Precision Medicine in the Cognitive Computing Era.

2016 reminded us of how much work needs to be done in the search for predicting and finding a cure for #heart disease with the loss of Princess Leia!

Cardiovascular diseases like cancer continues to accounts for millions of death and lost productivity in the USA so finding a moon shot to cure cardiovascular disease and cancer could be a defining moment in medicine as was the discovery of penicillin to fight infection about half a century ago. We need to begin to predict disease patterns before they happen ,maintain health through population based approaches and redefine how we categorize and manage chronic diseases by integrating precision medicine platform technologies.

2017 and the Precision Medicine Era :A New Beginning!

Precision medicine seeks to take into account individual variability in genes, environment and lifestyle by leveraging a host of platform technologies which include genomic risk profiling technology, point of care diagnostic testing, wearable and remote monitoring platforms, targeted drug discovery, synthetic biology, cognitive computing and BIG DATA Science to predict disease before it happens and deliver personalized, precise treatments at the right time.

Preparing for the quantified self!

The quantified self-movement is in full swing with according to Pew Internet and American Life Project’s report 69% of U.S. adults keeping track of at least one health indicator such as weight, diet, exercise routine, or symptom with half-tracking “in their heads” one-third keeping notes on paper, and one in five using technology to keep tabs on their health status. Research by the Center for Medicare and Medicaid Services shows national health care expenditures are nearing $3 trillion dollars per year. By making so many things intelligent with embedded networked sensors, we can add intelligence to almost anything with all those sensors continuing to create rapidly increasing amounts of data which so far has not found its way into our electronic health medical records.

The Panomic Data Era !

A combination of genomic, epigenomic, transcriptomic, and metabolomics information - a patient’s ‘panomic’ data –could soon be part of a proposed personal health record (PHR).We could soon start to see a shift in medical data ownership with an increasing shift to patient ownership with individuals and or populations able to store their own genomic, wearable and other personal medical data sets. As this shift happens there would be a need to develop standards for standardization  patient owned and generated data as well as finding efficient ways to store such large amounts of patient owned data with the purpose of developing predictive clinical decision support tools in real time at the point of care.

Precision medicine and the promise to predict and cure disease!

Precision medicine requires a thorough knowledge and handling of multi-parametric data sets with proficiency in interpreting “-omics” data which places new demands on the medical professionals who may be ill equipped currently to deal with the anticipated complexity and volume of new information currently been generated from wearable platforms, genomic data sets, point of care diagnostics, synthetic biology platforms as well as data generated from big data projects using cognitive computing and machine learning algorithms. Addressing these complex challenges will require development of new effective clinical decision support tools and new learning systems by leveraging cognitive computing tools like Watson and deep learning platforms like Nvidia to be integrated in decision and clinical support workflows . Decision support tools will have the potential to address these limitations and enable precision-medicine approaches to healthcare by providing clinicians and patients with individualized information and preferences, intelligently filtered at the point of care. Decision supported tools powered by cognitive computing will provide clinicians with options for tests ordering indicating the sensitivity, specificity, and positive predictive value of tests; and aid clinical workflows by providing algorithms to facilitate decisions on the basis of these test results. Diagnostic support tools will enable clinicians new analytical tools that enables us to pinpoint patient-specific differences and on the treatment side novel therapies and new technologies will permit us to exploit those differences for better patient outcomes. Innovative therapies such as ivacaftor, a cystic fibrosis treatment that targets only a small set of mutations in the CFTR gene, could be weapons in our treatment armamentarium to provide the ‘right drug in the right dose at the right time’ using precision medicine platforms.

“To me, the goal is simple ... It’s to identify the people who need the treatment the most and who stand to benefit the most, and to avoid ... exposing people to side effects who don’t stand to gain” – By Erik Swain.

The cognitive computing era is upon us and precision medicine could radically change how medicine is practiced ,delivered ,financed and taught . Precision medicine may also change the way we regulate ,finance and conduct research and development and promises to deeply affect public trust and the nature of the patient–clinician relationship at the same time requiring unprecedented collaboration among health care stakeholders using collaborative virtualized platforms . Let's prepare for that exciting future acknowledging that the knowledge and practices of yesterday may not be enough but we can rely to a new future where we can redefine how we predict and treat diseases using precision medicine platform technologies.

This article is part of the LinkedIn Top Voices list, a collection of the must-read writers of the year. Check out more #BigIdeas2017 here.