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

Okpeafoh S Agimelen,Vaclav Svoboda,Bilal Ahmed,Javier Cardona,Jerzy Dziewierz,Cameron J Brown,Thomas Mcglone,Alison Cleary,Christos Tachtatzis,Craig Michie,Alastair J Florence,Ivan Andonovic,Anthony J Mulholland,Jan Sefcik

doi:10.1016/j.apt.2018.09.003

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.

Highlights

Quantitative particle attributes such as particle size and shape influence behaviours of slurries and powders such as flowability, filterability and dissolution
The two-dimensional volume based probability density function (PDF) of particle length and aspect ratio estimated using offline imaging (Morphologi G3) for both the starting material and the final milled product for benzoic acid are shown in Fig. 2(a) and (b), respectively2
The results show that these tools are suitable for monitoring changes in particle size and shape distributions and number of particles in slurries

Summary

Introduction

Quantitative particle attributes such as particle size and shape influence behaviours of slurries and powders such as flowability, filterability and dissolution. These behaviours in turn determine performance of various downstream operations carried out in the manufacturing process as well as performance of resulting particulate products. There are several approaches providing empirical control of particle size distributions (PSD) in crystallisation processes, such as seeding (to provide control over particle number concentrations) [4] and high shear wet milling (to provide control over particle size).

Methods

Results

Conclusion