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Manufacturing classification system in the real world: factors influencing manufacturing process choices for filed commercial oral solid dosage formulations, case studies from industry and considerations for continuous processing.
Leane, Michael; Pitt, Kendal; Reynolds, Gavin K; Dawson, Neil; Ziegler, Iris; Szepes, Aniko; Crean, Abina M; Dall Agnol, Rafaela.
Afiliación
  • Leane M; a Drug Product Science & Technology (DPST), Bristol-Myers Squibb , Moreton , UK.
  • Pitt K; b Global Manufacturing and Supply, GlaxoSmithKline , Ware , UK.
  • Reynolds GK; c Process Engineering, Astra Zeneca , Macclesfield , UK.
  • Dawson N; d Global Research and Development, Pfizer , Sandwich , UK.
  • Ziegler I; e Corden Pharma International GmbH , Plankstadt , Germany.
  • Szepes A; f Research and Development Division, F. Hoffmann-La Roche AG , Basel , Switzerland.
  • Crean AM; g Pharmaceutical Manufacturing Technology Centre, School of Pharmacy , University College Cork - National University of Ireland , Cork , Ireland.
  • Dall Agnol R; h Synthesis and Solid State Pharmaceutical Centre, School of Pharmacy , University College Cork - National University of Ireland , Cork , Ireland.
  • The Manufacturing Classification System McS Working Group; i Curso de Farmácia, Centro de Ciências Biológicas e da Saúde , Universidade de Caxias do Sul , Caxias do Sul , Brazil.
Pharm Dev Technol ; 23(10): 964-977, 2018 Dec.
Article en En | MEDLINE | ID: mdl-30320539
Following the first Manufacturing Classification System (MCS) paper, the team conducted surveys to establish which active pharmaceutical ingredient (API) properties were important when selecting or modifying materials to enable an efficient and robust pharmaceutical manufacturing process. The most commonly identified factors were (1) API particle size: small particle sizes are known to increase risk of processing issues; (2) Drug loading in the formulation: high drug loadings allow less opportunity to mitigate poor API properties through the use of excipients. The next step was to establish linkages with process decisions by identifying publicly-available proxies for these important parameters: dose (in place of drug loading) and BCS class (in place of particle size). Poorly-soluble API were seen as more likely to have controlled (smaller) particle size than more highly soluble API. Analysis of 435 regulatory filings revealed that higher doses and more poorly-soluble API was associated with more complex processing routes. Replacing the proxy factors with the original parameters should give the opportunity to demonstrate stronger trends. This assumption was tested by accessing a dataset relating to commercial tablet products. This showed that, for dry processes, a larger particle size was associated with higher achievable drug loading as determined by percolation threshold.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tamaño de la Partícula / Preparaciones Farmacéuticas / Composición de Medicamentos / Industria Farmacéutica Tipo de estudio: Prognostic_studies Límite: Animals / Humans País/Región como asunto: Europa Idioma: En Revista: Pharm Dev Technol Asunto de la revista: FARMACIA Año: 2018 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tamaño de la Partícula / Preparaciones Farmacéuticas / Composición de Medicamentos / Industria Farmacéutica Tipo de estudio: Prognostic_studies Límite: Animals / Humans País/Región como asunto: Europa Idioma: En Revista: Pharm Dev Technol Asunto de la revista: FARMACIA Año: 2018 Tipo del documento: Article Pais de publicación: Reino Unido