Next Article in Journal
Hierarchical Particle Approach for Co-Precipitated Amorphous Solid Dispersions for Use in Preclinical In Vivo Studies
Previous Article in Journal
Insight into the Web of Stress Responses Triggered at Gene Expression Level by Porphyrin-PDT in HT29 Human Colon Carcinoma Cells
 
 
Article

Process Model Approach to Predict Tablet Weight Variability for Direct Compression Formulations at Pilot and Production Scale

1
SSPC Pharmaceutical Research Centre, School of Pharmacy, University College Cork, T12 K8AF Cork, Ireland
2
Alkermes Pharma Ireland Limited, N37 EA09 Athlone, Ireland
3
Pharmaceutical Manufacturing Technology Centre (PMTC), Bernal Institute, University of Limerick, V94 T9PX Limerick, Ireland
4
Alkermes Inc., Waltham, MA 02451, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Afzal R. Mohammed
Pharmaceutics 2021, 13(7), 1033; https://doi.org/10.3390/pharmaceutics13071033
Received: 17 May 2021 / Revised: 29 June 2021 / Accepted: 1 July 2021 / Published: 7 July 2021
(This article belongs to the Section Pharmaceutical Technology, Manufacturing and Devices)
Optimizing processing conditions to achieve a critical quality attribute (CQA) is an integral part of pharmaceutical quality by design (QbD). It identifies combinations of material and processing parameters ensuring that processing conditions achieve a targeted CQA. Optimum processing conditions are formulation and equipment-dependent. Therefore, it is challenging to translate a process design between formulations, pilot-scale and production-scale equipment. In this study, an empirical model was developed to determine optimum processing conditions for direct compression formulations with varying flow properties, across pilot- and production-scale tablet presses. The CQA of interest was tablet weight variability, expressed as percentage relative standard deviation. An experimental design was executed for three model placebo blends with varying flow properties. These blends were compacted on one pilot-scale and two production-scale presses. The process model developed enabled the optimization of processing parameters for each formulation, on each press, with respect to a target tablet weight variability of <1%RSD. The model developed was successfully validated using data for additional placebo and active formulations. Validation formulations were benchmarked to formulations used for model development, employing permeability index values to indicate blend flow. View Full-Text
Keywords: quality by design; tablet weight variability; powder flow; process optimization; process model; direct compression quality by design; tablet weight variability; powder flow; process optimization; process model; direct compression
Show Figures

Graphical abstract

MDPI and ACS Style

Peddapatla, R.V.G.; Sheridan, G.; Slevin, C.; Swaminathan, S.; Browning, I.; O’Reilly, C.; Worku, Z.A.; Egan, D.; Sheehan, S.; Crean, A.M. Process Model Approach to Predict Tablet Weight Variability for Direct Compression Formulations at Pilot and Production Scale. Pharmaceutics 2021, 13, 1033. https://doi.org/10.3390/pharmaceutics13071033

AMA Style

Peddapatla RVG, Sheridan G, Slevin C, Swaminathan S, Browning I, O’Reilly C, Worku ZA, Egan D, Sheehan S, Crean AM. Process Model Approach to Predict Tablet Weight Variability for Direct Compression Formulations at Pilot and Production Scale. Pharmaceutics. 2021; 13(7):1033. https://doi.org/10.3390/pharmaceutics13071033

Chicago/Turabian Style

Peddapatla, Raghu V. G., Gerard Sheridan, Conor Slevin, Shrikant Swaminathan, Ivan Browning, Clare O’Reilly, Zelalem A. Worku, David Egan, Stephen Sheehan, and Abina M. Crean. 2021. "Process Model Approach to Predict Tablet Weight Variability for Direct Compression Formulations at Pilot and Production Scale" Pharmaceutics 13, no. 7: 1033. https://doi.org/10.3390/pharmaceutics13071033

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop