Radical change at all levels of healthcare demands new solutions and better ways of managing the enormous volumes of data now impacting human health. The task is monumental and urgent. The cost to bring a new drug to market is enormous. At the same time, the potential for these drugs is becoming narrower and more specialized. Streamlining processes, prioritizing investments, and improving outcomes are critical not only to the industry but also to individual patients.
Data-driven insights and analytics can have a positive impact. The data now exists to transform drug research, discovery and development, as well as the practice of evidence-based healthcare. But tapping data from many sources and making sense of it is a tremendous challenge. The sources are many and varied. The volume is enormous.
The format can be unstructured, residing in clinical trials, medical papers, insurance claims, health records and even in the human genome. The evidence is there for a better, more efficient healthcare system. But curating that data and analyzing it is beyond human capability. New technologies and approaches are opening broad new opportunities to manage, analyze, and put to productive use the huge volumes of medical and healthcare data and information.
The Enterra Enterprise Cognitive SystemTM — AilaTM — combines the efficiency and accuracy of cognitive computing with natural language processing to acquire and understand the clinical research and evidence necessary to deliver more reliable ways of discovering drugs and practicing medicine.
Aila provides an artificial intelligence platform that can find the nuanced relationships inside huge volumes of data. This includes information that can illuminate drug interactions, surface important evidence-based research, as well as uncover unseen risks, cures and treatments that create a healthier world for us all.