Version 1
: Received: 9 April 2024 / Approved: 10 April 2024 / Online: 10 April 2024 (10:53:56 CEST)
How to cite:
Mahahong, T.; Saleewong, T. Development of a Compartment Model to Study the Pharmacokinetics of Medical THC after Oral Administration. Preprints2024, 2024040699. https://doi.org/10.20944/preprints202404.0699.v1
Mahahong, T.; Saleewong, T. Development of a Compartment Model to Study the Pharmacokinetics of Medical THC after Oral Administration. Preprints 2024, 2024040699. https://doi.org/10.20944/preprints202404.0699.v1
Mahahong, T.; Saleewong, T. Development of a Compartment Model to Study the Pharmacokinetics of Medical THC after Oral Administration. Preprints2024, 2024040699. https://doi.org/10.20944/preprints202404.0699.v1
APA Style
Mahahong, T., & Saleewong, T. (2024). Development of a Compartment Model to Study the Pharmacokinetics of Medical THC after Oral Administration. Preprints. https://doi.org/10.20944/preprints202404.0699.v1
Chicago/Turabian Style
Mahahong, T. and Teerapol Saleewong. 2024 "Development of a Compartment Model to Study the Pharmacokinetics of Medical THC after Oral Administration" Preprints. https://doi.org/10.20944/preprints202404.0699.v1
Abstract
This paper presents a compartmental model aimed at investigating the pharmacokinetics of medical THC after oral administration. The model was developed to be multi-compartmental, describing the kinetics of THC and its metabolites in bodily tissues. Utilizing the law of mass action, the model was converted into ordinary differential equations (ODEs), illustrating the rate of concentration changes of THC and its metabolites in each compartment. Subsequently, we applied the nonstandard finite difference (NSFD) method to construct numerical solution schemes. These schemes were implemented in the MATLAB program, along with estimated pharmacokinetic rate constants. The results of the investigation demonstrate that the simulation curves depicting the plasma concentration-time profiles of THC and THC-OH closely resemble the actual data samples, indicating that this model accurately describes the pharmacokinetics of medical THC and its metabolites. Moreover, the model exhibits predictive capabilities regarding the pharmacokinetics of THC and its metabolites in various tissues. Consequently, the model serves as a valuable tool for enhancing our understanding of the pharmacokinetics of THC and its metabolites and for guiding adjustments to dosage and administration durations for oral medical THC products.
Computer Science and Mathematics, Computational Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
