Overcoming Challenges Using AI and Machine Vision in the Pharmaceutical Industry

For pharmaceutical companies to increase their R&D output, it’s important to have reliable pharmaceutical vision inspection systems for samples and developed solutions. Such systems must be cost-effective, efficient, and reliable. Many companies are turning to machine vision for the pharmaceutical industry in-line inspection needs. These vision technologies offer lightning-fast ways to inspect samples accurately for informed conclusions.

Until recently, the identification of drug targets has been a concern due to many factors, including limited data and tools. Finding specific molecules or cells in the body responsible for a particular disease or health condition is not a procedure done by conventional equipment. This task requires high-content screening, image-based phenotyping, and machine learning-based analysis, to mention a few. Pharmaceutical vision inspection systems can be trained to recognize image patterns to identify potential drug targets, predict solutions, and develop actual solutions.

Key Inspection Points

In the medical industry, the need to track individual packages throughout the production process continues to increase. With machine vision, it is possible to perform a variety of inspections - such as character, barcode, and label inspections - with a single device.

Another long-standing challenge in drug discovery and development is innovation. Because of rising costs of research, patent concerns, and pricing pressure, it might be difficult for pharmaceutical companies to stay at the forefront of changes in generative AI, artificial intelligence, and digital technology. However, they must find ways to keep up with the trend so they can continue developing new products and treatment solutions that meet the evolving needs of modern patients. Again, machine vision systems offer solutions in this case.

Instead of carrying out inspections manually, machine vision systems drug companies to automate product inspections for tablets, vials, capsules, and more. For example, in a fast-moving medicine production line, vials could be subjected to contamination or cross-contamination. The vials may also not be filled to the required level. These or similar situations cannot be tolerated.

This is where machine vision for the pharmaceutical industry comes into the picture. Detecting issues relating to quality in a fast-moving line is nearly impossible for human vision. Machine vision systems have high quality cameras and machine vision software for the pharmaceutical industry. This combination of features helps detect contaminants, ensure consistent fill levels, identify defects, and enhance overall product quality.

Considering all the benefits that machine vision systems offer, pharmaceutical companies need to embrace this innovation. This way, they can solve innovation-related, drug discovery and development, and other long-standing challenges in the industry.

Lot codes, branding, expiration dates, and other critical manufacturing information must be verified as correct before final goods depart the facility. Prints are typically very small. So it’s very possible and common for errors in labeling to go unnoticed, particularly for human eyes and traditional inspection equipment. The fact that drug manufacturing lines have a high volume of packages that need to be inspected every day underscores why antiquated systems are not effective.

With the new KEYENCE VS Series smart camera, drug manufacturers can achieve precision-based and lightning-fast quality control. The VS Series can scan labels and blister packs for errors, defects, and omissions. The vision system has an inbuilt AI model and rule-based programming to deliver powerful product quality and yield.

Printing defects on tablets running on high-speed production lines cannot be detected sufficiently with older automated systems or human vision. An entire batch of products may need to be condemned because of defects, resulting in unnecessary waste and increased production costs. In cases where defects go undetected, it could lead to costly recalls, fines, or serious legal situations. As an AI-enabled vision system, KEYENCE’s VS Series provides superior functions that enable pharmaceutical companies to inspect high-volume tablets or pills individually.

Opened or damaged packaging could signal contamination or “dent” in the quality of tablets, pills, or raw materials. AI-powered pharmaceutical vision inspection systems use sensor technology to detect anomalies in product conditions. These conditions could be abnormal increases in temperature levels, humidity fluctuations, damaged packaging, or opened packages. AI-enabled vision system solutions offer AI machine-learning algorithms to identify patterns of signaling contamination. They also come with monitoring units that can alert quality control teams to potential tampering in real time. KEYENCE’s AI-powered vision systems can help in these situations.

Deep learning is a subset of artificial intelligence that imitates the human brain’s neural networks which is aimed at imitating those of the human brain to recognize patterns and make intelligent decisions without external actors. Deploying the right AI vision systems means having a solution that can be trained on large datasets to recognize risk patterns. This would help in the identification of contaminants, defects, and other anomalies with remarkable accuracy.