A phase I, randomized, ascending-dose study to assess safety, pharmacokinetics, and activity of GDC-8264, a RIP1 inhibitor, in healthy volunteers.

Receptor-interacting protein 1 (RIP1) is a key regulator of multiple signaling pathways that mediate inflammatory responses and cell death. RIP1 kinase activity mediates apoptosis and necroptosis induced by tumor necrosis factor (TNF)-α, Toll-like receptors, and ischemic tissue damage. RIP1 has been implicated in several human pathologies and consequently, RIP1 inhibition may represent a therapeutic approach for diseases dependent on RIP1-mediated inflammation and cell death. GDC-8264 is a potent, selective, and reversible small molecule inhibitor of RIP1 kinase activity. This phase I, randomized, placebo-controlled, double-blinded trial examined safety, pharmacokinetics (PKs), and pharmacodynamics (PDs) of single- (5-225 mg) and multiple- (50 and 100 mg once daily, up to 14 days) ascending oral doses of GDC-8264 in healthy volunteers, and also tested the effect of food on the PKs of GDC-8264. All adverse events in GDC-8264-treated subjects in both stages were mild. GDC-8264 exhibited dose-proportional increases in systemic exposure; the mean terminal half-life ranged from 10-13 h, with limited accumulation on multiple dosing (accumulation ratio [AR] ~ 1.4); GDC-8264 had minimal renal excretion at all doses. A high-fat meal had no significant effect on the PKs of GDC-8264. In an ex vivo stimulation assay of whole blood, GDC-8264 rapidly and completely inhibited release of CCL4, a downstream marker of RIP1 pathway activation, indicating a potent pharmacological effect. Based on PK-PD modeling, the GDC-8264 half-maximal inhibitory concentration for the inhibition of CCL4 release was estimated to be 0.58 ng/mL. The favorable safety, PKs, and PDs of GDC-8264 support its further development for treatment of RIP1-driven diseases.

A quantitative systems pharmacological approach identified activation of JNK signaling pathway as a promising treatment strategy for refractory HER2 positive breast cancer.

HER2-positive breast cancer (BC) is a rapidly growing and aggressive BC subtype that predominantly affects younger women. Despite improvements in patient outcomes with anti-HER2 therapy, primary and/or acquired resistance remain a major clinical challenge. Here, we sought to use a quantitative systems pharmacological (QSP) approach to evaluate the efficacy of lapatinib (LAP), abemaciclib (ABE) and 5-fluorouracil (5-FU) mono- and combination therapies in JIMT-1 cells, a HER2+ BC cell line exhibiting intrinsic resistance to trastuzumab. Concentration-response relationships and temporal profiles of cellular viability were assessed upon exposure to single agents and their combinations. To quantify the nature and intensity of drug-drug interactions, pharmacodynamic cellular response models were generated, to characterize single agent and combination time course data. Temporal changes in cell-cycle phase distributions, intracellular protein signaling, and JIMT-1 cellular viability were quantified, and a systems-based protein signaling network model was developed, integrating  protein dynamics to drive the observed changes in cell viability. Global sensitivity analyses for each treatment arm were performed, to identify the most influential parameters governing cellular responses. Our QSP model was able to adequately characterize protein dynamic and cellular viability trends following single and combination drug exposure. Moreover, the model and subsequent sensitivity analyses suggest that the  activation of the stress pathway, through pJNK, has the greatest impact over the observed declines of JIMT-1 cell viability in vitro. These findings suggest that dual HER2 and CDK 4/6 inhibition may be a promising novel treatment strategy for refractory HER2+ BC, however, proof-of-concept in vivo studies are needed to further evaluate the combined use of these therapies.

Pharmacodynamic Models of Differential Bortezomib Signaling Across Several Cell Lines of Multiple Myeloma.

The heterogeneous polyclonal nature of multiple myeloma complicates the identification of protein biomarkers predictive of drug response. In this study, a pharmacodynamic systems modeling approach was used to link in vitro bortezomib exposure and myeloma cell death. The exposure-response was integrated through a network of important protein biomarker dynamics activated by bortezomib in four myeloma cell lines. The pharmacodynamic models reasonably characterized the protein and myeloma cell dynamics simultaneously following bortezomib (20 nM) treatment. The models were used to identify differences in pathway dynamics across cell lines from model-estimated protein biomarker turnover parameters and global sensitivity analyses. Additionally, a statistical correlation analysis between drug sensitivity and model-fitted protein activation profiles (i.e., cumulative area under the protein expression-time curves) supported the identification of shared biomarkers associated with sensitivity differences among the cell lines. Both types of analysis identified similar important proteins associated with bortezomib pharmacodynamics, such as phosphorylated Nuclear Factor kappa-light-chain-enhancer of activated B cells (pNFkappaB), phosphorylated protein kinase B (pAKT), and caspase-8 (Cas 8).

Network-Based Analysis of Bortezomib Pharmacodynamic Heterogeneity in Multiple Myeloma Cells.

The objective of this study is to evaluate the heterogeneity in pharmacodynamic response in four in vitro multiple myeloma cell lines to treatment with bortezomib, and to assess whether such differences are associated with drug-induced intracellular signaling protein dynamics identified via a logic-based network modeling approach. The in vitro pharmacodynamic-efficacy of bortezomib was evaluated through concentration-effect and cell proliferation dynamical studies in U266, RPMI8226, MM.1S, and NCI-H929 myeloma cell lines. A Boolean logic-based network model incorporating intracellular protein signaling pathways relevant to myeloma cell growth, proliferation, and apoptosis was developed based on information available in the literature and used to identify key proteins regulating bortezomib pharmacodynamics. The time-course of network-identified proteins was measured using the MAGPIX protein assay system. Traditional pharmacodynamic modeling endpoints revealed variable responses of the cell lines to bortezomib treatment, classifying cell lines as more sensitive (MM.1S and NCI-H929) and less sensitive (U266 and RPMI8226). Network centrality and model reduction identified key proteins (e.g., phosphorylated nuclear factor-κB, phosphorylated protein kinase B, phosphorylated mechanistic target of rapamycin, Bcl-2, phosphorylated c-Jun N-terminal kinase, phosphorylated p53, p21, phosphorylated Bcl-2-associated death promoter, caspase 8, and caspase 9) that govern bortezomib pharmacodynamics. The corresponding relative expression (normalized to 0-hour untreated-control cells) of proteins demonstrated a greater magnitude and earlier onset of stimulation/inhibition in cells more sensitive (MM.1S and NCI-H929) to bortezomib-induced cell death at 20 nM, relative to the less sensitive cells (U266 and RPMI8226). Overall, differences in intracellular signaling appear to be associated with bortezomib pharmacodynamic heterogeneity, and key proteins may be potential biomarkers to evaluate bortezomib responses.