The Effect of Formulation Variables on the Manufacturability of Clopidogrel Tablets via Fluidized Hot-Melt Granulation—From the Lab Scale to the Pilot Scale

Author:

Kovács Béla12ORCID,Tőkés Erzsébet-Orsolya23,Kelemen Éva Katalin2ORCID,Zöldi Katalin2,Boda Francisc4ORCID,Suba Edit2,Kovács-Deák Boglárka3,Casian Tibor5

Affiliation:

1. Department F1, Biochemistry and Environmental Chemistry, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mureș, 540142 Târgu Mureș, Romania

2. Gedeon Richter Romania, 540306 Târgu Mureș, Romania

3. 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

4. Department F1, General and Inorganic Chemistry, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mureș, 540142 Târgu Mureș, Romania

5. Department of Pharmaceutical Technology and Biopharmacy, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania

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.

Funder

University of Medicine, Pharmacy, Science and Technology “George Emil Palade“ of Târgu Mureș Research

Publisher

MDPI AG

Reference38 articles.

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2. Quality-by-design in pharmaceutical development: From current perspectives to practical applications;Boda;Acta Pharm.,2021

3. Beckett, C., Eriksson, L., Johansson, E., and Wikström, C. (2017). Pharmaceutical Quality by Design: A Practical Approach, John Willey and Sons.

4. Principal component analysis;Greenacre;Nat. Rev. Methods Prim.,2022

5. The diversity in the applications of partial least squares: An overview;Mehmood;J. Chemom.,2016

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