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Toxicokinetic studies and translational mechanistic modeling of New Psychoactive Substances using the Synthetic Cannabinoid Cumyl-5F-P7AICA.

Subject Area Toxicology, Laboratory Medicine
Term since 2022
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 508380150
 
A major aim of the proposed project is a comprehensive characterization of the toxicokinetic properties of the synthetic cannabinoid cumyl-5F-P7AICA in a pig model already established for toxicokinetic studies. Following inhalative administration and preparation of the collected samples, blood-/serum-/exhaled breath- and adipose tissue- concentration-time profiles should be established and the concentrations of the substance in the organs and tissues at the time of death should be determined. Based on these data, a toxicokinetic model for the cannabinoid should first be established using allometric scaling. In order to ensure a comprehensive transferability of the animal experimental findings to the human situation, an extended modeling in the sense of a translational approach or a proof-of-concept should be carried out using further cannabinoids (with different core structures) having already been investigated. With additional consideration of compound-specific parameters such as protein binding and lipophilicity as well as certain transport proteins and degrading enzymes, a physiology-based toxicokinetics model (PBTK) should thus be developed and transferred to humans by means of allometric scaling. In this way, the validity of the newly established PBTK modeling should be validated in comparison with the modeling developed in the preliminary work on the substances JWH-210, RCS-4 and THC.Another aim is the determination of the postmortem stability of cumyl-5F-P7AICA under different ambient conditions. For this purpose, the animals should be stored for three days at room temperature in the open air or in water. After 24 hours, different organ and tissue specimens as well as samples of different body fluids should be collected and analyzed.
DFG Programme Research Grants
Co-Investigator Professor Dr. Peter Schmidt
 
 

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