Applications of Machine Learning in Solid Oral Dosage Form Development

This review comprehensively summarizes the application of machine learning in solid oral dosage form development over the past three decades. In both academia and industry, machine learning is increasingly applied for multiple preformulation/formulation and process development studies. Further, this review provides the authors' perspectives on how pharmaceutical scientists can use machine learning for right projects and in right ways; some key ingredients include (1) the determination of inputs, outputs, and objectives; (2) the generation of a database containing high-quality data; (3) the development of machine learning models based on dataset training and model optimization; (4) the application of trained models in making predictions for new samples. It is expected by the authors and others that machine learning will promisingly play a more important role in tomorrow's projects for solid oral dosage form development. (c) 2021 American Pharmacists Association. Published by Elsevier Inc. All rights reserved.

Automated summary

This review comprehensively discusses the application of machine learning in solid oral dosage form development over the past three decades, providing insights on how pharmaceutical scientists can utilize machine learning effectively. The authors anticipate that machine learning will play a more significant role in future projects for solid oral dosage form development.