CFPD-PK simulation of inhaled Delta-9-tetrahydrocannabinol aerosol dynamics: Transport, deposition, and translocation in a mouth-to-G10 subject-specific human airway

• Published in: Journal of aerosol science Vol. 177; p. 106334
• Main Authors: Sperry, Ted, Feng, Yu, Song, Chen, Shi, Zhiqiang
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-03-2024
• Subjects: Computational fluid particle dynamics (CFPD); Inhalation dosimetry; Medicinal Delta-9-tetrahydrocannabinol (THC); Pharmacokinetics (PK); Puff waveforms; Puff waveforms; Medicinal Delta-9-tetrahydrocannabinol (THC); Pharmacokinetics (PK); Computational fluid particle dynamics (CFPD); Inhalation dosimetry
• ISSN: 0021-8502; 1879-1964
• DOI: 10.1016/j.jaerosci.2024.106334

Medical cannabis is increasingly used as an alternative therapy for various conditions, including chronic pain, multiple sclerosis, epilepsy, and cancer-related symptoms. However, it is crucial to ensure that patients receive the intended dose of tetrahydrocannabinol (THC) from inhaled cannabis for optimal therapeutic effect without overdose risk. This requires a comprehensive understanding of the factors that influence the pharmacokinetics (PKs) of THC in the respiratory system. However, accurate estimation of lung dosimetry and blood concentration of inhaled THC remains challenging partially because the influence of diversified patient-specific puff patterns on inhaled THC transport, deposition, and translocation is still not well quantified. To address the knowledge gap mentioned above, this study employed a hybrid computational fluid-particle dynamics (CFPD) and PK model to evaluate factors that influence delivered doses of THC to the human respiratory system and the resultant THC-plasma concentration-time profile. Specifically, this study compared multiple puff waveforms for inhalation-holding-exhalation (IHE) with total puff volumes from 55 to 82 ml for 2 or 3 s, hold durations from 0 to 5 s, and three puff waveforms (i.e., square, sinusoidal, and realistic). THC deposition in the airways was recorded during all phases for each case using either 452,849 particles per second for the 1.128-μm monodisperse cases or 399,866 particles per second for the polydisperse cases, with the mass median aerodynamic diameter (MMAD) of 1.128 μm. Pulmonary air-THC particle flow transport dynamics, THC particle deposition data, and THC vapor absorption were predicted using CFPD for four airway regions, then scaled by region-specific bioavailability factors. The deposited THC mass in airway regions represents the initial mass entering a 3-compartment PK model, to predict the THC-plasma concentration-time profiles. The CFPD-PK results revealed significant variability in THC transport, deposition, and plasma concentration based on IHE factors. Specifically, larger puff volumes and longer holding times enhanced THC deposition in deeper airways and increased THC-plasma concentrations. Realistic transient puff waveforms predicted higher particle deposition and THC-plasma concentrations than simplified square waveforms. Polydisperse particle distributions show more realistic deposition patterns than monodisperse particle simulations. This study provides insights into the complexity of THC inhalation therapy, emphasizing the importance of considering individualized puff patterns and realistic particle size distributions in accurately predicting therapeutic outcomes, which is highly related to THC deposition in the lung and THC plasma concentration. These findings and the CFPD-PK modeling framework offer guidance for clinicians in prescribing personalized THC dosages, support regulatory science in evaluating inhalation devices, and contribute to ongoing research aimed at optimizing THC delivery for maximum therapeutic effectiveness while minimizing potential overdose risks.
•A CFPD-PK model is used to investigate puff waveform influence on THC transport and translocation.•Longer hold times enhance THC lung deposition and increase THC blood levels.•Larger puff volumes and longer puff duration boost THC blood levels and respiratory deposition.•Realistic puff waveforms outperform square ones in predicting THC transport and effects.•Polydisperse particles show more accurate THC deposition patterns than monodisperse.