Population pharmacokinetic/pharmacodynamic modelling of the psychedelic experience induced by N,N-dimethyltryptamine
Emma Eckernäs (1), Christopher Timmermann (2), Daniel Röshammar (3), Michael Ashton (1)
(1) University of Gothenburg, Sweden, (2) Imperial College London, UK, (3) Pharmetheus, Sweden
Introduction/Objectives: N,N-dimethyltryptamine (DMT) is a naturally occurring, psychedelic compound that is believed to have potential as a treatment option in a number of psychiatric disorders. After intravenous administration, DMT is rapidly metabolized leading to a short half-life . This is believed to be mainly due to metabolism by monoamine oxidase (MAO) leading to formation of indole 3-acetic acid (IAA). For DMT to be orally available, co-administration with a MAO inhibitor is necessary to avoid complete metabolism in the GI and liver . It has previously been stated that the psychedelic effects of DMT closely follows the plasma concentrations . However, very little work has been done to thoroughly examine the pharmacokinetic (PK) properties of DMT and the relationship between plasma concentration and effect. This study aimed to characterize population PK of DMT as well as the population pharmacokinetic/pharmacodynamic (PKPD) relationship between DMT plasma concentration and psychedelic experience as measured through a subjective intensity rating.
Methods: Data from 13 healthy subjects having received one of four doses of DMT (7, 14, 18 or 20 mg) intravenously were modelled in NONMEM v7.4 using a population approach. Plasma samples had been obtained before and at different time points up to 60 minutes after DMT administration. Subjective psychedelic intensity was obtained by asking for ratings of intensity on a scale from 0-10 every minute during the first 20 minutes. The analysis was performed using a sequential approach where a population PK model was first established to describe plasma concentrations of DMT. The model was then extended to include the inactive metabolite IAA. Finally, the PKPD model was developed using an approach whereby population PK parameters were fixed but individual PK parameters were estimated simultaneously with PD parameters. The subjective ratings were handled as continuous data but with the addition of a logit transformation to restrict the predicted values between 0 and 10. The final model was used to simulate 100 subjects receiving a single intravenous DMT dose of either 7, 14 or 20 mg.
Results: A total of 92 and 87 plasma concentration observations of DMT and IAA respectively, as well as 273 subjective intensity ratings were included in this analysis. DMT plasma concentrations were well described by a two-compartment model with first-order elimination as a single elimination pathway leading to the formation of IAA. IAA observations were described by a one-compartment model with first-order elimination. The relationship between DMT plasma concentrations and subjective intensity ratings was best described by an effect compartment model with a sigmoid Emax response. Between subject variability was incorporated on clearance, volume of distribution for the metabolite as well as EC50, the plasma concentration of DMT needed to reach half of the maximal effect, and gamma, the slope factor describing the steepness of the PKPD relationship. DMT clearance was estimated to be 32 L/min with a between subject variability of 47%CV. EC50 was estimated at 92.5 nM with a between subject variability of 38%CV. For the simulated subjects, the median maximum psychedelic intensity score achieved was 4, 8 and 9 for the 7, 14 and 20 mg dose, respectively. The proportion of patients achieving an intensity score of at least 5 or higher increased from 39 to 97 and 100% across the 7, 14 and 20 mg doses
Conclusions: A PKPD model was constructed that accurately describes the observed PK and psychedelic effects of DMT in this study. Even though this was a relatively small study this is a first step towards gaining an increased understanding of the PKPD characteristics of DMT. We believe that this model can be useful in predicting suitable doses in a clinical dose finding setting based on the desired intensity of the subjective experience. In addition, the variability observed in the data highlights the need for larger studies with the ability to investigate potential covariates and causes for these observations.
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