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Pharma Tech Outlook | Tuesday, January 18, 2022
To ensure that the patient is safe, visual inspection is used to identify defects and reject parenteral containers. Vials, glass bottles, pre-filled syringes, and blow-fill-seal containers, according to engineer Davide Luisari, design manager at Bonfiglioli Engineering S.r.l., are best to get supervised under (Automatic Visual Inspection)AVI. Visual inspection particularly looks for aesthetic defects such as scratches and dents. It also detects the foreign particles in the drug, which is the most crucial benefit of AVI.
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AVI is a combination of high-resolution cameras, illuminators, and computers that capture the image in motion from all angles and process the image to specialized software that detects the contaminants in the product. This process segregates the products into confirming and non-confirming packages. The latter is rejected automatically via algorithms. The finest visual inspection does not destroy products. A visual examination may either be manual or automatic:
Manual visual inspection: One or more qualified operators do this task.
AVI: A computer does the same tests as humans. These robots frequently outperform humans in terms of fault detection, false rejections, and speed.
AVIs are placed before labelling and packing, unlike manual methods, says Luisari.
“AVI systems are deployed end-of-line, generally before labelling and packaging,” explains Luisari. “Infeed and outfeed for AVI machines may be done in-line, either via belt-to-belt or by trays. Manual or automated product loading and unloading.” Identifying particle kinds early is important, according to John Shabushnig, principal consultant, Insight Pharma Consulting, LLC. This identification reduces the formulation's intrinsic particle burden.
“Identify and decrease particle contamination sources in manufacturing,” adds Shabushnig. While developing and manufacturing, visual inspection helps ensure that the product and process are stable.
The acceptance criteria described are based on a Knapp Test, which is a detailed test carried out to ensure that automated inspection is similar to manual inspection. Shabushnig recommends manufacturers drive process improvement by using particle characterization and identification information. Adds that advances in artificial intelligence (AI) can help improve inspection practices. The application of artificial intelligence (AI) to visual inspection for pharmaceutical products is increasing daily, says Bonfiglioli Engineering's Luisari. Many manufacturers have incorporated multiple testing methods into their production processes.
AI analysis refines the definition of 'acceptable' and 'defective' products, to generate an improved 'defects directory'. Inspections of injectable drug products are probabilistic and many defects will not achieve 100% probability of detection, says Shabushnig. Well-designed and operated inspection programs provide valuable information on the performance of the manufacturing process and contributes to the assurance of product quality.
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