Activation of the fibroblast growth factor receptor FGFR4 by FGF19 drives hepatocellular carcinoma (HCC), a disease with few, if any, effective treatment options. While a number of pan-FGFR inhibitors are being clinically evaluated, their application to FGF19-driven HCC may be limited by dose-limiting toxicities mediated by FGFR1-3 receptors. To evade the potential limitations of pan-FGFR inhibitors, we generated H3B-6527, a highly selective covalent FGFR4 inhibitor, through structure-guided drug design. Studies in a panel of 40 HCC cell lines and 30 HCC PDX models showed that FGF19 expression is a predictive biomarker for H3B-6527 response. Moreover, coadministration of the CDK4/6 inhibitor palbociclib in combination with H3B-6527 could effectively trigger tumor regression in a xenograft model of HCC. Overall, our results offer preclinical proof of concept for H3B-6527 as a candidate therapeutic agent for HCC cases that exhibit increased expression of FGF19. .

Mutations in estrogen receptor alpha (ER) that confer resistance to existing classes of endocrine therapies are detected in up to 30% of patients who have relapsed during endocrine treatments. Since a significant proportion of therapy-resistant breast cancer metastases continue to be dependent on ER signaling, there remains a critical need to develop the next generation of ER antagonists that can overcome aberrant ER activity. Through our drug discovery efforts, we identified H3B-5942 which covalently inactivates both wild-type and mutant ER by targeting Cys530 and enforcing a unique antagonist conformation. H3B-5942 belongs to a class of ER antagonist referred to as Selective Estrogen Receptor Covalent Antagonists (SERCAs).In vitro comparisons of H3B-5942 with standard of care (SoC) 10, 2018; DOI: 10.1158/2159-8290.CD-17-1229 3Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on July SignificanceNearly 30% of endocrine-therapy resistant breast cancer metastases harbor constitutively activating mutations in ER. Selective Estrogen Receptor Covalent Antagonist (SERCA) H3B-5942 engages C530 of both ER WT and ER MUT, promotes a unique antagonist conformation, and demonstrates improved in vitro and in vivo activity over standard of care (SoC) agents.Importantly, single agent efficacy can be further enhanced by combining with CDK4/6 or mTOR inhibitors.

Potential applications of MPS in the ADME discipline.

Recent European Medicines Agency (final) and US Food and Drug Administration (draft) drug interaction guidances proposed that human circulating metabolites should be investigated in vitro for their drug-drug interaction (DDI) potential if present at ‡25% of the parent area under the time-concentration curve (AUC) (US Food and Drug Administration) or ‡25% of the parent and ‡10% of the total drug-related AUC (European Medicines Agency). To examine the application of these regulatory recommendations, a group of scientists, representing 18 pharmaceutical companies of the Drug Metabolism Leadership Group of the Innovation and Quality Consortium, conducted a scholarship to assess the risk of contributions by metabolites to cytochrome P450 (P450) inhibition-based DDIs. The group assessed the risk of having a metabolite as the sole contributor to DDI based on literature data and analysis of the 137 most frequently prescribed drugs, defined structural alerts associated with P450 inhibition/inactivation by metabolites, and analyzed current approaches to trigger in vitro DDI studies for metabolites. The group concluded that the risk of P450 inhibition caused by a metabolite alone is low. Only metabolites from 5 of 137 drugs were likely the sole contributor to the in vivo P450 inhibition-based DDIs. Two recommendations were provided when assessing the need to conduct in vitro P450 inhibition studies for metabolites: 1) consider structural alerts that suggest P450 inhibition potential, and 2) use multiple approaches (e.g., a metabolite cut-off value of 100% of the parent AUC and the R met strategy) to predict P450 inhibition-based DDIs caused by metabolites in the clinic.