Literature DB >> 27543350

Enabling real time release testing by NIR prediction of dissolution of tablets made by continuous direct compression (CDC).

Pallavi Pawar1, Yifan Wang1, Golshid Keyvan1, Gerardo Callegari1, Alberto Cuitino2, Fernando Muzzio3.   

Abstract

A method for predicting dissolution profiles of directly compressed tablets for a fixed sustained release formulation manufactured in a continuous direct compaction (CDC) system is presented. The methodology enables real-time release testing (RTRt). Tablets were made at a target drug concentration of 9% Acetaminophen, containing 90% lactose and 1% Magnesium Stearate, and at a target compression force of 24kN. A model for predicting dissolution profiles was developed using a 3(4-1) fractional factorial experimental design built around this targeted condition. Four variables were included: API concentration (low, medium, high), blender speed (150rpm, 200rpm, 250rpm), feed frame speed (20rpm, 25rpm, 30rpm), compaction force (8KN, 16KN, 24KN). The tablets thus obtained were scanned at-line in transmission mode using Near IR spectroscopy. The dissolution profiles were described using two approaches, a model-independent "shape and level" method, and a model-dependent approach based on Weibull's model. Multivariate regression was built between the NIR scores as the predictor variables and the dissolution profile parameters as the response. The model successfully predicted the dissolution profiles of the individual tablets (similarity factor, f2 ∼72) manufactured at the targeted set point. This is a first ever published manuscript addressing RTRt for dissolution prediction in continuous manufacturing, a novel and state of art technique for tablet manufacturing.
Copyright © 2016. Published by Elsevier B.V.

Entities:  

Keywords:  Continuous manufacturing; Dissolution prediction; Feeders; Near IR spectroscopy; Real time release; Tablets

Mesh:

Substances:

Year:  2016        PMID: 27543350     DOI: 10.1016/j.ijpharm.2016.08.033

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


  4 in total

1.  Dissolution Testing in Drug Product Development: Workshop Summary Report.

Authors:  Andreas Abend; David Curran; Jesse Kuiper; Xujin Lu; Hanlin Li; Andre Hermans; Pramod Kotwal; Dorys A Diaz; Michael J Cohen; Limin Zhang; Erika Stippler; German Drazer; Yiqing Lin; Kimberly Raines; Lawrence Yu; Carrie A Coutant; Haiyan Grady; Johannes Krämer; Sarah Pope-Miksinski; Sandra Suarez-Sharp
Journal:  AAPS J       Date:  2019-01-28       Impact factor: 4.009

2.  Fast, Spectroscopy-Based Prediction of In Vitro Dissolution Profile of Extended Release Tablets Using Artificial Neural Networks.

Authors:  Dorián László Galata; Attila Farkas; Zsófia Könyves; Lilla Alexandra Mészáros; Edina Szabó; István Csontos; Andrea Pálos; György Marosi; Zsombor Kristóf Nagy; Brigitta Nagy
Journal:  Pharmaceutics       Date:  2019-08-09       Impact factor: 6.321

3.  Continuous direct compression: Development of an empirical predictive model and challenges regarding PAT implementation.

Authors:  B Bekaert; B Van Snick; K Pandelaere; J Dhondt; G Di Pretoro; T De Beer; C Vervaet; V Vanhoorne
Journal:  Int J Pharm X       Date:  2021-12-25

Review 4.  Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets.

Authors:  Guolin Shi; Longfei Lin; Yuling Liu; Gongsen Chen; Yuting Luo; Yanqiu Wu; Hui Li
Journal:  RSC Adv       Date:  2021-02-23       Impact factor: 3.361

  4 in total

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