Artificial intelligence (AI) can be attributed back to the days of the earliest algorithms. One could argue that AI dates as far back as one of the masters, herself, Ada Lovelace. At the end of the day AI, and the algorithms that encompass it, can be boiled down to data and mathematical formulas. Its power was seen early through the application of another master, Alan Turing and his enigma machine, which was instrumental in bringing down the demise of the third reich.
Since those early days, mathematicians have created and evolved algorithms into new and more complex organisms over time. Machine learning (ML) has been taught and doctorates have been successfully defended in all manners of applied and theoretical fields of mathematics studies.
In that time, we have seen ML and AI have repeated renaissances with various time intervals, and the industry has shown interest in utilizing it for various commercial verticals. Yet, it hasn’t been until recently that we have seen such a prolonged resurgence of interest by both commercial enterprises and the lay public. The main driver of this resurgence has been the overwhelming amount of digitized data and modern-day processing power that graphical processing units (GPUs) have allotted. This is coupled with the popularity and success of modern-day monoliths of technology companies such as Amazon and Facebook. With these advances, we have seen and have come to rely on and interact with AI in our everyday lives. We rely on digital assistants to make appointments for us, decide what we would like to watch, make recommendations on what we should buy, suggest what route we should take when traveling and decide who we should date — and the list goes on and on.
Now, these very same leaders of technologies have set their sites on a new industry to disrupt: health care. This new race to unleash the powers of AI to overcome one of humanity’s greatest challenges, disease, began when arguably one of the best-known faces of AI, a company I’ve worked for in the past, announced new healthcare unit: IBM Watson was starting a health care division. Since then, there has been a gold rush of major technology companies and an overwhelming number of innovative startups that have come out to partner with health care networks of varying sizes to claim the ammunition in this new arms race: data.
As the cacophony of these announcements were made — and as the venture capitalists’ checks became larger and larger — the smart money was on the total eradication of disease and the near extinction of one of the most honorable of human professions: the physician.
However, after so much time and investment, that nirvana of a world free of disease has yet to materialize. Why? This isn’t to say we have had no progress. AI has made the greatest strides when combining the ever-growing silos of data. The greatest breakthrough AI has given us is it has shown us that traditional point-of-care medicine is not sufficient, nor has it been proficient enough to capture the complexities of disease or more importantly of wellness. It has shown us the deficiencies we have in truly evaluating a patient’s overall health and all the parameters that entail the evolution of pathology.
What we have learned is that the advancement of understanding must incorporate a panomic view of the patient, which merges all data points over the span of wellness and of the disease process to be able to fully understand the progression of pathology and to discover novel biomarkers of disease. It has also shown us that this panomic view must extend beyond just point-of-care medicine and incorporate a holistic view of the patient: diet, daily habits, routines, work, living conditions, environment, etc. We must go beyond the traditional data points. For centuries, physicians have been evaluating heart rate, respiratory rate and the like, and while these points are vital, we must leverage the strengths of AI to be able to go beyond base “omics” and develop new diagnostics by evaluating data that only machines can interpret, whether it be at the cellular level or within genomics, protein wrapping, pixel data, microbiome, molecular and even quantum levels of disease and wellness. It will be this integration of panomic data that will be the key to deciphering these enigmas and perhaps life’s greatest challenge: aging.
This integration of data and evolution of medicine, however, will need the proper supervision from physicians, ethicists, computer scientists and philosophers to be able to thread the needle of privacy and data security. It will take novel partnerships that you are seeing develop with such groups as Amazon, Berkshire Hathaway and JPMorgan to develop Haven to bring together the various degrees of expertise and resources needed to accomplish this task. As these and other partnerships progress, we will see that the future of health care AI and the key for a healthier future may, in part, lie in panomics.