Human Pharmacokinetics of LYS006, an Oral Leukotriene A4 Hydrolase Inhibitor Displaying Target-Mediated Drug Disposition.

LYS006 is a potent leukotriene A4 hydrolase inhibitor currently in clinical development for long-term treatment of various neutrophil-driven inflammatory conditions. Here, we present pharmacokinetics from the first-in-human study with complementary metabolism and transporter profiling data. The randomized first-in-human study included nine cohorts receiving 5-2*100 mg of LYS006 or placebo, a crossover food-effect part, and a multiple-dose part consisting of two fasted (5 mg and 15 mg once daily) and three fed cohorts (20-80 mg twice a day) of LYS006 or placebo. LYS006 and metabolites were assessed in plasma and urine, and transporters involved in LYS006 disposition were analyzed in vitro. Systemic plasma exposure increased with dose; steady-state exposure was dose proportional up to 40 mg twice a day. Steady state was achieved after ∼3 days, with mean accumulation of 2.1-fold for 5 mg once daily and ≤1.4-fold for all higher doses. Despite limited accumulation, a long terminal half-life (T1/2) was observed. The long T1/2 and saturable binding to blood cells, which causes a highly nonlinear blood-to-plasma distribution, reflect a strong impact of target binding on drug distribution at lower concentrations. Skin biopsy and blister fluid concentration data indicated saturable binding in the former but not the latter, suggesting saturable binding in tissues beyond blood. Major excretion of LYS006 (∼90% of dose) through urine at steady state triggered renal transporter investigations that identified LYS006 as a substrate of organic anion transporter (OAT)3, OAT4, breast cancer resistance protein, and multidrug resistance-associated protein 4. Seven metabolites were identified in human plasma and urine, comprising only 4% of the dose recovered in urine at steady state. SIGNIFICANCE STATEMENT: Pharmacokinetic data from a first-in-human study combined with in vitro work support dose and regimen selection for patient studies with LYS006 and provide guidance on drug interaction investigations and other clinical pharmacology work needed for further development. Mass balance information at steady state without the use of a radiolabel, skin concentrations, and identification of the major clearance pathway, as well as the transporters driving elimination, make this a particularly conclusive early study despite nonlinear pharmacokinetics impacted by target binding.

Integration of Pharmacokinetics, Pharmacodynamics, Safety, and Efficacy into Model-Informed Dose Selection in Oncology First-in-Human Study: A Case of Roblitinib (FGF401).

Model-informed dose selection has been drawing increasing interest in oncology early clinical development. The current paper describes the example of FGF401, a selective fibroblast growth factor receptor 4 (FGFR4) inhibitor, in which a comprehensive modeling and simulation (M&S) framework, using both pharmacometrics and statistical methods, was established during its first-in-human clinical development using the totality of pharmacokinetics (PK), pharmacodynamic (PD) biomarkers, and safety and efficacy data in patients with cancer. These M&S results were used to inform FGF401 dose selection for future development. A two-compartment population PK (PopPK) model with a delayed 0-order absorption and linear elimination adequately described FGF401 PK. Indirect PopPK/PD models including a precursor compartment were independently established for two biomarkers: circulating FGF19 and 7α-hydroxy-4-cholesten-3-one (C4). Model simulations indicated a close-to-maximal PD effect achieved at the clinical exposure range. Time-to-progression was analyzed by Kaplan-Meier method which favored a trough concentration (Ctrough )-driven efficacy requiring Ctrough above a threshold close to the drug concentration producing 90% inhibition of phospho-FGFR4. Clinical tumor growth inhibition was described by a PopPK/PD model that reproduced the dose-dependent effect on tumor growth. Exposure-safety analyses on the expected on-target adverse events, including elevation of aspartate aminotransferase and diarrhea, indicated a lack of clinically relevant relationship with FGF401 exposure. Simulations from an indirect PopPK/PD model established for alanine aminotransferase, including a chain of three precursor compartments, further supported that maximal target inhibition was achieved and there was a lack of safety-exposure relationship. This M&S framework supported a dose selection of 120 mg once daily fasted or with a low-fat meal and provides a practical example that might be applied broadly in oncology early clinical development.

Contribution of machine learning to tumor growth inhibition modeling for hepatocellular carcinoma patients under Roblitinib (FGF401) drug treatment.

Machine learning (ML) opens new perspectives in identifying predictive factors of efficacy among a large number of patients' characteristics in oncology studies. The objective of this work was to combine ML with population pharmacokinetic/pharmacodynamic (PK/PD) modeling of tumor growth inhibition to understand the sources of variability between patients and therefore improve model predictions to support drug development decisions. Data from 127 patients with hepatocellular carcinoma enrolled in a phase I/II study evaluating once-daily oral doses of the fibroblast growth factor receptor FGFR4 kinase inhibitor, Roblitinib (FGF401), were used. Roblitinib  PKs was best described by a two-compartment model with a delayed zero-order absorption and linear elimination. Clinical efficacy using the longitudinal sum of the longest lesion diameter data was described with a population PK/PD model of tumor growth inhibition including resistance to treatment. ML, applying elastic net modeling of time to progression data, was associated with cross-validation, and allowed to derive a composite predictive risk score from a set of 75 patients' baseline characteristics. The two approaches were combined by testing the inclusion of the continuous risk score as a covariate on PD model parameters. The score was found as a significant covariate on the resistance parameter and resulted in 19% reduction of its variability, and 32% variability reduction on the average dose for stasis. The final PK/PD model was used to simulate effect of patients' characteristics on tumor growth inhibition profiles. The proposed methodology can be used to support drug development decisions, especially when large interpatient variability is observed.

Co-Targeting of MDM2 and CDK4/6 with Siremadlin and Ribociclib for the Treatment of Patients with Well-Differentiated or Dedifferentiated Liposarcoma: Results from a Proof-of-Concept, Phase Ib Study.

PURPOSE: Well-differentiated (WDLPS) and dedifferentiated (DDLPS) liposarcoma are characterized by co-amplification of the murine double minute-2 (MDM2) and cyclin-dependent kinase-4 (CDK4) oncogenes. Siremadlin, a p53-MDM2 inhibitor, was combined with ribociclib, a CDK4/6 inhibitor, in patients with locally advanced/metastatic WDLPS or DDLPS who had radiologically progressed on, or despite, prior systemic therapy. PATIENTS AND METHODS: In this proof-of-concept, phase Ib, dose-escalation study, patients received siremadlin and ribociclib across different regimens until unacceptable toxicity, disease progression, and/or treatment discontinuation: Regimen A [4-week cycle: siremadlin once daily (QD) and ribociclib QD (2 weeks on, 2 weeks off)], Regimen B [3-week cycle: siremadlin once every 3 weeks; ribociclib QD (2 weeks on, 1 week off)], and Regimen C [4-week cycle: siremadlin once every 4 weeks; ribociclib QD (2 weeks on, 2 weeks off)]. The primary objective was to determine the maximum tolerated dose (MTD) and/or recommended dose for expansion (RDE) of siremadlin plus ribociclib in one or more regimens. RESULTS: As of October 16, 2019 (last patient last visit), 74 patients had enrolled. Median duration of exposure was 13 (range, 1-174) weeks. Dose-limiting toxicities occurred in 10 patients, most of which were Grade 3/4 hematologic events. The RDE was siremadlin 120 mg every 3 weeks plus ribociclib 200 mg QD (Regimen B). Three patients achieved a partial response, and 38 achieved stable disease. One patient (Regimen C) died as a result of treatment-related hematotoxicity. CONCLUSIONS: Siremadlin plus ribociclib demonstrated manageable toxicity and early signs of antitumor activity in patients with advanced WDLPS or DDLPS.

A framework to guide dose & regimen strategy for clinical drug development.

Optimizing new drug therapies remains a challenge for clinical development, despite the use of ever more sophisticated quantitative methodologies. Although conceptually simple, the idea of finding the right treatment at the right dose for the right patient to ensure an appropriate balance of risks and benefits is challenging and requires a multidisciplinary approach. In this paper, we present a framework developed as a tool for organizing knowledge and facilitating collaboration in development teams.

Pharmacokinetic-pharmacodynamic guided optimisation of dose and schedule of CGM097, an HDM2 inhibitor, in preclinical and clinical studies.

BACKGROUND: CGM097 inhibits the p53-HDM2 interaction leading to downstream p53 activation. Preclinical in vivo studies support clinical exploration while providing preliminary evidence for dosing regimens. This first-in-human phase I study aimed at assessing the safety, MTD, PK/PD and preliminary antitumor activity of CGM097 in advanced solid tumour patients (NCT01760525). METHODS: Fifty-one patients received oral treatment with CGM097 10-400 mg 3qw (n = 31) or 300-700 mg 3qw 2 weeks on/1 week off (n = 20). Choice of dose regimen was guided by PD biomarkers, and quantitative models describing the effect of CGM097 on circulating platelet and PD kinetics. RESULTS: No dose-limiting toxicities were reported in any regimens. The most common treatment-related grade 3/4 AEs were haematologic events. PK/PD models well described the time course of platelet and serum GDF-15 changes, providing a tool to predict response to CGM097 for dose-limiting thrombocytopenia and GDF-15 biomarker. The disease control rate was 39%, including one partial response and 19 patients in stable disease. Twenty patients had a cumulative treatment duration of >16 weeks, with eight patients on treatment for >32 weeks. The MTD was not determined. CONCLUSIONS: Despite delayed-onset thrombocytopenia frequently observed, the tolerability of CGM097 appears manageable. This study provided insights on dosing optimisation for next-generation HDM2 inhibitors. TRANSLATIONAL RELEVANCE: Haematologic toxicity with delayed thrombocytopenia is a well-known on-target effect of HDM2 inhibitors. Here we have developed a PK/PD guided approach to optimise the dose and schedule of CGM097, a novel HDM2 inhibitor, using exposure, platelets and GDF-15, a known p53 downstream target to predict patients at higher risk to develop thrombocytopenia. While CGM097 had shown limited activity, with disease control rate of 39% and only one patient in partial response, the preliminary data from the first-in-human escalation study together with the PK/PD modeling provide important insights on how to optimize dosing of next generation HDM2 inhibitors to mitigate hematologic toxicity.

Translational Modeling of Anticancer Efficacy to Predict Clinical Outcomes in a First-in-Human Phase 1 Study of MDM2 Inhibitor HDM201.

We report on a retrospective model-based assessment of the predictive value of translating antitumor drug activity from in vivo experiments to a phase I clinical study in cancer patients treated with the MDM2 inhibitor, HDM201. Tumor growth inhibition models were developed describing the longitudinal tumor size data in human-derived osteosarcoma xenograft rats and in 96 solid tumor patients under different HDM201 treatment schedules. The model structure describing both datasets captures the delayed drug effect on tumor growth via a series of signal transduction compartments, including a resistance component. The models assumed a drug-killing effect on both sensitive and resistant cells and parameterized to estimate two tumor static plasma drug concentrations for sensitive (TSCS) and resistant cells (TSCR). No change of TSCS and TSCR with schedule was observed, implying that antitumor activity for HDM201 is independent of treatment schedule. Preclinical and clinical model-derived TSCR were comparable (48 ng/mL vs. 74 ng/mL) and demonstrating TSCR as a translatable metric for antitumor activity in clinic. Schedule independency was further substantiated from modeling of clinical serum growth differentiation factor-15 (GDF-15) as a downstream marker of p53 pathway activation. Equivalent cumulative induction of GDF-15 was achieved across schedules when normalized to an equivalent total dose. These findings allow for evaluation of optimal dosing schedules by maximizing the total dose per treatment cycle while mitigating safety risk with periods of drug holiday. This approach helped guide a phase I dose escalation study in the selection of an optimal dose and schedule for HDM201.

Dose and Schedule Determine Distinct Molecular Mechanisms Underlying the Efficacy of the p53-MDM2 Inhibitor HDM201.

Activation of p53 by inhibitors of the p53-MDM2 interaction is being pursued as a therapeutic strategy in p53 wild-type cancers. Here, we report distinct mechanisms by which the novel, potent, and selective inhibitor of the p53-MDM2 interaction HDM201 elicits therapeutic efficacy when applied at various doses and schedules. Continuous exposure of HDM201 led to induction of p21 and delayed accumulation of apoptotic cells. By comparison, high-dose pulses of HDM201 were associated with marked induction of PUMA and a rapid onset of apoptosis. shRNA screens identified PUMA as a mediator of the p53 response specifically in the pulsed regimen. Consistent with this, the single high-dose HDM201 regimen resulted in rapid and marked induction of PUMA expression and apoptosis together with downregulation of Bcl-xL in vivo Knockdown of Bcl-xL was identified as the top sensitizer to HDM201 in vitro, and Bcl-xL was enriched in relapsing tumors from mice treated with intermittent high doses of HDM201. These findings define a regimen-dependent mechanism by which disruption of MDM2-p53 elicits therapeutic efficacy when given with infrequent dosing. In an ongoing HDM201 trial, the observed exposure-response relationship indicates that the molecular mechanism elicited by pulse dosing is likely reproducible in patients. These data support the clinical comparison of daily and intermittent regimens of p53-MDM2 inhibitors.Significance: Pulsed high doses versus sustained low doses of the p53-MDM2 inhibitor HDM201 elicit a proapoptotic response from wild-type p53 cancer cells, offering guidance to current clinical trials with this and other drugs that exploit the activity of p53. Cancer Res; 78(21); 6257-67. ©2018 AACR.

Safety and pharmacokinetics of olokizumab, an anti-IL-6 monoclonal antibody, administered to healthy male volunteers: A randomized phase I study.

Interleukin-6 (IL-6) is implicated in the pathophysiology of several inflammatory conditions. Olokizumab, a humanized anti-IL-6 monoclonal antibody, selectively blocks the final assembly of the IL-6 signaling complex. A randomized, double-blind, placebo-controlled, phase I dose-escalation study assessed the safety and tolerability of escalating single doses of olokizumab administered intravenously (iv) or subcutaneously (sc) to 67 healthy male volunteers. The pharmacokinetics, pharmacodynamics and immunogenicity of olokizumab were also assessed. Olokizumab was tolerated at doses up to 3.0 mg/kg sc and 10.0 mg/kg iv; the maximum tolerated dose was not reached. No serious adverse events or withdrawals as a result of treatment-emergent adverse events were reported. Pharmacokinetic analysis showed that both maximum serum concentration and area under the concentration-time curve increased linearly with increasing dose. Mean terminal half-life was 31.5 days (standard deviation 12.4 days). The bioavailability of the sc doses ranged from 84.2% to 92.5%. Rapid decreases in C-reactive protein concentrations were observed, with no dose dependency.

Pharmacokinetic parameters estimation using adaptive Bayesian P-splines models.

In preclinical and clinical experiments, pharmacokinetic (PK) studies are designed to analyse the evolution of drug concentration in plasma over time i.e. the PK profile. Some PK parameters are estimated in order to summarize the complete drug's kinetic profile: area under the curve (AUC), maximal concentration (C(max)), time at which the maximal concentration occurs (t(max)) and half-life time (t(1/2)).Several methods have been proposed to estimate these PK parameters. A first method relies on interpolating between observed concentrations. The interpolation method is often chosen linear. This method is simple and fast. Another method relies on compartmental modelling. In this case, nonlinear methods are used to estimate parameters of a chosen compartmental model. This method provides generally good results. However, if the data are sparse and noisy, two difficulties can arise with this method. The first one is related to the choice of the suitable compartmental model given the small number of data available in preclinical experiment for instance. Second, nonlinear methods can fail to converge. Much work has been done recently to circumvent these problems (J. Pharmacokinet. Pharmacodyn. 2007; 34:229-249, Stat. Comput., to appear, Biometrical J., to appear, ESAIM P&S 2004; 8:115-131).In this paper, we propose a Bayesian nonparametric model based on P-splines. This method provides good PK parameters estimation, whatever be the number of available observations and the level of noise in the data. Simulations show that the proposed method provides better PK parameters estimations than the interpolation method, both in terms of bias and precision. The Bayesian nonparametric method provides also better AUC and t(1/2) estimations than a correctly specified compartmental model, whereas this last method performs better in t(max) and C(max) estimations.We extend the basic model to a hierarchical one that treats the case where we have concentrations from different subjects. We are then able to get individual PK parameter estimations. Finally, with Bayesian methods, we can get easily some uncertainty measures by obtaining credibility sets for each PK parameter.