Telaprevir 2 (VX-950), an inhibitor of the hepatitis C virus (HCV(a)) NS3-4A protease, is in phase 3 clinical trials. One of the major metabolites of 2 is its P1-(R)-diastereoisomer, 3 (VRT-394), containing an inversion at the chiral center next to the alpha-ketoamide on exchange of a proton with solvent. Compound 3 is approximately 30-fold less active against HCV protease. In an attempt to suppress the epimerization of 2 without losing activity against the HCV protease, the proton at that chiral site was replaced with deuterium (d). The compound 1 (d-telaprevir) is as efficacious as 2 in in vitro inhibition of protease activity and viral replication (replicon) assays. The kinetics of in vitro stability of 1 and 2 in buffered pH solutions and plasma samples, including human plasma, suggest that 1 is significantly more stable than 2. Oral administration (10 mg/kg) in rats resulted in a approximately 13% increase of AUC for 1.

Amprenavir (141W94, VX-478, KVX-478) is metabolized primarily by CYP3A4 (cytochrome P450 3A4) in recombinant systems and human liver microsomes (HLM). The effects of ketoconazole, terfenadine, astemizole, rifampicin, methadone, and rifabutin upon amprenavir metabolism were examined in vitro using HLM. Ketoconazole, terfenadine, and astemizole were observed to inhibit amprenavir depletion, consistent with their known specificity for CYP3A4. The HIV protease inhibitors, indinavir, saquinavir, ritonavir, and nelfinavir, were included in incubations containing amprenavir to examine the interactions of HIV protease inhibitors in vitro. The order of amprenavir metabolism inhibition in human liver microsomes was observed to be: ritonavir > indinavir > nelfinavir > saquinavir. The Ki value for amprenavir-mediated inhibition of testosterone hydroxylation in human liver microsomes was found to be approximately 0.5 microM. Studies suggest that amprenavir inhibits CYP3A4 to a greater extent than saquinavir, and to a much lesser extent than ritonavir. Amprenavir, nelfinavir, and indinavir appear to inhibit CYP3A4 to a moderate extent, suggesting a selected number of coadministration restrictions.

While several therapeutic options exist, the need for more effective, safe, and convenient treatment for a variety of autoimmune diseases persists. Targeting the Janus tyrosine kinases (JAKs), which play essential roles in cell signaling responses and can contribute to aberrant immune function associated with disease, has emerged as a novel and attractive approach for the development of new autoimmune disease therapies. We screened our compound library against JAK3, a key signaling kinase in immune cells, and identified multiple scaffolds showing good inhibitory activity for this kinase. A particular scaffold of interest, the 1H-pyrrolo[2,3-b]pyridine series (7-azaindoles), was selected for further optimization in part on the basis of binding affinity (Ki) as well as on the basis of cellular potency. Optimization of this chemical series led to the identification of VX-509 (decernotinib), a novel, potent, and selective JAK3 inhibitor, which demonstrates good efficacy in vivo in the rat host versus graft model (HvG). On the basis of these findings, it appears that VX-509 offers potential for the treatment of a variety of autoimmune diseases.

(R)-2-((2-(1H-pyrrolo [2,3-b]pyridin-3-yl)pyrimidin-4-yl)amino)-2-methyl-N-(2,2,2-trifluoroethyl)butanamide decernotinib) is an oral Janus kinase 3 inhibitor that has been studied in patients with rheumatoid arthritis. Patients with rheumatoid arthritis often receive multiple medications, such as statins and steroids, to manage the signs and symptoms of comorbidities, which increases the chances of drug-drug interactions (DDIs). Mechanism-based inhibition is a subset of time-dependent inhibition (TDI) and occurs when a molecule forms a reactive metabolite which irreversibly binds and inactivates drug-metabolizing enzymes, potentially increasing the systemic load to toxic concentrations. Traditionally, perpetrating compounds are screened using human liver microsomes (HLMs); however, this system may be inadequate when the precipitant is activated by a non-cytochrome P450 (P450)-mediated pathway. Even though studies assessing competitive inhibition and TDI using HLM suggested a low risk for CYP3A4-mediated DDI in the clinic, VX-509 increased the area under the curve of midazolam, atorvastatin, and methyl-prednisolone by approximately 12.0-, 2.7-, and 4.3-fold, respectively. Metabolite identification studies using human liver cytosol indicated that VX-509 is converted to an oxidative metabolite, which is the perpetrator of the DDIs observed in the clinic. As opposed to HLM, hepatocytes contain the full complement of drug-metabolizing enzymes and transporters and can be used to assess TDI arising from non-P450-mediated metabolic pathways. In the current study, we highlight the role of aldehyde oxidase in the formation of the hydroxylmetabolite of VX-509, which is involved in clinically significant TDIbased DDIs and represents an additional example in which a system-dependent prediction of TDI would be evident.

Typically, concentration-response curves are based upon nominal inducer concentrations for in-vitro-to-in-vivo extrapolation of CYP3A4 induction. The limitation of this practice is that it assumes the hepatocyte culture model is a static system. We assessed whether correcting for: 1) changes in perpetrator concentration in the induction medium during the incubation period, 2) perpetrator binding to proteins in the induction medium, and 3) nonspecific binding of perpetrator can improve the accuracy of CYP3A4 induction predictions. Of the seven compounds used in this evaluation, significant parent loss and nonspecific binding were observed for rifampicin (29.3-38.3%), pioglitazone (64.3-78.6%), and rosiglitazone (57.1-75.5%). As a result, the free measured EC values (EC) of pioglitazone, rosiglitazone, and rifampicin were significantly lower than the nominal EC values. In general, the accuracy of the induction predictions, using multiple static models, improved when corrections were made for measured medium concentrations, medium protein binding, and nonspecific binding of the perpetrator, as evidenced by 18-29% reductions in the root mean square error. The relative induction score model performed better than the basic static and mechanistic static models, resulting in lower prediction error and no false-positive or false-negative predictions. However, even when the EC value was used, the induction prediction for bosentan, which is a substrate of organic anion transporter proteins, was overpredicted by approximately 2-fold. Accounting for the ratio of unbound intracellular concentrations to unbound medium concentrations (K) (0.5-7.5) and the predicted multiple-dose K (0.6) for bosentan resulted in induction predictions within 35% of the observed interaction.