Citation
Rasool, Muhammad F., et al. "Development and Evaluation of Physiologically Based Pharmacokinetic Drug-disease Models for Predicting Captopril Pharmacokinetics in Chronic Diseases." Scientific Reports, vol. 11, no. 1, 2021, p. 8589.
Rasool MF, Ali S, Khalid S, et al. Development and evaluation of physiologically based pharmacokinetic drug-disease models for predicting captopril pharmacokinetics in chronic diseases. Sci Rep. 2021;11(1):8589.
Rasool, M. F., Ali, S., Khalid, S., Khalid, R., Majeed, A., Imran, I., Saeed, H., Usman, M., Ali, M., Alali, A. S., AlAsmari, A. F., Ali, N., Asiri, A. M., Alasmari, F., & Alqahtani, F. (2021). Development and evaluation of physiologically based pharmacokinetic drug-disease models for predicting captopril pharmacokinetics in chronic diseases. Scientific Reports, 11(1), 8589. https://doi.org/10.1038/s41598-021-88154-2
Rasool MF, et al. Development and Evaluation of Physiologically Based Pharmacokinetic Drug-disease Models for Predicting Captopril Pharmacokinetics in Chronic Diseases. Sci Rep. 2021 04 21;11(1):8589. PubMed PMID: 33883647.
TY - JOUR
T1 - Development and evaluation of physiologically based pharmacokinetic drug-disease models for predicting captopril pharmacokinetics in chronic diseases.
AU - Rasool,Muhammad F,
AU - Ali,Shazia,
AU - Khalid,Sundus,
AU - Khalid,Ramsha,
AU - Majeed,Abdul,
AU - Imran,Imran,
AU - Saeed,Hamid,
AU - Usman,Muhammad,
AU - Ali,Mohsin,
AU - Alali,Amer S,
AU - AlAsmari,Abdullah F,
AU - Ali,Nemat,
AU - Asiri,Ali Mohammed,
AU - Alasmari,Fawaz,
AU - Alqahtani,Faleh,
Y1 - 2021/04/21/
PY - 2020/11/30/received
PY - 2021/04/08/accepted
PY - 2021/4/22/entrez
PY - 2021/4/23/pubmed
PY - 2021/11/16/medline
SP - 8589
EP - 8589
JF - Scientific reports
JO - Sci Rep
VL - 11
IS - 1
N2 - The advancement in the processing speeds of computing machines has facilitated the development of complex physiologically based pharmacokinetic (PBPK) models. These PBPK models can incorporate disease-specific data and could be used to predict pharmacokinetics (PK) of administered drugs in different chronic conditions. The present study aimed to develop and evaluate PBPK drug-disease models for captopril after incorporating relevant pathophysiological changes occurring in adult chronic kidney disease (CKD) and chronic heart failure (CHF) populations. The population-based PBPK simulator Simcyp was used as a modeling and simulation platform. The visual predictive checks and mean observed/predicted ratios (ratio(Obs/pred)) of the PK parameters were used for model evaluation. The developed disease models were successful in predicting captopril PK in all three stages of CKD (mild, moderate, and severe) and CHF, as the observed and predicted PK profiles and the ratio(obs/pred) for the PK parameters were in close agreement. The developed captopril PBPK models can assist in tailoring captopril dosages in patients with different disease severity (CKD and CHF).
SN - 2045-2322
UR - https://www.unboundmedicine.com/medline/citation/33883647/Development_and_evaluation_of_physiologically_based_pharmacokinetic_drug_disease_models_for_predicting_captopril_pharmacokinetics_in_chronic_diseases_
DB - PRIME
DP - Unbound Medicine
ER -