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The Effect of Formulation Variables on the Manufacturability of Clopidogrel Tablets via Fluidized Hot-Melt Granulation-From the Lab Scale to the Pilot Scale.
Kovács, Béla; Tokés, Erzsébet-Orsolya; Kelemen, Éva Katalin; Zöldi, Katalin; Boda, Francisc; Suba, Edit; Kovács-Deák, Boglárka; Casian, Tibor.
Afiliación
  • Kovács B; Department F1, Biochemistry and Environmental Chemistry, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mureș, 540142 Târgu Mureș, Romania.
  • Tokés EO; Gedeon Richter Romania, 540306 Târgu Mureș, Romania.
  • Kelemen ÉK; Gedeon Richter Romania, 540306 Târgu Mureș, Romania.
  • Zöldi K; The Doctoral School of Medicine and Pharmacy, Institution Organizing University Doctoral Studies, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mureș, 540142 Târgu Mureș, Romania.
  • Boda F; Gedeon Richter Romania, 540306 Târgu Mureș, Romania.
  • Suba E; Gedeon Richter Romania, 540306 Târgu Mureș, Romania.
  • Kovács-Deák B; Department F1, General and Inorganic Chemistry, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mureș, 540142 Târgu Mureș, Romania.
  • Casian T; Gedeon Richter Romania, 540306 Târgu Mureș, Romania.
Pharmaceutics ; 16(3)2024 Mar 13.
Article en En | MEDLINE | ID: mdl-38543285
ABSTRACT
Solid pharmaceutical formulations with class II active pharmaceutical ingredients (APIs) face dissolution challenges due to limited solubility, affecting in vivo behavior. Robust computational tools, via data mining, offer valuable insights into product performance, complementing traditional methods and aiding in scale-up decisions. This study utilizes the design of experiments (DoE) to understand fluidized hot-melt granulation manufacturing technology. Exploratory data analysis (MVDA) highlights similarities and differences in tablet manufacturability and dissolution profiles at both the lab and pilot scales. The study sought to gain insights into the application of multivariate data analysis by identifying variations among batches produced at different manufacturing scales for this technology. DoE and MVDA findings show that the granulation temperature, time, and Macrogol type significantly impact product performance. These factors, by influencing particle size distribution, become key predictors of product quality attributes such as resistance to crushing, disintegration time, and early-stage API dissolution in the profile. Software-aided data mining, with its multivariate and versatile nature, complements the empirical approach, which is reliant on trial and error during product scale-up.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Pharmaceutics Año: 2024 Tipo del documento: Article País de afiliación: Rumanía

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Pharmaceutics Año: 2024 Tipo del documento: Article País de afiliación: Rumanía
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