challenging for drugs that involve complex transporter-enzyme interplay. In this study, we demonstrate this interplay in the CLH and DDI effect in the presence of CYP3A4 perpetrator for pevonedistat using both the conventional clearance model (CCM) and the extended clearance model (ECM). In vitro metabolism and hepatocyte uptake data showed that pevonedistat is actively transported into the liver via multiple uptake transporters and metabolized predominantly by CYP3A4 (88%). The active uptake clearance (CLact,inf) and passive diffusion clearance (CLdiff,inf) were 21 and 8.7 ml/min/kg, respectively. The CLact,inf was underpredicted as Empirical Scaling Factor of 13 was needed to recover the in vivo plasma clearance (CLplasma). Both CCM and ECM predicted CLplasma of pevonedistat reasonably well (predicted CLplasma of 30.8 (CCM) and 32.1 (ECM) versus observed CLplasma of 32.2 ml/min/kg). However, both systemic and liver exposures in the presence of itraconazole were well predicted by ECM but not by CCM (predicted pevonedistat plasma area under the concentration-time curve ratio (AUCR) 2.73 (CCM) and 1.23 (ECM))., The ECM prediction is in accordance with the observed clinical DDI data (observed plasma AUCR of 1.14) that showed CYP3A4 inhibition did not alter pevonedistat exposure systemically, although ECM predicted liver AUCR of 2.85. Collectively, these data indicated that the hepatic uptake is the rate-determining step in the CLH of pevonedistat and are consistent with the lack of systemic clinical DDI with itraconazole. SIGNIFICANCE STATEMENT: In this study, we successfully demonstrated that the hepatic uptake is the rate-determining step in the CLH of pevonedistat. Both the conventional and extended clearance models predict CLplasma of pevonedistat well however, only the ECM accurately predicted DDI effect in the presence of itraconazole, thus providing further evidence for the lack of DDI with CYP3A4 perpetrators for drugs that involve complex transporter-enzyme interplay as there are currently not many examples in the literature except prototypical OATP substrate drugs.

Design of proteasome inhibitors with oral efficacy in vivo against Plasmodium falciparum and selectivity over the human proteasome.

The Plasmodium falciparum proteasome is a potential antimalarial drug target. We have identified a series of amino-amide boronates that are potent and specific inhibitors of the P. falciparum 20S proteasome (Pf20S) ß5 active site and that exhibit fast-acting antimalarial activity. They selectively inhibit the growth of P. falciparum compared with a human cell line and exhibit high potency against field isolates of P. falciparum and Plasmodium vivax They have a low propensity for development of resistance and possess liver stage and transmission-blocking activity. Exemplar compounds, MPI-5 and MPI-13, show potent activity against P. falciparum infections in a SCID mouse model with an oral dosing regimen that is well tolerated. We show that MPI-5 binds more strongly to Pf20S than to human constitutive 20S (Hs20Sc). Comparison of the cryo-electron microscopy (EM) structures of Pf20S and Hs20Sc in complex with MPI-5 and Pf20S in complex with the clinically used anti-cancer agent, bortezomib, reveal differences in binding modes that help to explain the selectivity. Together, this work provides insights into the 20S proteasome in P. falciparum, underpinning the design of potent and selective antimalarial proteasome inhibitors.

Discovery of TAK-981, a First-in-Class Inhibitor of SUMO-Activating Enzyme for the Treatment of Cancer.

SUMOylation is a reversible post-translational modification that regulates protein function through covalent attachment of small ubiquitin-like modifier (SUMO) proteins. The process of SUMOylating proteins involves an enzymatic cascade, the first step of which entails the activation of a SUMO protein through an ATP-dependent process catalyzed by SUMO-activating enzyme (SAE). Here, we describe the identification of TAK-981, a mechanism-based inhibitor of SAE which forms a SUMO-TAK-981 adduct as the inhibitory species within the enzyme catalytic site. Optimization of selectivity against related enzymes as well as enhancement of mean residence time of the adduct were critical to the identification of compounds with potent cellular pathway inhibition and ultimately a prolonged pharmacodynamic effect and efficacy in preclinical tumor models, culminating in the identification of the clinical molecule TAK-981.

Preclinical absorption, distribution, metabolism, excretion and pharmacokinetics of a novel selective inhibitor of breast cancer resistance protein (BCRP).

1. Breast cancer resistance protein (BCRP) plays an important role in drug absorption, distribution and excretion. It is challenging to evaluate BCRP functions in preclinical models because commonly used BCRP inhibitors are nonspecific or unstable in animal plasma. 2. In this work, in vitro absorption, distribution, metabolism and elimination (ADME) assays and pharmacokinetic (PK) experiments in Bcrp knockout (KO) (Abcg2-/-) and wild-type (WT) FVB mice and Wistar rats were conducted to characterize the preclinical properties of a novel selective BCRP inhibitor (ML753286, a Ko143 analog). 3. ML753286 is a potent inhibitor for BCRP, but not for P-glycoprotein (P-gp), organic anion-transporting polypeptide (OATP) or major cytochrome P450s (CYPs). It has high permeability, but is not an efflux transporter substrate. ML753286 has low to medium clearance in rodent and human liver S9 fractions, and is stable in plasma cross species. Bcrp inhibition affects oral absorption and clearance of sulfasalazine in rodents. A single dose of ML753286 at 50-300 mg/kg orally, and at 20 mg/kg intravenously or 25 mg/kg orally inhibits Bcrp functions in mice and rats, respectively. 4. These findings confirm that ML753286 is a useful selective inhibitor to evaluate BCRP/Bcrp activity in vitro and in rodent model systems.

Efflux transporter breast cancer resistance protein dominantly expresses on the membrane of red blood cells, hinders partitioning of its substrates into the cells, and alters drug-drug interaction profiles.

1. Red blood cell (RBC) partitioning is important in determining pharmacokinetic and pharmacodynamic properties of a compound; however, active transport across RBC membranes is not well understood, particularly without transporter-related cell membrane proteomics data. 2. In this study, we quantified breast cancer resistance protein (BCRP/Bcrp) and MDR1/P-glycoprotein (P-gp) protein expression in RBCs from humans, monkeys, dogs, rats and mice using nanoLC/MS/MS, and evaluated their effect on RBC partitioning and plasma exposure of their substrates. BCRP-specific substrate Cpd-1 and MDR1-specific substrate Cpd-2 were characterized using Caco-2 Transwell® system and then administered to Bcrp or P-gp knockout mice. 3. The quantification revealed BCRP/Bcrp but not MDR1/P-gp to be highly expressed on RBC membranes. The knockout mouse study indicated BCRP/Bcrp pumps the substrate out of RBCs, lowering its partitioning and thus preventing binding to intracellular targets. This result was supported by a Cpd-1 and Bcrp inhibitor ML753286 drug-drug interaction (DDI) study in mice. Because of enhanced partitioning of Cpd-1 into RBCs after BCRP/Bcrp inhibition, Cpd-1 plasma concentration changed much less extent with genetic or chemical knockout of Bcrp albeit marked blood concentration increase, suggesting less DDI effect. 4. This finding is fundamentally meaningful to RBC partitioning, pharmacokinetics and DDI studies of BCRP-specific substrates.

Utilizing In Vitro Dissolution-Permeation Chamber for the Quantitative Prediction of pH-Dependent Drug-Drug Interactions with Acid-Reducing Agents: a Comparison with Physiologically Based Pharmacokinetic Modeling.

For many orally administered basic drugs with pH-dependent solubility, concurrent administration with acid-reducing agents (ARAs) can significantly impair their absorption and exposure. In this study, pH-dependent drug-drug interaction (DDI) prediction methods, including in vitro dissolution-permeation chamber (IVDP) and physiologically based pharmacokinetic (PBPK) modeling, were evaluated for their ability to quantitatively predict the clinical DDI observations using 11 drugs with known clinical pH-dependent DDI data. The data generated by IVDP, which consists of a gastrointestinal compartment and a systemic compartment separated by a biomimic membrane, significantly correlated with the clinical DDI observations. The gastrointestinal compartment AUC ratio showed strong correlation with clinical AUC ratio (R=0.72 and P=0.0056), and systemic compartment AUC ratio showed strong correlation with clinical Cmax ratio (R=0.91 and P=0.0003). PBPK models were also developed for the 11 test compounds. The simulations showed that the predictions from PBPK model with experimentally measured parameters significantly correlated with the clinical DDI observations. Future studies are needed to evaluate predictability of Z-factor-based PBPK models for pH-dependent DDI. Overall, these data suggested that the severity of pH-dependent DDI can be predicted by in vitro and in silico methods. Proper utilization of these methods before clinical DDI studies could allow adequate anticipation of pH-dependent DDI, which helps with minimizing pharmacokinetic variation in clinical studies and ensuring every patient with life-threatening diseases receives full benefit of the therapy.

Synthesis of a new inhibitor of breast cancer resistance protein with significantly improved pharmacokinetic profiles.

The design, synthesis, in vitro inhibitory potency, and pharmacokinetic (PK) profiles of Ko143 analogs are described. Compared to commonly used Ko143, the new breast cancer resistance protein (BCRP) inhibitor (compound A) showed the same potency and a significantly improved PK profile in rats (lower clearance [1.54L/h/kg] and higher bioavailability [123%]). Ko143 on the other hand suffers from poor bioavailability. Compared to Ko143, compound A would be a useful probe for delineating the role of BCRP during in vivo studies in animals.

Inhibition of hepatic organic anion-transporting polypeptide by RNA interference in sandwich-cultured human hepatocytes: an in vitro model to assess transporter-mediated drug-drug interactions.

Organic anion-transporting polypeptides (OATPs), members of the SLCO/SLC21 family, mediate the transport of various endo- and xenobiotics. In human liver, OATP1B1, 1B3, and 2B1 are located at the basolateral membrane of hepatocytes and are involved in hepatic drug uptake and biliary elimination. Clinically significant drug-drug interactions (DDIs) mediated by hepatic OATPs have drawn great attention from clinical practitioners and researchers. However, there are considerable challenges to prospectively understanding the extent of OATP-mediated DDIs because of the lack of specific OATP inhibitors or substrates and the limitations of in vitro tools. In the present study, a novel RNA interference knockdown sandwich-cultured human hepatocyte model was developed and validated. Quantitative polymerase chain reaction, microarray and immunoblotting analyses, along with uptake assays, illustrated that the expression and transport activity of hepatic OATPs were reduced by small interfering (siRNA) efficiently and specifically in this model. Although OATP siRNA decreased only 20 to 30% of the total uptake of cerivastatin into human hepatocytes, it caused a 50% reduction in cerivastatin metabolism, which was observed by monitoring the formation of the two major metabolites of cerivastatin. The results suggest that coadministration of a drug that is a hepatic OATP inhibitor could significantly alter the pharmacokinetic profile of cerivastatin in clinical studies. Further studies with this novel model demonstrated that OATP and cytochrome P450 have a synergistic effect on cerivastatin-gemfibrozil interactions. The siRNA knockdown sandwich-cultured human hepatocytes may provide a new powerful model for evaluating DDIs.