Researchers at the University of Toronto say they have successfully tested the use of machine learning models to guide the design of long-acting injectable drug formulations. The potential for machine ...

Early on, the drug substance (DS) manufacturer will provide a wealth of preliminary characterization data. And if the drug is active in early nonclinical and preclinical testing, a larger quantity of ...

Formulation complexity, especially in small molecule drugs, has been getting more attention as capabilities continue to ...

This interview addresses the challenges and complexities of developing and manufacturing controlled-release drug formulations. Could you introduce yourself and your expertise in drug development and ...

In the world of drug discovery and clinical trials, drug formulation can make or break a product’s success, yet its role often goes underappreciated, says Christine Allen, cofounder and CEO of ...

Mood and anxiety disorders represent a leading cause of disability worldwide. Current first-line pharmacological treatments, ...

The Central Drugs Standard Control Organisation (CDSCO) has issued a clarification on the regulation of formulation ...

To optimize the final formulation for a drug, it must meet many criteria beyond producing a safe and effective product. For example, it must be stable and amenable to various manufacturing steps, such ...

A new study in the Journal of Managed Care & Specialty Pharmacy finds that the introduction of new formulations of drugs often delays the introduction of generic competitors by two or more years. The ...

Scientists have successfully tested the use of machine learning models to guide the design of long-acting injectable drug formulations. The potential for machine learning algorithms to accelerate drug ...

In the last 10 years, there has been significant development in computer simulation of pharmaceutical materials, processes and product performance. Gradually, more mechanistically based models are ...