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For Productivity and Efficiency

Automation

Modern life sciences companies face many challenges and risks as they push the boundaries of science to invent new medicines and other products in a marketplace that is both highly competitive and stringently regulated. Use of automation is gradually spreading across pharmaceutical, medical device, and biotechnology companies, from clinical trials to regulatory compliance to the back office.


Mandated by the U.S. Food and Drug Administration (FDA), the Computer Systems Validation (CSV) process represents a critical step in the deployment and maintenance of software applications for life sciences companies. To improve the quality, efficacy and safety of products that affect human health, CSV helps verify that the computer systems that manage and maintain electronic records operate in a consistent fashion and yield consistent results based on their intended use. Many life sciences companies are moving to adopt robotics and cognitive automation (R&CA).


In life sciences industry, many companies struggle with enhancing the effectiveness of lifecycle management because of high costs, fragmented technology and processes affecting time to market with increased compliance risks due to limited visibility and collaboration. Automation of regulatory procedures can intensely improve the efficiency and productivity of manufacturers. Process automation can not only save time but also ensure that the product is manufactured in consistent manner with utmost reproducibility. Automation can help life sciences companies maximize product value by being compliant at all times with applicable regulations, keeping products in the market longer, and entering new markets faster. It controls deep domain knowledge in end-to-end regulatory affairs to streamline processes, embrace best practices, and standardize, where possible, while customizing to meet the unique requirements of each environment. Analytics experts further extend the power of the solution by combining the readily available regulatory data with other external data sources to provide alerts about potential regulatory, safety, or competitive risks by applying sophisticated predictive analytics. 



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