A multi-step machine learning approach for accelerating QbD-based process development of protein spray drying

22. June 2023

This study proposes a new material-efficient multi-step machine learning (ML) approach for the development of a design space (DS) for...

Application of unsupervised and supervised learning to a material attribute database of tablets produced at two different granulation scales

26. May 2023

The purpose of this study is to demonstrate the usefulness of machine learning (ML) for analyzing a material attribute database...

Predicting pharmaceutical inkjet printing outcomes using machine learning

28. April 2023

Inkjet printing has been extensively explored in recent years to produce personalised medicines due to its low cost and versatility....

Machine learning approaches to the prediction of powder flow behaviour of pharmaceutical materials from physical properties

17. April 2023

Understanding powder flow in the pharmaceutical industry facilitates the development of robust production routes and effective manufacturing processes. In pharmaceutical...

Machine learning in additive manufacturing & Microfluidics for smarter and safer drug delivery systems

18. March 2023

A new technological passage has emerged in the pharmaceutical field, concerning the management, application, and transfer of knowledge from humans...

Formulation and Characterization of Buccal Films Containing Valsartan with Additional Support from Image Analysis

17. March 2023

The present study was aimed to the development and characterization of valsartan-containing buccal films with an introduction to a novel...

Technological advances and challenges for exploring attribute transmission in tablet development by high shear wet granulation

16. March 2023

High shear wet granulation and tableting (HSWG-T) are complex pharmaceutical processes, which makes tablet quality be influenced by many variables...

Machine Learning