Title: New possibilities in real-time quality control with new generation machine vision technology

Biography:

Nika Oman Kadunc completed her degree in Physics in 2009 at the University of Ljubljana. She participated in several research and development projects involving software development, machine vision algorithms and industrial sensor development. 

Abstract

The aim of improving the quality of pharmaceutical end products and optimizing production efficiency drives the need for progress in real-time quality control with process analytical technology (PAT) tools for monitoring critical quality and performance attributes. Multiparticulate dosage forms – using coated or uncoated pellets or granules – are increasingly used in the production of solid dosage forms as they enable favourable release profiles of active ingredients. With these, the Critical Quality Attributes (CQAs) that affect the physicochemical properties of drug substances and final dosage forms are particle size, particle shape and, with coating applications, also coating thickness and coating uniformity. The machine vision technology brings advantages over other PAT techniques as it provides means of contactless, non-invasive, non-destructive, fast and accurate automatic measurements of particles together with easy implementation and calibration. The benefits of the presented PAT technology offer new possibilities for optimizing and a better understanding of production processes and, subsequently, of the end product quality assurance.