Quantitative Systems Pharmacology Modeling of Avadomide-Induced Neutropenia Enables Virtual Clinical Dose and Schedule Finding Studies

Abstract

Avadomide is a cereblon E3 ligase modulator and a potent antitumor and immunomodulatory agent. Avadomide trials are challenged by neutropenia as a major adverse event and a dose-limiting toxicity. Intermittent dosing schedules supported by preclinical data provide a strategy to reduce frequency and severity of neutropenia; however, the identification of optimal dosing schedules remains a clinical challenge. Quantitative systems pharmacology (QSP) modeling offers opportunities for virtual screening of efficacy and toxicity levels produced by alternative dose and schedule regimens, thereby supporting decision-making in translational drug development. We formulated a QSP model to capture the mechanism of avadomide-induced neutropenia, which involves cereblon-mediated degradation of transcription factor Ikaros, resulting in a maturation block of the neutrophil lineage. The neutropenia model was integrated with avadomide-specific pharmacokinetic and pharmacodynamic models to capture dose-dependent effects. Additionally, we generated a disease-specific virtual patient population to represent the variability in patient characteristics and response to treatment observed for a diffuse large B-cell lymphoma trial cohort. Model utility was demonstrated by simulating the avadomide effect in the virtual population for various dosing schedules and determining the incidence of high-grade neutropenia, its duration, and the probability of recovery to low-grade neutropenia.

Applications of Quantitative Systems Pharmacology (QSP) in Drug Development for NAFLD and NASH and Its Regulatory Application

“…QSP modeling is a mechanism-based mathematical modeling approach that describes not only the pathophysiology of a disease, but also how pharmacological interventions can modify the mechanisms of pathophysiology ( 11 – 15 ). Simulated populations (aka virtual populations) provide a useful approach for capturing the pathophysiology of the disease inasmuch as they provide the ability to make predictions that account for inter-patient variability in both disease pathophysiology and clinical status ( 13 , 14 , 16 ). Predicted pharmacologic effects on simulated patients result from predicting compound exposure and pharmacodynamics (PD).…”

“…Weight loss has been shown to be an efficacious treatment approach, although patient compliance is challenging ( 107 ). Consistent with current QSP methodologies, we applied weight loss to our SimPops to further validate the simulated patients ( 13 , 14 , 16 ). Included as a submodel within NAFLDsym is the QSP model of body weight developed by Hall et al .…”