Predicting pharmaceutical powder flow from microscopy images using deep learning-Reference-Cited by-同舟云学术

Predicting pharmaceutical powder flow from microscopy images using deep learning

Published:2023 Issue:2 Volume:2 Page:459-470
ISSN:2635-098X
Container-title:Digital Discovery
language:en
Short-container-title:Digital Discovery

Author:

Wilkinson Matthew R.¹²³^ORCID,Pereira Diaz Laura⁴^ORCID,Vassileiou Antony D.⁴^ORCID,Armstrong John A.⁴^ORCID,Brown Cameron J.⁴^ORCID,Castro-Dominguez Bernardo¹²³^ORCID,Florence Alastair J.⁴^ORCID

Affiliation:

1. Department of Chemical Engineering, University of Bath, Claverton Down, Bath BA2 7AY, UK

2. EPSRC Future Continuous Manufacturing and Advanced Crystallisation Research Hub (CMAC), University of Bath, Claverton Down, Bath BA2 7AY, UK

3. Centre for Sustainable and Circular Technologies (CSCT), University of Bath, Claverton Down, Bath BA2 7AY, UK

4. EPSRC Future Continuous Manufacturing and Advanced Crystallisation Research Hub, c/o Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK

Abstract

We present deep learning to predict the flowability of pharmaceuticals from microscopy images. This enables flowability assessments with smaller API quantities, saving experiment time and costs when material is limited during early drug development.

Funder

Higher Education Funding Council for England

Engineering and Physical Sciences Research Council

University of Bath

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2023/DD/D2DD00123C

Reference38 articles.

1. Comparison between integrated continuous direct compression line and batch processing – The effect of raw material properties

2. Provoking an end-to-end continuous direct compression line with raw materials prone to segregation

3. A Demonstration of Mixing Robustness in a Direct Compression Continuous Manufacturing Process

4. Lubricants in Pharmaceutical Solid Dosage Forms

5. An Estimate of Hopper Outlet Size and Slope for Mass Flow from the Flowability Index

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