Multi-sensor inline measurements of crystal size and shape distributions during high shear wet milling of crystal slurries

Okpeafoh Stephen Agimelen, Vaclav Svoboda, Bilal Ahmed, Javier Cardona, Jerzy Dziewierz, Cameron Brown, Thomas McGlone, Alison Cleary, Christos Tachtatzis, Walter Michie, Alastair Florence, Ivan Andonovic, Anthony Mulholland

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Size and shape distributions are among critical quality attributes of particulate products and their inline measurement is crucial for monitoring and control of particle manufacturing processes. This requires advanced tools that can estimate particle size and shape distributions from multi-sensor data captured in situ across various processing steps.

In this work, we study changes in size and shape distributions, as well as number of particles during high shear wet milling, which is increasingly being employed for size reduction in crystalline slurries in pharmaceutical processing. Saturated suspensions of benzoic acid, paracetamol and metformin hydrochloride were used in this study. We employ our recently developed tools for estimating particle aspect ratio and particle size distributions from chord length distribution (CLD) measurements and imaging. We also compare estimated particle size distributions from CLD and imaging with corresponding estimates from offline instruments.

The results show that these tools are capable of quantitatively capturing changes in particle sizes and shape during wet milling inline. This is the first time that such a capability has been reported in the literature. The ability to quantitatively monitor particle size and shape distributions in real time will enable development of more realistic and accurate population balance models of wet milling and crystallisation, and aid more efficient control of crystallisation processes.
Original languageEnglish
JournalAdvanced Powder Technology
Publication statusPublished - 31 Dec 2018

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