Category: Pharma Update

Optimized product and process improvement is important to CxOs. In particular, for the pharmaceutical manufacturing sector, Big Data analytics can be used to generate deeper insights to identify process bottlenecks and improve operational efficiency. Big Data enables multi-dimensional analysis to determine the performance of a particular drug. This input can be used to build various strategies to enhance the performance of that drug and quality of associated services and products.

The top priority for pharmaceutical and life sciences companies is to improve the quality of human health and wellbeing. Big Data helps achieve this priority by leveraging innovative techniques to enhance productivity in R&D, and reducing the cycle time for drug development and delivering them to the correct market and customer segments.

The life sciences industry is no exception to this revolution. Big Data is generated in the form of RFID and sensor data from medical devices and pharmaceutical manufacturing organizations, raw data from various state-of-the-art machines that process blood samples, tissues and so on. This large volume of data can be processed using a Big Data platform to support scientific analytics.


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