Enabling Personalized Medicine Through Big Data

It is no secret that there is a digital transformation happening across life sciences and healthcare. This seismic shift is being facilitated by cutting-edge technology that is enabling the interrogation and aggregation of the vast quantities of data that we now have at our fingertips. The adoption of automated processes using technologies like artificial intelligence (AI), which incorporates human intelligence into machines through a set of rules, and machine learning (ML), an application of AI whereby the computer learns automatically through its experiences, is key to collecting and analyzing the vast and varied data that is now available and facilitating a move to a personalized approach to medicine.

A new realm of possibility

While the term has been used more frequently in recent years, personalized medicine is not a new concept; healthcare professionals have been tailoring treatment to an individual’s specific needs since the advent of medicine. However, the ground-breaking advancements being made today allow us to understand a patient’s potential susceptibility to certain diseases, and their predicted response to treatments. 

Facilitating this shift is the availability of ‘big data’, characterized by the three Vs:

• Velocity – the speed at which data is being collected
• Volume – the amount of data collected
• Variety – the broad range of data types being collected, for example imaging or unstructured data.