MedCity Influencers, Health IT

Data: The central component of precision medicine

Realizing the full potential of precision medicine starts with finding better ways to collect, share and make decisions based on data.

Precision medicine – the practice of taking individual variations in genetic, lifestyle and environmental factors into account when developing treatment plans – will have a strong positive impact for patients and providers alike. For example, the presence of certain biomarkers in a cancer patient’s genome can accurately predict the efficacy of a particular drug.

Realizing the full potential of precision medicine starts with finding better ways to collect, share and make decisions based on data. Patients must be placed into subgroups based on characteristics known to impact risks, diagnoses and outcomes. Big data thinking is essential for identifying these characteristics with confidence, but unfortunately, most hospitals and physician groups are not yet ready to support this form of analytics. There are a number of daunting challenges that must be overcome first:

Data collection
For each relevant subgroup, data must be collected from thousands of patients, a huge task in itself. Furthermore, there is still significant uncertainty as to what data should be collected. This is particularly true with the human genome, where our understanding is still in its early stages.

One possibility is pooling the data that already exists in large organizations to facilitate cooperation. That way, institutions can identify which dimensions of data are relevant and then create a baseline using whatever data is available.

Data Incompatibility
The data needed to support precision medicine is currently siloed in a large number of incompatible systems. From a technical point of view, integrating data from providers, payers, pharmaceutical companies and medical device companies to be analyzed is a huge task.

Business partnerships and consolidations may help with both data collection and integration. For example, a large pharmaceutical company could acquire a health insurance company to give the Healthcare giant the control needed to meld the companies’ two data ecosystems.

Data sharing
Beyond technical considerations, there are other serious issues. To protect privacy, patient consent is mandatory before medical records can be shared, making data collection even more cumbersome. Not all participants in the ecosystem are willing to share data; a new regulatory framework that facilitates sharing is needed first. 

Studying the human genome is expensive, and its cost is another barrier that must be overcome. The good news is while precision medicine can claim clinically documented successes, it is still in its infancy and not always able to attract the necessary funding.

Competing Priorities
Most participants in the healthcare industry must deal with a variety of issues ranging from improved patient outcomes and chronic care management to regulatory compliance and competition in their respective markets. Under these conditions, making precision medicine a priority is a significant challenge.

There are, however, some exceptions. For example, one New York City hospital network now operates a clinic that provides patient care but also conducts data science initiatives for populations as well as individuals.

The Solution Exists
From a high-level perspective, precision medicine has much to offer both patients and providers, and it is no surprise that the market is predicted to reach over $88 billion by 2022. There are certainly challenges related to data, costs and organizational priorities, but there is also evidence that these challenges can be met. There are platforms to manage the huge amounts of disparate medical data exist, along with algorithms to provide actionable insights leading to testable treatment hypotheses. Given the data tools available, and the dedication of so many research teams within the larger medical ecosystem, it is inevitable that precision medicine will flourish over time.




Venky is an SVP and global head of Infosys’ Healthcare Industry Vertical. In this role, he is responsible for profitable growth of Infosys’ Healthcare business. His responsibility straddles Infosys Healthcare strategy, market innovation, building high performance teams and managing critical relationships with senior client executives in the Healthcare industry. He has deep understanding of Healthcare business and specializes in leveraging technology to solve business problems at scale. Venky has spent over two decades with Infosys and has broad experience spanning multiple industries and geographies. He has won a multitude of excellence awards and Gold Standard awards for outstanding achievement ranging from thought leadership in the industry to client management. He holds an undergraduate degree in mechanical engineering and an executive leadership program from Stanford graduate school of business.

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