Safer, more reliable products and happier customers
Life science companies face massive challenges due to changing regulatory hurdles, increasing competition, and ever-higher levels of investment needed for successful innovation and product development and production. Data science can better equip companies in the life science sector to succeed amidst these challenges. By making the best of use of data from research, clinical trials, the production line, and customers themselves, life sciences companies can not only improve their customers’ lives but establish and maintain market leadership.
Characterize patient populations
Better characterize diseases and patient populations to identify treatment patterns, patient adherence, and more.
Develop products faster
More quickly analyze research records, databases, journal articles and other resources to find insights to help create the next breakthrough product.
Process customer feedback
Easily analyze unstructured feedback from virtually any data source to better understand product usage and gain insights for the next innovation.
Assess and manage product quality
Monitor product quality throughout the global value chain and remediate potential problems before they have a negative impact.
Prevent production downtime
Predict and proactively address production equipment failures to reduce costs by preemptively scheduling maintenance activities at the most cost-effective time.
Lightning Fast Data Science
Built for analytics teams, RapidMiner unifies the entire data science lifecycle from data prep to machine learning to predictive model deployment. Organizations can build machine learning models and put them into production faster than ever, using RapidMiner’s lightning fast visual workflow designer and automated modeling capabilities. 400,000 analytics professionals use RapidMiner products to drive revenue, reduce costs, and avoid risks.
