How to Improve Quality in Pharma Industry using Machine Vision

1. How to Improve Quality in Pharma Industry using Machine Vision HOW TO IMPROVE QUALITY IN PHARMA INDUSTRY USING MACHINE VISION Quality has always been the top concern in pharmaceutical manufacturing applications. Stringent FDA standards mean high levels of liability for errors in production. Machine vision plays a major role in delivering consistently high-quality products in the pharmaceutical industry, but machine vision can also deliver productivity gains, within the confines of strict quality demands. The pharmaceutical industry was one of the earliest adopters of machine vision, as the incentives to guarantee product integrity and safety have always been foremost in this industry. Machine vision technology has advanced significantly over the years since its initial entry into the industrial sector. It is now suited for very specific applications in the pharmaceutical industry and creates productivity in a number of ways. Manufacturing, shipping, and data processing are the most common use cases for machine vision in the pharmaceutical space. Machine vision has automated many different applications. Typically, machine vision technology is used for critical processes such as:

2. QUALITY CONTROL FOR PRODUCT AND PACKAGING One of the most prominent applications for machine vision software in pharmaceuticals is in the quality control and packaging departments. The possibilities for these range from the quantity and condition detection to the inspection of packaging and included items such as printed instructions and dose applicators. Companies can utilize machine learning on the production and packaging lines to ensure each of their production units meet their organizational quality requirements and other compliances. The business problems within pharmaceutical quality control and packaging inspection that machine vision addresses most often are as follows: Counting the number of pills each bottle is filled with • Inspecting each pharmaceutical pill for accurate dimensions and any damage • Inspecting packaging for quality control or damage • Quality control of secondary items such as the instruction leaflet • Label validation for product information and barcodes • Quality control can also be extended to a product’s packaging when used to detect the presence of childproof caps, plastic wrappers over bottle caps, the correct box, or any other packaging element. A camera at the end of the production line could feed a machine learning model footage of each unit being packaged, and it would scan the video for each item being attached properly. Also Read: Understanding Cost of Quality while investing in Quality Control Automation SHIPMENT TRACKING AND PRODUCT TRACEABILITY In the pharmaceuticals domain, it is imperative that drugs and all other products be trackable on their way to stores and distribution centers for maximum accountability and compliance. The products

3. must also be traceable from the patient’s possession back to the manufacturer in case of any defects or unforeseen side effects. Pharmaceutical companies are responsible for providing all the necessary tracking and manufacturer information with all of their products. Machine vision solutions can help consolidate all this information and deliver it across channels during many steps of the shipping process. Companies can utilize machine vision software to ensure their tracking information is both accurate and readily available across the channels that would need to access it. This could be in the case of an emergency or a simple customer service inquiry. The possible departments that could benefit greatly by using machine vision technology for this purpose are as follows: Factories and each of their various production lines • Distribution Centers • Warehouses • A machine learning model could also be trained to detect information from barcodes for retail inventory and serialization codes to prevent counterfeiting. Serialization codes could be related to the date of manufacturing as well as the factory or production line where the product was manufactured. This could help pharmaceutical companies to determine where and when a given product unit was made if they were ever asked. Related Article: 7 Common Applications of Machine Vision in Manufacturing DIGITIZATION Another major possibility for machine vision in pharmaceuticals is the automation business processes such as document digitization and data entry. A machine learning model for OCR trained in clinical and pharmaceutical forms could discern and extract key data points from those forms and deliver them to a database. This can prove to be tremendously useful for companies with a large number of physical forms containing data that they want to use for future projects. Machine vision could help digitize the following documents and more: Clinical Trial Documents • Clinical data or medical records from patient reports •

4. Lab Notebooks • • Patient reports may contain useful information about a patient’s response to a drug and the severity of any side effects. This is especially important if a new side effect is discovered or if the patient has an allergy to the drug. With proper digitization both the business and the customers can benefit as the company can factor in every past patient reaction and use that awareness to drive patient health and satisfaction. Read More: https://bit.ly/35kOg4r