Author: Jim Walker, Contributing Editor, PharmaLeaders

At the recent EyeForPharma “Marketing & Customer Experience” session in Philadelphia, it was not surprising to learn that many Big Pharma companies have been embracing Big Data solutions. In fact, data has been at the heart of pharma R&D for decades. Recently, as customer data sources have exploded, many firms are staffing up their data teams to tackle the other end of the pipeline – namely applying machine learning and data algorithms to address complex commercial challenges.

Taking a deep dive into Big Data, Steve Wong and Zheng Yang from Boehringer Ingelheim each presented a wide range of cases where BI is harnessing data to do everything from optimize product shipping and logistics to analyzing mobile data that measures the prevalence of coughing in a target population.

Interestingly, the latest Gartner tracking has found we are at the peak of the AI and Deep Learning Hype Cycle.

If it feels like this Big Data story never gets old, it might be because, according to Gartner, that we have been at a Hype Peak for Machine Learning and Deep Learning for the past four years!

So where do we go from here? If the adoption curve holds true, the hype will finally start to die down and there might even be a backlash. Eventually though, in the 2020s we should see countless applications emerge for AI and machine learning across all aspects of healthcare, which will impact not just R&D, but commercialization and clinical practice as well. In the meantime, teams at BI and elsewhere will continue to leverage their deep expertise across a range of groundbreaking commercial challenges.