https://pubmed.ncbi.nlm.nih.gov/35639246/
Arch Pharm Res. 2022 May;45(5):352-366
Chang‑Keun Cho, Pureum Kang, Hye‑Jung Park, Eunvin Ko, Chou Yen Mu, Yun Jeong Lee, Chang‑Ik Choi, Hyung Sik Kim, Choon‑Gon Jang, Jung‑Woo Bae, Seok‑Yong Lee
Abstract
Piroxicam is a non-steroidal anti-inflammatory drug used to alleviate symptoms of osteoarthritis and rheumatoid arthritis. CYP2C9 genetic polymorphism significantly influences the pharmacokinetics of piroxicam. The objective of this study was to develop and validate the piroxicam physiologically based pharmacokinetic (PBPK) model related to CYP2C9 genetic polymorphism. PK-Sim® version 10.0 was used for the PBPK modeling. The PBPK model was evaluated by predicted and observed plasma concentration-time profiles, fold errors of predicted to observed pharmacokinetic parameters, and a goodness-of-fit plot. The turnover number (kcat) of CYP2C9 was adjusted to capture the pharmacokinetics of piroxicam in different CYP2C9 genotypes. The population PBPK model overall accurately described and predicted the plasma concentration-time profiles in different CYP2C9 genotypes. In our simulations, predicted AUCinf in CYP2C91/2, CYP2C91/3, and CYP2C93/3 genotypes were 1.83-, 2.07-, and 6.43-fold higher than CYP2C91/1 genotype, respectively. All fold error values for AUC, Cmax, and t1/2 were included in the acceptance criterion with the ranges of 0.57-1.59, 0.63-1.39, and 0.65-1.51, respectively. The range of fold error values for predicted versus observed plasma concentrations was 0.11-3.13. 93.9% of fold error values were within the two-fold range. Average fold error, absolute average fold error, and root mean square error were 0.93, 1.27, and 0.72, respectively. Our model accurately captured the pharmacokinetic alterations of piroxicam according to CYP2C9 genetic polymorphism.
https://pubmed.ncbi.nlm.nih.gov/35639246/ Arch Pharm Res. 2022 May;45(5):352-366 Chang‑Keun Cho, Pureum Kang, Hye‑Jung Park, Eunvin Ko, Chou Yen Mu, Yun Jeong Lee, Chang‑Ik Choi, Hyung Sik Kim, Choon‑Gon Jang, Jung‑Woo Bae, Seok‑Yong Lee
Abstract Piroxicam is a non-steroidal anti-inflammatory drug used to alleviate symptoms of osteoarthritis and rheumatoid arthritis. CYP2C9 genetic polymorphism significantly influences the pharmacokinetics of piroxicam. The objective of this study was to develop and validate the piroxicam physiologically based pharmacokinetic (PBPK) model related to CYP2C9 genetic polymorphism. PK-Sim® version 10.0 was used for the PBPK modeling. The PBPK model was evaluated by predicted and observed plasma concentration-time profiles, fold errors of predicted to observed pharmacokinetic parameters, and a goodness-of-fit plot. The turnover number (kcat) of CYP2C9 was adjusted to capture the pharmacokinetics of piroxicam in different CYP2C9 genotypes. The population PBPK model overall accurately described and predicted the plasma concentration-time profiles in different CYP2C9 genotypes. In our simulations, predicted AUCinf in CYP2C91/2, CYP2C91/3, and CYP2C93/3 genotypes were 1.83-, 2.07-, and 6.43-fold higher than CYP2C91/1 genotype, respectively. All fold error values for AUC, Cmax, and t1/2 were included in the acceptance criterion with the ranges of 0.57-1.59, 0.63-1.39, and 0.65-1.51, respectively. The range of fold error values for predicted versus observed plasma concentrations was 0.11-3.13. 93.9% of fold error values were within the two-fold range. Average fold error, absolute average fold error, and root mean square error were 0.93, 1.27, and 0.72, respectively. Our model accurately captured the pharmacokinetic alterations of piroxicam according to CYP2C9 genetic polymorphism.
Keywords: CYP2C9; Genetic polymorphism; Pharmacokinetics; Physiologically based pharmacokinetic (PBPK) model; Piroxicam.
© 2022. The Pharmaceutical Society of Korea.