Machine Learning is making great strides for the Pharmaceutical industry in drug development and pharmaceutical operations. Artificial Intelligence has helped in making Drug Discovery and Manufacturing much more efficient, bringing new drugs to clinical trials, and for public usage, in a faster and cost effective manner.
NATURAL LANGUAGE PROCESSING
Pharmaceutical companies save their lab notes and clinical trial data into databases to record their observations of certain drugs, molecules, and chemicals. AI tools can enrich drug research by extracting information from these unstructured data sources and use them in the testing of current and future drugs. NLP applications can be taught to understand pharmaceutical jargon and search this data for topics, phrases and terms, for findings that are more relevant to the company’s current research than initially discovered. AI assists in saving countless man-hours in unnecessary research and saves the costs for conducting additional research experiments.
Pharmaceutical Quality Control
Packaging and Labeling of Pharmaceutical Products have to adhere to strict guidelines, but manual inspections can be error-prone and inadequate. A Computer Vision model fed with video data from the production line can ensure quality adherence in packaging and labeling. The AI can detect concerning attributes of the packaged product, such as tampered sealings, compromised packaging materials, absence of child-proof caps etc. Printed barcodes and labels can be checked for accuracy and visibility using optical character recognition (OCR) technology. AI ensures that there are no deviations from the standards set by the manufacturer.
Packaging and Labeling Quality
Pharmaceutical companies are accountable for providing the highest quality of the medicines and drugs to the public. Implementation of AI assists these companies in maintaining industry standards and guarantee the quality of their products. High-resolution video feeds of the production line are monitored using Computer Vision. This AI implementation can track the condition of the product, including conformity of shape and size, damaged pills if the standardized fill rate is being met for each product container etc. AI circumvents the need for error-prone manual inspections, alerting operations personnel to abnormalities in the production process. This saves the company millions each year from producing medicines and drugs that are not fit for use.
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