Use of physiologically based pharmacokinetic modelling of new psychoactive substances

The use of new psychoactive substances (NPS) has been critically increasing. Synthetic cathinones (SC), a large class of NPS widely abused since the mid-2000s, are derivatives of cathinone, a naturally occurring ß-ketone amphetamine analogue found in the leaves of Catha edulis (khat) plant. Due to their ease of synthesis, as well to circumvent existing laws on controlled substances, and/or to enhance pharmacological activity, new SC have been constantly synthesized.

SC pharmacological effects may be similar to those of cocaine, amphetamine or ‘ecstasy’, can elicit powerful effects such as delusions, hallucinations and potentially dangerous behaviour, but those effects can vary depending upon the class. Hence, it presupposes that a certain amount of the substance reaches CNS at a certain rate, after being absorbed and distributed. The duration of the effects will depend not only on the pharmacological mechanism of interaction with the CNS, but also on the elimination of the NPS from the main blood stream. The science related to the kinetics of absorption, distribution and elimination (ADME) of substances in the human body is Pharmacokinetics (PK).

The conventional way to determine the PK of a new psychoactive compound in vivo is to conduct preclinical studies in animals. These experimental techniques are however costly, resource-intensive, lengthy, and most of all not suited for screening large number of NPS candidates. Moreover, clinical studies in humans with administration of NPS for PK purpose (even using micro dosing) can be seen as unethical and would be highly cost. Therefore, until experimental techniques are able to catch up to the current rate of NPS production, the bottleneck effect clearly prompts an alternative approach.

A potential solution lies in Physiologically Based PK (PBPK) modelling, making use of physiological information and physicochemical data as well as mathematical models to describe biological processes and physiological kinetic processes by series of differential equations, in order to portray the complex transport processes of a compound throughout the body and to simulate its in vivo performance.

PBPK models were applied to cathinone and mephedrone (the most used SC) and were verified with clinically observed results from healthy adults obtained in the literature, as shown in Figures below. One aim of the PBPK modelling effort was to obtain a mechanistic understanding of the difference in exposure and pharmacokinetics that was observed between NPS formulations. Moreover, NPS PBPK models were developed for healthy teenage (15-18 years old) and adult (18-64 years old) populations for other emerging SC: buphedrone, n-ethylhexedrone (NEH), 4-methyletcathinone (4-MEC), and flephedrone (4-FMC).

PBPK modeling and simulations were carried out in PK-Sim® (version 7.2.1 - Build 2). Absorption and distribution of compounds were also predicted from this software. Metabolism and excretion were predicted from online platform pkCSM (accessible from http://biosig.unimelb.edu.au/pkcsm/).

Physical-chemistry properties for NPS were estimated in MarvinSketch v.16.7.11.0 application, from Chemaxon (Academic Research License for Faculty of Pharmacy). Pharmacokinetic modelling and Non-Compartmental Analysis were performed using Phoenix® WinNonlin® 7.0 (Certara USA Inc, Princeton, NJ).