Circadian Modulation of Enterohepatic Circulation: Time-Varying Delay Analysis in Two-Compartment Pharmacokinetic Control
Abstract
To develop a pharmacokinetic model that incorporates circadian rhythms and other time-varying physiological processes into drug enterohepatic circulation (EHC). Methods: We extended a two-compartment EHC model by introducing a time-varying delay term to represent circadian variation, mealinduced gallbladder contractions, and inter-individual chronotypes. Numerical simulations compared the time-varying model against a traditional constant-delay model. Results: The timevarying model revealed critical time-of-day effects on drug levels: dosing time, meal timing, and patient chronotype substantially altered secondary peak timing and magnitude, sometimes yielding higher secondary peaks than the initial peak. Conclusions: Incorporating circadian dynamics into EHC models highlights the importance of dosing time and supports chronotherapy strategies for drugs undergoing enterohepatic recycling.
Read the paper
Related studies
- Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years — Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2018
- Improving sleep quality leads to better mental health: A meta-analysis of randomised controlled trials
- Community transmission and viral load kinetics of the SARS-CoV-2 delta (B.1.617.2) variant in vaccinated and unvaccinated individuals in the UK: a prospective, longitudinal, cohort study
- Occupation and risk of severe COVID-19: prospective cohort study of 120,075 UK Biobank participants
- Clinical presentation and virological assessment of confirmed human monkeypox virus cases in Spain: a prospective observational cohort study
- Comparison of the characteristics, morbidity, and mortality of COVID-19 and seasonal influenza: a nationwide, population-based retrospective cohort study
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.