Literature DB >> 30192373

A Comparative Study Between Allometric Scaling and Physiologically Based Pharmacokinetic Modeling for the Prediction of Drug Clearance From Neonates to Adolescents.

Iftekhar Mahmood1, Million A Tegenge2.   

Abstract

The objective of this study was to compare the predictive performance of an allometric model with that of a physiologically based pharmacokinetic (PBPK) model to predict clearance or area under the concentration-time curve (AUC) of drugs in subjects from neonates to adolescents. From the literature, 10 studies were identified in which clearance or AUC of drugs from neonates to adolescents was predicted by PBPK models. In these published studies, drugs were given to children either by intravenous or oral route. The allometric model was an age-dependent exponent (ADE) model for the prediction of clearance across the age groups. The predicted clearance or AUC values from the PBPK and ADE models were compared with the experimental values. The acceptable prediction error was the percentage of subjects within an 0.5- to 2-fold or 0.5- to 1.5-fold prediction error. There were 73 drugs with a total of 372 observations. From PBPK and allometric models, 91.1% and 90.6% of observations were within 0.5- to 2-fold prediction error, respectively. For children ≤2 years old (n = 130), PBPK and allometric models had 89% and 87% of observations within the 0.5- to 2-fold prediction error, respectively. This study indicates that the predictive power of PBPK and allometric models was essentially similar for the prediction of clearance or AUC in pediatric subjects ranging from neonates to adolescents.
© 2018, The American College of Clinical Pharmacology.

Entities:  

Keywords:  Allometry; Children; Clearance; PBPK

Mesh:

Year:  2018        PMID: 30192373     DOI: 10.1002/jcph.1310

Source DB:  PubMed          Journal:  J Clin Pharmacol        ISSN: 0091-2700            Impact factor:   3.126


  8 in total

1.  Simulated Assessment of Pharmacokinetically Guided Dosing for Investigational Treatments of Pediatric Patients With Coronavirus Disease 2019.

Authors:  Anil R Maharaj; Huali Wu; Christoph P Hornik; Stephen J Balevic; Chi D Hornik; P Brian Smith; Daniel Gonzalez; Kanecia O Zimmerman; Daniel K Benjamin; Michael Cohen-Wolkowiez
Journal:  JAMA Pediatr       Date:  2020-10-05       Impact factor: 16.193

2.  A General Biphasic Bodyweight Model for Scaling Basal Metabolic Rate, Glomerular Filtration Rate, and Drug Clearance from Birth to Adulthood.

Authors:  Teh-Min Hu
Journal:  AAPS J       Date:  2022-05-10       Impact factor: 3.603

3.  Determining the Effects of Chronic Kidney Disease on Organic Anion Transporter1/3 Activity Through Physiologically Based Pharmacokinetic Modeling.

Authors:  Samuel Dubinsky; Paul Malik; Dagmar M Hajducek; Andrea Edginton
Journal:  Clin Pharmacokinet       Date:  2022-05-05       Impact factor: 5.577

4.  Antimicrobial Dosing Recommendations in Pediatric Continuous Renal Replacement Therapy: A Critical Appraisal of Current Evidence.

Authors:  Gideon Stitt; Samuel Dubinsky; Andrea Edginton; Yuan-Shung V Huang; Athena F Zuppa; Kevin Watt; Kevin Downes
Journal:  Front Pediatr       Date:  2022-05-12       Impact factor: 3.569

5.  A Retrospective Evaluation of Allometry, Population Pharmacokinetics, and Physiologically-Based Pharmacokinetics for Pediatric Dosing Using Clearance as a Surrogate.

Authors:  Qier Wu; Sheila Annie Peters
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2019-02-26

Review 6.  Accelerating Drug Development in Pediatric Oncology With the Clinical Pharmacology Storehouse.

Authors:  Mohamad Shebley; Rajeev M Menon; John P Gibbs; Nimita Dave; Su Y Kim; Patrick J Marroum
Journal:  J Clin Pharmacol       Date:  2018-12-18       Impact factor: 3.126

7.  Physiologically-Based Pharmacokinetic Modeling vs. Allometric Scaling for the Prediction of Infliximab Pharmacokinetics in Pediatric Patients.

Authors:  Paul R V Malik; Andrea N Edginton
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2019-10-19

8.  Population Pharmacokinetic Modeling and Simulation of TQ-B3101 to Inform Dosing in Pediatric Patients With Solid Tumors.

Authors:  Fen Yang; Huali Wu; Yunhai Bo; Ye Lu; Hong Pan; Su Li; Qin Lu; Simin Xie; Harry Liao; Bing Wang
Journal:  Front Pharmacol       Date:  2022-01-18       Impact factor: 5.810

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.