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Clinical Trial
. 2025 Feb;14(2):376-388.
doi: 10.1002/psp4.13282. Epub 2024 Nov 26.

MDMA pharmacokinetics: A population and physiologically based pharmacokinetics model-informed analysis

Affiliations
Clinical Trial

MDMA pharmacokinetics: A population and physiologically based pharmacokinetics model-informed analysis

Marilyn A Huestis et al. CPT Pharmacometrics Syst Pharmacol. 2025 Feb.

Abstract

Midomafetamine (3,4-methylenedioxymethamphetamine [MDMA]) is under the U.S. Food and Drug Administration review for treatment of post-traumatic stress disorder in adults. MDMA is metabolized by CYP2D6 and is a strong inhibitor of CYP2D6, as well as a weak inhibitor of renal transporters MATE1, OCT1, and OCT2. A pharmacokinetic phase I study was conducted to evaluate the effects of food on MDMA pharmacokinetics. The results of this study, previously published pharmacokinetic data, and in vitro data were combined to develop and verify MDMA population pharmacokinetic and physiologically based pharmacokinetic models. The food effect study demonstrated that a high-fat/high-calorie meal did not alter MDMA plasma concentrations, but delayed Tmax. The population pharmacokinetic model did not identify any clinically meaningful covariates, including age, weight, sex, race, and fed status. The physiologically based pharmacokinetic model simulated pharmacokinetics for the proposed 120 and 180 mg MDMA HCl clinical doses under single- and split-dose (2 h apart) conditions, indicating minor differences in overall exposure, but lower AUC within the first 4 h and delayed Tmax when administered as a split dose compared to a single dose. The physiologically based pharmacokinetic model also investigated the drug-drug interaction magnitude by varying the fraction metabolized by a representative CYP2D6 substrate (atomoxetine) and evaluated inhibition of renal transporters. The simulations confirm MDMA is a potent CYP2D6 inhibitor, but likely has no meaningful impact on the pharmacokinetics of drugs sensitive to renal transport. This model-informed drug development approach was employed to inform drug-drug interaction potential and predict pharmacokinetics of clinically relevant dosing regimens of MDMA.

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Conflict of interest statement

MAH, WBS, AV, CL, and RB received payment from Lykos Therapeutics for support with the research. AV is a contractor of Lykos Therapeutics. NBM is an employee of and has stock/stock options in Lykos Therapeutics. BY‐K is an employee of and has stock/stock options in Lykos Therapeutics where she is the Chief Scientific Officer, was previously an employee of MAPS, and has received support from Lykos Therapeutics and MAPS for attending meetings/travel. All other authors declared no competing interests in this work. No authors were compensated for authorship activities associated with this article.

Figures

FIGURE 1
FIGURE 1
Pharmacokinetic studies and models' overview. HCl, hydrochloride; MDA, 3,4‐methylenedioxyamphetamine; MDMA, 3,4‐methylenedioxymethamphetamine; N, number of participants in analysis population; PBPK, physiologically based pharmacokinetic; PK, pharmacokinetic; PopPK, population pharmacokinetic.
FIGURE 2
FIGURE 2
PopPK Model: Covariate effects on (a) MDMA and (b) MDA. For all covariate scenarios, all other covariates were maintained at values for a reference individual. The reference individual was defined as a white male from the NIDA study population, weighing 70 kg, aged 25 years, with baseline creatine clearance of 113 mL/min, and fed a light meal. Left side of the plot: Number to the right of body weight corresponds to the 5th and 95th percentiles of the population in kg. Numbers to the right of categorical covariates correspond to numbers of subjects in each category (Nonreference: Reference). Right side of the plot. Values in boxes represent data shown in the graph, summarizing the median and 95% confidence interval for AUC (left box) and C max (right box). AUC refers to AUC0–44. AUC, area under the plasma concentration–time curve; CI, confidence interval; C max, maximum observed plasma concentration; CV, coefficient of variation; MDA, 3,4‐methylenedioxyamphetamine; MDMA, 3,4‐methylenedioxymethamphetamine.
FIGURE 3
FIGURE 3
PBPK model: Simulated MDMA exposure following single and split dose of MDMA. (a) MDMA AUC from 0 to 44 h post‐first dose; (b) MDMA AUC from 0 to 4 h post‐first dose; (c) MDMA C max. Box plot area, dark line, and whiskers represent the interquartile range, median, and range of simulated values; black circles are outlier values. AUC, area under the curve; C max, maximum observed concentration; MDA, 3,4‐methylenedioxyamphetamine; MDMA, 3,4‐methylenedioxymethamphetamine.
FIGURE 4
FIGURE 4
PBPK model: Predicted change in AUC and C max for a theoretical substrate over a range of fmCYP2D6 values following split dose of MDMA. Depicted are simulated AUC (teal) and C max (orange) ratios over the range of fmCYP2D6 = 0.05 to 0.95 following a single oral dose administered with the second dose of a split 180 mg dose of MDMA HCl (2 h interval between doses). The dashed horizontal lines represent the FDA cutoff values for a weak (ratio ≥1.25), moderate (2≤ ratio <5), or strong (ratio ≥5) interaction. AUC, area under the curve; C max, maximum observed concentration; fmCYP2D6, fraction metabolized by CYP2D6; GMR, geometric means ratio; MDMA, 3,4‐methylenedioxymethamphetamine.
FIGURE 5
FIGURE 5
PBPK Model: Simulated metformin exposure in the absence of MDMA and with the first dose of a split dose of 180 mg MDMA HCl. (a) Metformin AUC from 0 to 72 h post‐first dose and (b) metformin C max. Box plot area, dark line, and whiskers represent the interquartile range, median, and range of simulated values; symbols are outlier values. AUC, area under the curve; C max, maximum observed concentration; K i , inhibitor constant; MDMA, 3,4‐methylenedioxymethamphetamine.

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