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...

Predicting pharmaceutical powder flow from microscopy images using deep learning

2. March 2023

The powder flowability of active pharmaceutical ingredients and excipients is a key parameter in the manufacturing of solid dosage forms...

Machine learning using multi-modal data predicts the production of selective laser sintered 3D printed drug products

7. February 2023

Three-dimensional (3D) printing is drastically redefining medicine production, offering digital precision and personalized design opportunities. One emerging 3D printing technology...

Advancing oral delivery of biologics: Machine learning predicts peptide stability in the gastrointestinal tract

2. February 2023

The oral delivery of peptide therapeutics could facilitate precision treatment of numerous gastrointestinal (GI) and systemic diseases with simple administration...

The applications of machine learning to predict the forming of chemically stable amorphous solid dispersions prepared by hot-melt extrusion

31. January 2023

Amorphous solid dispersion (ASD) is one of the most important strategies to improve the solubility and dissolution rate of poorly...

Surrogate modeling of dissolution behavior toward efficient design of tablet manufacturing processes

23. January 2023

This paper presents surrogate models of dissolution behavior to identify the critical input parameters in tablet manufacturing processes. Dissolution behavior...

Machine learning models to accelerate the design of polymeric long-acting injectables

20. January 2023

Long-acting injectables are considered one of the most promising therapeutic strategies for the treatment of chronic diseases as they can...

The next generation of evidence-based medicine

20. January 2023

Recently, advances in wearable technologies, data science and machine learning have begun to transform evidence-based medicine, offering a tantalizing glimpse...

Patient-specific in vitro drug release testing coupled with in silico PBPK modeling to forecast the in vivo performance of oral extended-release levodopa formulations in Parkinson’s disease patients

26. October 2022

Biorelevant in vitro release models are valuable analytical tools for oral drug development but often tailored to gastrointestinal conditions in ‘average’ healthy...

Technology development to evaluate the effectiveness of viscosity reducing excipients

22. September 2022

Addition of pharmaceutical excipients is a commonly used approach to decrease the viscosity of highly concentrated protein formulations, which otherwise...

Machine Learning