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Computing optimal drug dosing with OptiDose: implementation in NONMEM.
Bachmann, Freya; Koch, Gilbert; Bauer, Robert J; Steffens, Britta; Szinnai, Gabor; Pfister, Marc; Schropp, Johannes.
Afiliación
  • Bachmann F; Department of Mathematics and Statistics, University of Konstanz, PO Box 195, 78457, Konstanz, Germany.
  • Koch G; Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital, Spitalstrasse 33, 4056, Basel, Switzerland. gilbert.koch@ukbb.ch.
  • Bauer RJ; ICON Clinical Research LLC, Blue Bell, PA, USA.
  • Steffens B; Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital, Spitalstrasse 33, 4056, Basel, Switzerland.
  • Szinnai G; Pediatric Endocrinology and Diabetology, University of Basel Children's Hospital, Spitalstrasse 33, 4056, Basel, Switzerland.
  • Pfister M; Department of Clinical Research, University of Basel and University Hospital Basel, Basel, Switzerland.
  • Schropp J; Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital, Spitalstrasse 33, 4056, Basel, Switzerland.
J Pharmacokinet Pharmacodyn ; 50(3): 173-188, 2023 06.
Article en En | MEDLINE | ID: mdl-36707456
Determining a drug dosing recommendation with a PKPD model can be a laborious and complex task. Recently, an optimal dosing algorithm (OptiDose) was developed to compute the optimal doses for any pharmacometrics/PKPD model for a given dosing scenario. In the present work, we reformulate the underlying optimal control problem and elaborate how to solve it with standard commands in the software NONMEM. To demonstrate the potential of the OptiDose implementation in NONMEM, four relevant but substantially different optimal dosing tasks are solved. In addition, the impact of different dosing scenarios as well as the choice of the therapeutic goal on the computed optimal doses are discussed.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Programas Informáticos Tipo de estudio: Guideline Idioma: En Revista: J Pharmacokinet Pharmacodyn Asunto de la revista: FARMACOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Programas Informáticos Tipo de estudio: Guideline Idioma: En Revista: J Pharmacokinet Pharmacodyn Asunto de la revista: FARMACOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Alemania