Literature DB >> 32325242

Review of real-time release testing of pharmaceutical tablets: State-of-the art, challenges and future perspective.

Daniel Markl1, Martin Warman2, Melanie Dumarey3, Eva-Lotta Bergman3, Staffan Folestad3, Zhenqi Shi4, Leo Francis Manley4, Daniel J Goodwin5, J Axel Zeitler6.   

Abstract

In the last decade significant advances have been made in process analytical technologies and digital manufacturing of pharmaceutical oral solid dosage forms leading to enhanced product knowledge and process understanding. These developments provide an excellent platform for realising real-time release testing (RTRT) to eliminate all, or certain, off-line end product tests assuring that the drug product is of intended quality. This review article presents the state of the art, an RTRT development workflow as well as challenges and opportunities of RTRT in batch and continuous manufacturing of pharmaceutical tablets. Critical quality attributes, regulatory aspects and the scientific basis of enabling technologies and models for RTRT are discussed and a systematic development workflow for the robust design of an RTRT environment is presented. This includes the discussion of key considerations for the identification of the critical quality attributes and points of testing as well as the development of the sampling strategy, a hard and/or soft sensor approach and operational procedures. The final sections present two RTRT use cases in an industrial setting as well as critically discuss challenges and provide a future perspective of RTRT.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Models; Process analytical technology; Real-time release testing; Soft sensors; Tablet manufacturing

Year:  2020        PMID: 32325242     DOI: 10.1016/j.ijpharm.2020.119353

Source DB:  PubMed          Journal:  Int J Pharm        ISSN: 0378-5173            Impact factor:   5.875


  2 in total

1.  Development of a Controlled Continuous Low-Dose Feeding Process.

Authors:  Sara Fathollahi; Julia Kruisz; Stephan Sacher; Jakob Rehrl; M Sebastian Escotet-Espinoza; James DiNunzio; Benjamin J Glasser; Johannes G Khinast
Journal:  AAPS PharmSciTech       Date:  2021-10-12       Impact factor: 3.246

2.  Big data collection in pharmaceutical manufacturing and its use forproduct quality predictions.

Authors:  Janja Žagar; Jurij Mihelič
Journal:  Sci Data       Date:  2022-03-23       Impact factor: 8.501

  2 in total

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