The idea of “big data” transforming healthcare has existed for decades, but recent technological innovations are finally making big data accessible and usable in an actionable way. Artificial intelligence (AI) and advanced natural-language programming (NLP) tools are now able to read unstructured data, which constitutes the majority of healthcare data. Complex rules algorithms can now rapidly process such data to identify key clinical features in both individual patients and patient subpopulations.
These machine learning approaches can quickly and clearly establish which patients are nonresponsive to current therapies, as well as potential synergistic combinations that could enhance and prolong lives. Healthcare technology leaders have made immense strides over the past few decades, but there is still progress to be made when it comes to complex problems such as cancer care and clinical drug development. The 21st Century Cures Act, passed in 2016, has been a major driver of new technologies and applications, because it describes how to leverage vast amounts of electronic health data for new therapeutic innovations.