Marketing

Process (computing)

Engineering

Biology

Materials science

Coating

Image processing

Work in process

Operating system

Tableting

Computer science

New product development

Chemical engineering

Manufacturing engineering

Business

Process analytical technology

Mechanical engineering

Nanotechnology

Bioinformatics

Mathematics

Flow (mathematics)

Image (mathematics)

Machine vision

Critical quality attributes

Residence time distribution

Process engineering

Operations management

Artificial intelligence

Geometry

Composite material

Quality by Design

Pharmaceutical manufacturing

Granulation

European Journal of Pharmaceutical Sciences

The goal of this paper is to give an introduction to analysis of images acquired by a digital camera with visible illumination and to review its applications as a Process Analytical Technology (PAT) which has great potential in pharmaceutical manufacturing. By utilizing in-line analytical techniques, it is possible to monitor the quality of all the material leaving a processing unit and to create models capable to predict product quality attributes, which are otherwise measured by cumbersome off-line techniques. The rapidly developing machine vision has proven its versatility in numerous applications and it has great potential as an in-line analytical tool. The ongoing conversion of the pharmaceutical industry from batch to continuous manufacturing accelerated the development of digital image analysis methods in the last decade. Among numerous other benefits, continuous technologies, equipped with digital image analysis, enable detecting disturbances in the material flow, and analyzing the products comprehensively. The purpose of this work is to give an insight into the currently available image analysis methods in the characterization of powders, crystallization, granulation, milling, mixing, tableting, film coating, in vitro dissolution testing, and residence time distribution measurements by highlighting some of the most relevant examples of application.

Applications of machine vision in pharmaceutical technology: A review