Role of Data Science in Life Sciences
Life sciences companies around the world are producing more data than they can handle. Hence they are leveraging the power of Data Science to gain an edge on their competitors. As Life sciences companies today are on the top of great achievements. With the technological advancements, every Life sciences company needs to adopt new solutions which are helpful for them in various ways to achieve their goals sooner. With the increased competition, regulation and margin pressures companies need to be more advanced and technologically sound to stay ahead in the competition. According to the McKinsey & Company, Implementation of Data Science in Healthcare Industry could save $300 billion annually which actually is a large amount. Life Science companies including pharmaceuticals, medical devices, and biotechnology face a huge challenge which can be solved with the help of Data Science and Analytics. Data Science drives the life sciences industry forward, optimizing nearly every dimension of the business.
For more information visit : http://canopusdatainsights.com/ Life Science companies can leverage Data Science and analytics in a new way to drive big decisions. Data Science can help the organization right from design, product planning, manufacturing to clinical trials which lead in better collaboration, cost optimization, failure prediction, information sharing and drive competitive advantage. Life sciences companies can benefit from Data Science in various ways: Risk analytics- To find the possible risks which can be caused by any impurity in the drug. Reduce cycle-times for clinical trials- Through better insights, cinical trials are streamlined to focus on specific populations and enable the “fast failures” and lead to reduced cycle time. Drug discovery & analysis- The biomedical data from various sources like pharma companies, laboratories, and hospitals are collected, analyzed and processed which help scientists in the discovery and reducing the cycle time for product development. Product failure analytics- Via predictive and root cause analysis of product failures. Inventory analytics- Building predictive models from internal and external data, that would predict the shortages in the availability of drugs impacting lost sales revenues & customer service levels. Enhance reporting systems- To meet the changing regulatory compliance needs more effectively
Real-time medical device analytics and visualizations- Leveraging Interconnecting data from implanted devices and personal care devices Social media analytics- To get the deeper customer perception about their products which help in improving the product and fixing current issues. An Indian Data Science Company, Canopus Data Insights is a leading provider of Data Science Products, Solutions and Services, to clients, from start-ups to large enterprises. It has expertise in generating insights from medical data and converting it into profitable business outcomes, be it Big Data or traditional data, structured or unstructured.