Source: forbes.com
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. By outlining strategy and future policies, it’s catalyzing an ecosystem of industry, provider, payer and academic research partners, thus paving the way for AI to become a critical tool for life science innovators working toward the future of precision and personalized medicine.
Today’s AI technologies are already providing significant utility through basic rules-based and imputation models which enrich and augment real-world data (RWD) that would otherwise be lost to missingness and human error. Forbes Technology Council member Jeff Elton is CEO of Concerto HealthAI, a leading innovator of healthcare solutions utilizing new and emerging RWD and AI technology. Elton believes that, as these technologies mature, they will become an integral part of the patient diagnosis, treatment and care management journey.
At Concerto HealthAI, Elton is leading breakthrough work in the use and integration of RWD and AI in cancer research and clinical trials in collaboration with the American Society of Clinical Oncology, the U.S. Food and Drug Administration and some of the world’s leading biomedical innovators, including Bristol-Myers Squibb and Pfizer.
Much of this work, as well as its current implications and future directions, are presented in his book, Healthcare Disrupted, published in 2016.
“At Concerto HealthAI, we’re constantly looking to revolutionize the use of RWD and accelerate the insights that lead to improved patient outcomes. To address this, we’ve developed some basic but powerful models that use AI to enrich and expand the utility of RWD,” Elton said. Through partnerships with ASCO’s CancerLinQ®, the FDA and a range of healthcare providers, the company has harnessed the abilities of AI and RWD to improve and expand clinical trials, increase accessibility to new treatments and speed up clinical drug development timelines.
According to Elton, focusing innovation on RWD and AI is boosting both patient outcomes and business revenues: “We’ve already developed an AI model that can correctly identify 32% more cases of metastatic breast cancer compared to simple database queries with traditional business rules. Another one of our AI models has been able to predict the survival of lung cancer patients three to 12 months from their last clinical visit. This is being recognized by the marketplace as well; our Q4 2019 revenues are more than 100% greater than they were only a year ago.”
His advice to healthcare providers and innovators looking to benefit from big data is to treat it like crude oil. “You need to define end-products of value, sometimes combine sources and always add a catalyst to get to the jet fuel or higher performance plastics that meet your use case.” He emphasized AI’s potential to enhance and augment data while providing a new lens on traditional challenges. “Whereas traditional statistical and tabular approaches might be limited by missingness and messiness, AI-augmented data is not.”
These new modes of insight and actions enabled by AI will likely reconceive many facets of the healthcare industry, especially the structure and patient subpopulations of clinical trials, as well as post-approval analysis of positive and negative outcomes. Elton says we have only begun to scratch the surface of engineered RWD and AI in healthcare. By partnering with researchers and scientists to first understand what their biggest research questions are, then think about how data, technology and AI might help them get answers fast, accurately and reliably, Elton is devoting his work at Concerto HealthAI to finding the best applications for this technology.