TY - JOUR
T1 - Development and Evaluation of a Virtual Population of Children with Obesity for Physiologically Based Pharmacokinetic Modeling
AU - the Best Pharmaceuticals for Children Act—Pediatric Trials Network Steering Committee
AU - Gerhart, Jacqueline G.
AU - Carreño, Fernando O.
AU - Edginton, Andrea N.
AU - Sinha, Jaydeep
AU - Perrin, Eliana M.
AU - Kumar, Karan R.
AU - Rikhi, Aruna
AU - Hornik, Christoph P.
AU - Harris, Vincent
AU - Ganguly, Samit
AU - Cohen-Wolkowiez, Michael
AU - Gonzalez, Daniel
AU - Benjamin, Daniel K.
AU - Hornik, Christoph
AU - Zimmerman, Kanecia
AU - Kennel, Phyllis
AU - Beci, Rose
AU - Hornik, Chi Dang
AU - Kearns, Gregory L.
AU - Laughon, Matthew
AU - Paul, Ian M.
AU - Sullivan, Janice
AU - Wade, Kelly
AU - Delmore, Paula
AU - Kennedy, Eunice
AU - Taylor-Zapata, Perdita
AU - Lee, June
AU - Anand, Ravinder
AU - Sharma, Gaurav
AU - Simone, Gina
AU - Kaneshige, Kim
AU - Taylor, Lawrence
AU - Green, Ann Thomas
AU - Lurie, Robert H.
N1 - Funding Information:
Pediatric Trials Network (PTN) Steering Committee Members: Daniel K. Benjamin Jr., Christoph Hornik, Kanecia Zimmerman, Phyllis Kennel, and Rose Beci, Duke Clinical Research Institute, Durham, NC; Chi Dang Hornik, Duke University Medical Center, Durham, NC; Gregory L. Kearns, Texas Christian University and UNTHSC School of Medicine, Fort Worth, TX; Matthew Laughon, University of North Carolina at Chapel Hill, Chapel Hill, NC; Ian M. Paul, Penn State College of Medicine, Hershey, PA; Janice Sullivan, University of Louisville, Louisville, KY; Kelly Wade, Children's Hospital of Philadelphia, Philadelphia, PA; Paula Delmore, Wichita Medical Research and Education Foundation, Wichita, KS. The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): Perdita Taylor-Zapata and June Lee. The Emmes Company, LLC (Data Coordinating Center): Ravinder Anand, Gaurav Sharma, Gina Simone, Kim Kaneshige, and Lawrence Taylor. PTN Publications Committee: Chaired by Thomas Green, Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL.
Funding Information:
M.C.-W. received support from the NICHD (HHSN275201000003I), the National Center for Advancing Translational Sciences [1U24TR001608]), and the FDA (1U18FD006298); he also receives research support from industry for neonatal and pediatric drug development, https://dcri.org/about-us/conflict-of-interest/ . The remaining authors have no relevant conflicts of interest to disclose.
Funding Information:
This research was funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) under award R01HD096435. The PTN Data Repository was funded under NICHD contract HHSN275201000003I for the PTN (PI: Daniel K. Benjamin, Jr.). J.G.G. received research support from a National Institute of General Medical Sciences funded T32 program (T32GM122741) and through a Fred Eshelman Pre-Doctoral Fellowship in Pharmaceutical Sciences from the American Foundation for Pharmaceutical Education. D.G. received research support from the NICHD (R01HD096435). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Publisher Copyright:
© 2021, The Author(s).
PY - 2022/2
Y1 - 2022/2
N2 - Background and Objective: While one in five children in the USA are now obese, and more than three-quarters receive at least one drug during childhood, there is limited dosing guidance for this vulnerable patient population. Physiologically based pharmacokinetic modeling can bridge the gap in the understanding of how pharmacokinetics, including drug distribution and clearance, changes with obesity by incorporating known obesity-related physiological changes in children. The objective of this study was to develop a virtual population of children with obesity to enable physiologically based pharmacokinetic modeling, then use the novel virtual population in conjunction with previously developed models of clindamycin and trimethoprim/sulfamethoxazole to better understand dosing of these drugs in children with obesity. Methods: To enable physiologically based pharmacokinetic modeling, a virtual population of children with obesity was developed using national survey, electronic health record, and clinical trial data, as well as data extracted from the literature. The virtual population accounts for key obesity-related changes in physiology relevant to pharmacokinetics, including increased body size, body composition, organ size and blood flow, plasma protein concentrations, and glomerular filtration rate. The virtual population was then used to predict the pharmacokinetics of clindamycin and trimethoprim/sulfamethoxazole in children with obesity using previously developed physiologically based pharmacokinetic models. Results: Model simulations predicted observed concentrations well, with an overall average fold error of 1.09, 1.24, and 1.53 for clindamycin, trimethoprim, and sulfamethoxazole, respectively. Relative to children without obesity, children with obesity experienced decreased clindamycin and trimethoprim/sulfamethoxazole weight-normalized clearance and volume of distribution, and higher absolute doses under recommended pediatric weight-based dosing regimens. Conclusions: Model simulations support current recommended weight-based dosing in children with obesity for clindamycin and trimethoprim/sulfamethoxazole, as they met target exposure despite these changes in clearance and volume of distribution.
AB - Background and Objective: While one in five children in the USA are now obese, and more than three-quarters receive at least one drug during childhood, there is limited dosing guidance for this vulnerable patient population. Physiologically based pharmacokinetic modeling can bridge the gap in the understanding of how pharmacokinetics, including drug distribution and clearance, changes with obesity by incorporating known obesity-related physiological changes in children. The objective of this study was to develop a virtual population of children with obesity to enable physiologically based pharmacokinetic modeling, then use the novel virtual population in conjunction with previously developed models of clindamycin and trimethoprim/sulfamethoxazole to better understand dosing of these drugs in children with obesity. Methods: To enable physiologically based pharmacokinetic modeling, a virtual population of children with obesity was developed using national survey, electronic health record, and clinical trial data, as well as data extracted from the literature. The virtual population accounts for key obesity-related changes in physiology relevant to pharmacokinetics, including increased body size, body composition, organ size and blood flow, plasma protein concentrations, and glomerular filtration rate. The virtual population was then used to predict the pharmacokinetics of clindamycin and trimethoprim/sulfamethoxazole in children with obesity using previously developed physiologically based pharmacokinetic models. Results: Model simulations predicted observed concentrations well, with an overall average fold error of 1.09, 1.24, and 1.53 for clindamycin, trimethoprim, and sulfamethoxazole, respectively. Relative to children without obesity, children with obesity experienced decreased clindamycin and trimethoprim/sulfamethoxazole weight-normalized clearance and volume of distribution, and higher absolute doses under recommended pediatric weight-based dosing regimens. Conclusions: Model simulations support current recommended weight-based dosing in children with obesity for clindamycin and trimethoprim/sulfamethoxazole, as they met target exposure despite these changes in clearance and volume of distribution.
UR - http://www.scopus.com/inward/record.url?scp=85116752268&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85116752268&partnerID=8YFLogxK
U2 - 10.1007/s40262-021-01072-4
DO - 10.1007/s40262-021-01072-4
M3 - Article
C2 - 34617262
AN - SCOPUS:85116752268
SN - 0312-5963
VL - 61
SP - 307
EP - 320
JO - Clinical Pharmacokinetics
JF - Clinical Pharmacokinetics
IS - 2
ER -