{"doi":"10.1111/cts.70401","title":"Using a <scp>PBPK</scp> Model Incorporating Lymphatic Absorption to Predict Food Effect, Multiple Dosing, and Hepatic Impairment of Cannabidiol","abstract":"ABSTRACT Cannabidiol (CBD) is one of the most extensively studied cannabinoids and is used for myriad conditions. Its oral pharmacokinetics are complex, exhibiting non‐linear absorption, significant food effects, and variable exposure in hepatic impairment. Existing physiologically based pharmacokinetic (PBPK) models for oral CBD have largely relied on fitted first‐order absorption or fitted dissolution profiles, limiting their mechanistic and predictive capabilities and extrapolation, particularly regarding the mechanistic details of its absorption. This study developed and verified the first PBPK model for oral CBD with mechanism‐based oral absorption based on our prior published PBPK model. It incorporated mechanism‐based absorption using the multi‐layer gut wall within the advanced dissolution, absorption, and metabolism (M‐ADAM) model within Simcyp. Pharmacokinetic parameters for CBD or population parameters related to absorption were obtained from the literature or optimized. Some physiological parameters (e.g., luminal bile salt and lymph flow rate) were adjusted mechanistically to account for CBD's sesame oil formulation and meal characteristics. The model well captured the CBD concentration‐time profiles and key pharmacokinetic parameters, including area under the concentration‐time curve (AUC), peak concentration ( C max ), and time to maximum concentration ( t max ) across diverse doses, fed/fasted states, and in patients with hepatic impairment (mild, moderate, severe). Predictions were consistently within two‐fold of observed data. This work offers a robust foundation for the mechanistic understanding of CBD's complex oral absorption. The verified models can optimize CBD dosing strategies, predict potential drug–drug interactions, and evaluate CBD pharmacokinetics in various specific populations, ultimately contributing to safer and more effective clinical use.","journal":"Clinical and Translational Science","year":2025,"id":537287,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9402,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1186400,"name":"Zhu Zhou","orcid":"0000-0002-3384-1346","position":1,"is_corresponding":false},{"id":1218348,"name":"Lixuan Qian","orcid":"0000-0003-3137-5529","position":0,"is_corresponding":true}],"reference_count":28,"raw_metadata":null,"created_at":"2026-07-19T02:52:12.997494Z","pmid":"41251333","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}