Program

PO1-11-30

Prediction and optimization of photo-activated curcumin dosage schedule in human, a promising antimicrobial candidate: A physiologically-based pharmacokinetic (PBPK) modeling

[Speaker] Teerachat Saeheng:1,2
[Co-author] Kesara Na-Bangchang:3,4, Rajith K. R. Rajoli:5, Marco Siccardi:5, Andrew Owen:5, Juntra Laothavorn:2
1:Infection Research, Leading Program, Graduate School of Biomedical Sciences, Nagasaki University, Japan, 2:Department of Clinical Product Development, Institute of Tropical Medicine, Nagasaki University, Japan, 3:Chulabhorn International College of Medicine, Thammasat University, PathumThani, Thailand, 4:Center of Excellence in Pharmacology and Molecular Biology of Malaria and Cholangiocarcinoma, Chulabhorn International College of Medicine, Thammasat University, PathumThani, Thailand, 5:Department of Molecular and Clinical Pharmacology, University of Liverpool, UK

Background
Antimicrobial resistance is emerging as one of the most serious threats to global public health and novel broad-spectrum antibiotics are highly to tackle future challenges. Curcumin is an herb with broad-spectrum antibacterial activities and has been shown to have synergistic effects with other antibiotics. To date, its antimicrobial activity has been investigated only in vitro and pre-clinical studies and human pharmacokinetic data are available for other therapeutic strategies. Nevertheless, the administration of existing curcumin formulations does not result in sufficient exposure for antimicrobial treatment. Physiologically-based pharmacokinetic (PBPK) modeling has been used to predict drug distribution and simulate clinical scenarios in virtual patients. The objective of this study was to develop a PBPK model for predicting optimal dosage through enhancement of curcumin absorption (Ka) for multi-microorganism treatment in adults.
Methods
A whole-PBPK model was built based on human physiological parameters and drug specific parameters. Average-folding errors (AFEs) of the area under the curve (AUC) and maximum blood concentration (Cmax) of simulated results from 100 virtual populations were compared to clinical data and further validated with different dosage regimens. The predicted clearance (CL), volume of distribution at steady state (Vss), half-life (t1/2) and oral bioavailability (F) were reported as mean (SD) values. Optimal AUC and Cmax for antimicrobial activities were determined using PK/PD indices: AUC/MIC (minimum inhibitory concentration) >125 and Cmax/MIC > 10.
Results
The AFEs for model prediction and model validation were within 1.5-and 2-fold of clinical observed data, respectively. Model prediction of CL (L/h), Vss (L), t1/2(hr) and F was 28.53 (1.3), 2.3 (0.35), 3.85 (0.71) and 0.98%, respectively. Theoretical benefits were simulated considering effect on Ka and optimized PK/PD indices were achieved at a dose of 500 mg T.I.D. with Ka=10h-1
Conclusions
The PBPK approach supported the simulation of curcumin pharmacokinetics and prediction of the antimicrobial activity, suggesting that the curcumin formulation could be improved and possibly be successful for treatment of resistant bacteria. However, further pre-clinical and clinical investigations are now warranted to confirm these simulations.
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