Facebook Twitter Instagram
    • Home
    • About Journal
      • Aim and Scope
      • Editorial Board
      • Indexing Info
      • Contact Us
    • Browse Issues
      • Articles in Press
      • Current Issue
      • Past Issues
    • For Authors
      • Instructions to Authors
      • Article Processing Charges
      • Submit your article
      • Downloads
    Facebook Twitter Instagram
    Pharmacognosy Communications
    • Home
    • About Journal
      • Aim and Scope
      • Editorial Board
      • Indexing Info
      • Contact Us
    • Browse Issues
      • Articles in Press
      • Current Issue
      • Past Issues
    • For Authors
      • Instructions to Authors
      • Article Processing Charges
      • Submit your article
      • Downloads
    Pharmacognosy Communications
    retyeyutreu
    Original Article

    Inhalation Absorption Prediction (IAP) Model for Predicting Medicinal Cannabis Phytochemical Pharmacokinetics

    wadmin1By wadmin1June 1, 2019Updated:August 10, 2021No Comments2 Mins Read
    Facebook Twitter Pinterest LinkedIn Tumblr WhatsApp Email
    Share
    Facebook Twitter LinkedIn WhatsApp Pinterest Email

    Kimber Wise1,2, Harsharn Gill1, Jamie Selby-Pham2
    1School of Science, RMIT University, Bundoora VIC 3083, AUSTRALIA.
    2Nutrifield, Sunshine West VIC 3020, AUSTRALIA.

    Pharmacognosy Communications,2019,9,3,85-90.
    DOI:10.5530/pc.2019.3.18
    Published:June 2019
    Type:Original Article

    ABSTRACT
    Introduction: The medicinal benefits from inhalation of Cannabis sativa phytochemicals have been extensively reported. Whilst in-silico models are available for prediction of phytochemical pharmacokinetics post-ingestion, no models are available to accurately predict inhalation pharmacokinetics. Therefore, the aim of this study was to explore the relationship between phytochemical physicochemical properties and inhalation pharmacokinetics and to develop an in-silico model for predicting the time of maximal compound concentration in plasma (Tmax) and compound elimination half-life (T½), following inhalation. Methods: A training set of compound pharmacokinetic
    data was collated from previous publications and compared to physicochemical parameters using regression analyses. Physicochemical parameters that correlated with Tmax and T½ were combined to develop a statistical model, which constructs functional fingerprints predicting compound concentrations in plasma post inhalation. Predicted functional fingerprints for three cannabis bioactive compounds were constructed and biomatched against previously reported physiological effects. Results: Inhalation Tmax was predicted (r2 = 0.84) by compound volume (Vol), topological surface area (TPSA) and molecular weight (MW), whilst T½ was predicted (r2 = 0.87) by molecular weight, volume and number of rotatable bonds (nrot). The resulting inhalation absorption prediction (IAP) model was achieved by combining Tmax and T½ predictions. The IAP model was applied to cannabis metabolites which accurately predicted decay functions in-vivo and biomatching with associated physiological effects. Conclusion: The IAP model was applied successfully to cannabis phytochemicals to explore the pharmacokinetics underpinning their medicinal effects. This study demonstrates the utility of the IAP model and highlights its applicability during the investigation of medicinal plants and their modes of action.
    Key words: Biomatching, Pharmacognosy, Functional fingerprint, Medicinal plants.
    Download PDF
    Share. Facebook Twitter Pinterest LinkedIn Tumblr WhatsApp Email
    About Journal
    About Journal

    Pharmacognosy Communications [Phcog Commn.] is a quarterly journal published by Phcog.Net. It is a peer reviewed journal aiming to publish high quality original research articles, methods, techniques and evaluation reports, critical reviews, short communications, commentaries and editorials of all aspects of medicinal plant research. The journal is aimed at a broad readership, publishing articles on all aspects of pharmacognosy, and related fields. The journal aims to increase understanding of pharmacognosy as well as to direct and foster further research through the dissemination of scientific information by the publication of manuscripts. The submission of original contributions in all areas of pharmacognosy are welcome.
    Indexed and Abstracted in : Chemical Abstracts, Excerpta Medica / EMBASE, Google Scholar, CABI Full Text, Ulrich’s International Periodical Directory, ProQuest, Journalseek & Genamics, PhcogBase, EBSCOHost, Academic Search Complete, Open J-Gate, SciACCESS.
    Rapid publication: Average time from submission to first decision is 30 days and from acceptance to In Press online publication is 45 days.
    Open Access Journal: Phcog Commn. is an open access journal, which allows authors to fund their article to be open access from publication.

    © 2025 Pharmacognosy Communications. Maintained by Manuscript TechnoMedia LLP.

    Type above and press Enter to search. Press Esc to cancel.

    Scroll Up