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A General Framework for Assessing In vitro/In vivo Correlation as a Tool for Maximizing the Benefit‐Risk Ratio of a Treatment Using a Convolution‐Based Modeling Approach

The net benefit of a treatment can be defined by the relationship between clinical improvement and risk of adverse events: the benefit‐risk ratio. The optimization of the benefit‐risk ratio can be achieved by identifying the most adequate dose (and/or dosage regimen) jointly with the best‐performing...

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Detalles Bibliográficos
Autores principales: Gomeni, Roberto, Fang, Lanyan (Lucy), Bressolle‐Gomeni, Françoise, Spencer, Thomas J., Faraone, Stephen V., Babiskin, Andrew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6389349/
https://www.ncbi.nlm.nih.gov/pubmed/30659771
http://dx.doi.org/10.1002/psp4.12378
Descripción
Sumario:The net benefit of a treatment can be defined by the relationship between clinical improvement and risk of adverse events: the benefit‐risk ratio. The optimization of the benefit‐risk ratio can be achieved by identifying the most adequate dose (and/or dosage regimen) jointly with the best‐performing in vivo release properties of a drug. A general in silico tool is presented for identifying the dose, the in vitro and the in vivo release properties that maximize the benefit‐risk ratio using convolution‐based modeling, an exposure‐response model, and a surface response analysis. A case study is presented to illustrate how the benefit‐risk ratio of methylphenidate for the treatment of attention deficit hyperactivity disorder can be maximized using the proposed strategy. The results of the analysis identified the characteristics of an optimized dose and in vitro/in vivo release suitable to provide a sustained clinical response with respect to the conventional dosage regimen and formulations.