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Clinical Trial
. 2021 Jan;10(1):30-39.
doi: 10.1002/psp4.12565. Epub 2020 Dec 30.

A Physiologically Based Pharmacokinetic Model to Predict Potential Drug-Drug Interactions and Inform Dosing of Acumapimod, an Oral p38 MAPK Inhibitor

Affiliations
Clinical Trial

A Physiologically Based Pharmacokinetic Model to Predict Potential Drug-Drug Interactions and Inform Dosing of Acumapimod, an Oral p38 MAPK Inhibitor

Alex Agyemang et al. CPT Pharmacometrics Syst Pharmacol. 2021 Jan.

Abstract

Acumapimod, an investigational oral p38 mitogen-activated protein kinase inhibitor for treatment during severe acute exacerbations of chronic obstructive pulmonary disease, is metabolized primarily by cytochrome P450 3A4 (CYP3A4) and is a P-glycoprotein (P-gp) substrate. Concerns about drug-drug interactions (DDIs) have meant patients receiving drugs that inhibit CYP3A4 were ineligible for acumapimod trials. We report on how 2 acumapimod clinical DDI studies and a physiologically-based pharmacokinetic (PBPK) model assessing how co-administration of a weak (azithromycin) and strong (itraconazole) CYP3A4 inhibitor affected acumapimod systemic exposure, informed decision making and supported concomitant use of CYP3A4 and P-gp inhibitors. Studies MBCT102 and MBCT103, respectively, demonstrated that co-administration of azithromycin or itraconazole had no clinically meaningful impact on acumapimod pharmacokinetics. Findings were consistent with PBPK model results. Safety profiles were similar when acumapimod was co-administered with azithromycin or itraconazole. These studies highlight the value of PBPK modeling in drug development, and its potential to inform DDI investigations.

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Conflict of interest statement

A.A. reports personal fees from Mereo BioPharma, Takeda, and Pfizer outside the submitted work. C.F. is an employee of ICON Clinical Research. W.M., and J.P. are employees of Mereo BioPharma.

Figures

Figure 1
Figure 1
Drug–drug interaction study designs. Study treatment and pharmacokinetic sampling for periods 1 and 2 of azithromycin (study MBCT102) (a) and itraconazole (study MBCT103) (b) treatment.
Figure 2
Figure 2
Simulated and observed (data points; from study MBCT102) mean plasma concentration‒time profiles of acumapimod. After a single oral dose (14 mg) in the absence (a and c) and presence (b and d) of multiple oral daily doses of azithromycin (500 mg for 3 days). In a and b, model 1 was used; in c and d, model 2 was used. The grey lines represent the outcomes of simulated individual trials (10 × 16 virtual individuals) and the black line is the mean data for the simulated population (n = 160). The grey dashed line represents the 95th and 5th percentile of the simulated data. It is not possible to see the early phase of the profile (between 0 and 24 hours) due to the scale of the x‐axis in this figure.
Figure 3
Figure 3
Simulated plasma concentration‒time profiles of acumapimod. After a single oral dose (75 mg) in the presence (dashed line) and absence (solid line) of multiple oral doses of itraconazole oral solution (200 mg q.d. for 20 days), using model 1 (a), and model 2 (b). The grey lines represent the outcomes of simulated individual trials (10 × 10 virtual individuals) and the solid/dashed black line is the mean data for the simulated population (n = 100).
Figure 4
Figure 4
Simulated plasma concentration‒time profiles of acumapimod. After a single oral dose (75 mg) in the presence (dashed line) and absence (solid line) of multiple oral doses of verapamil (240 mg q.d. for 20 days) (a) or itraconazole oral solution (200 mg q.d. for 20 days) (b). Model 1 was used. The grey lines represent the outcomes of simulated individual trials (10 × 10 virtual individuals), and the solid/dashed black line is the mean data for the simulated population (n = 100). It is not possible to see the early phase of the profile (between 0 and 96 hours) due to the scale of the x‐axis in the figure.

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