Iftekhar Mahmood1, Anna Cheng2, Edward Brauer2, Rita Humeniuk3. 1. Division of Hematology Clinical Review, Office of Blood Review and Research (OBRR), Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, 20993-0002, USA. Iftekhar.mahmood@fda.hhs.gov. 2. School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Los Angeles, CA, 90089, USA. 3. Office of the Commissioner, US Food and Drug Administration, Silver Spring, MD, 20993-0002, USA.
Abstract
BACKGROUND AND OBJECTIVE: Allometric scaling is extensively used for the prediction of pharmacokinetic parameters from animals to humans and is often used for the selection of first-in-human dose. Allometric scaling can also be used to predict a pharmacokinetic parameter in children from adult data including animal species such as rat and dog. The current study was undertaken to evaluate if the clearances of antimalarial drugs in children with malaria can be predicted allometrically (interspecies scaling) from adult rat, dog, and human adult (healthy as well patients with malaria) clearance values. METHODS: Three methods [simple allometry, maximum lifespan potential (MLP), and MLP with an empirical correction factor] using clearance values from adult rat, dog, and adult humans with and without malaria were used for the prediction of antimalarial drug clearance in children with malaria. RESULTS: The results of this study indicated that the simple allometry would systematically over-predict antimalarial drug clearance in children with malaria whereas the application of MLP would under-predict the clearances of these drugs in children. Therefore, an empirical correction factor was introduced to MLP which substantially improved the antimalarial drug clearances in children. CONCLUSIONS: Overall, the results of the study indicated that interspecies scaling using adult rat, dog, and human clearance values of antimalarial drugs could possibly be used to predict drug clearance in children with malaria of different age groups and may be useful during pediatric drug development of antimalarial drugs.
BACKGROUND AND OBJECTIVE: Allometric scaling is extensively used for the prediction of pharmacokinetic parameters from animals to humans and is often used for the selection of first-in-human dose. Allometric scaling can also be used to predict a pharmacokinetic parameter in children from adult data including animal species such as rat and dog. The current study was undertaken to evaluate if the clearances of antimalarial drugs in children with malaria can be predicted allometrically (interspecies scaling) from adult rat, dog, and human adult (healthy as well patients with malaria) clearance values. METHODS: Three methods [simple allometry, maximum lifespan potential (MLP), and MLP with an empirical correction factor] using clearance values from adult rat, dog, and adult humans with and without malaria were used for the prediction of antimalarial drug clearance in children with malaria. RESULTS: The results of this study indicated that the simple allometry would systematically over-predict antimalarial drug clearance in children with malaria whereas the application of MLP would under-predict the clearances of these drugs in children. Therefore, an empirical correction factor was introduced to MLP which substantially improved the antimalarial drug clearances in children. CONCLUSIONS: Overall, the results of the study indicated that interspecies scaling using adult rat, dog, and human clearance values of antimalarial drugs could possibly be used to predict drug clearance in children with malaria of different age groups and may be useful during pediatric drug development of antimalarial drugs.
Authors: F A Claessen; C J van Boxtel; R M Perenboom; R A Tange; J C Wetsteijn; P A Kager Journal: Trop Med Int Health Date: 1998-06 Impact factor: 2.622
Authors: Kevin T Batty; Brioni R Moore; Verity Stirling; Kenneth F Ilett; Madhu Page-Sharp; Keith B Shilkin; Ivo Mueller; Harin A Karunajeewa; Timothy M E Davis Journal: Toxicology Date: 2008-04-16 Impact factor: 4.221