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Dose Predictions for Drug Design.
Maurer, Tristan S; Smith, Dennis; Beaumont, Kevin; Di, Li.
Afiliação
  • Maurer TS; Medicine Design, Pfizer Worldwide Research and Development, Cambridge, Massachusetts 02139, United States.
  • Smith D; 4 The Maltings, Walmer, Kent CT14 7AR, U.K.
  • Beaumont K; Medicine Design, Pfizer Worldwide Research and Development, Cambridge, Massachusetts 02139, United States.
  • Di L; Medicine Design, Pfizer Worldwide Research and Development, Groton, Connecticut 06340, United States.
J Med Chem ; 63(12): 6423-6435, 2020 06 25.
Article em En | MEDLINE | ID: mdl-31913040
ABSTRACT
The efficacious dose of a drug is perhaps the most holistic metric reflecting its therapeutic potential. Dose is predicted at many stages in drug discovery and development. Prior to the 1990s, dose prediction was limited to the drug "working" at a reasonable dose and dose regimen in an animal model. Through the early 2000s, dose predictions were generated at candidate nomination and then refined during clinical development. Currently, dose predictions can be made early in drug discovery to enable drug design. Dose predictions at this stage can identify critical drug properties for a viable dose regimen and provide clinically relevant context to lead optimization. In this paper, we give an overview of the opportunities and challenges associated with dose prediction for drug design. A number of general considerations, approaches, and case examples are discussed.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Preparações Farmacêuticas / Desenho de Fármacos / Avaliação Pré-Clínica de Medicamentos / Descoberta de Drogas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Preparações Farmacêuticas / Desenho de Fármacos / Avaliação Pré-Clínica de Medicamentos / Descoberta de Drogas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article