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AI Will Impact Life Sciences

5 Ways Big Data and AI Will Impact Life Sciences Firms in 2018

While industries such as financial services have had a long track record of managing data, and applying analytics to optimizing customer relationships and developing new services, life sciences companies have only in recent years begun to fully embrace and seize upon the opportunities to organize and apply their data in a systematic way to a range of drug development and patient care challenges.
As life science firms begin to actively mature their use of data, notable progress is being made in the efficiencies of drug development and the quality of insights produced at the research stage. However, given the accelerating rate of learning about human biology and disease processes, the opportunities to utilize data for even larger gains also continue to grow.

Here are 5 major ways we see Big Data and AI impacting the Life Sciences in 2018:

1. We can expect the environment in the US to be increasingly hostile to high drug prices. It will, therefore, be essential for life science firms to defend their research budgets and their profit margins by utilizing robust data that clearly demonstrate the value of their products.
The opportunity to effectively integrate data from the real world (e.g. medical insurance claims), genomic research and clinical trials will allow life sciences firms to unlock answers to a host of high-value questions such as the true effectiveness of treatments which can then be used to defend pricing positions in this increasingly tough market environment.
2. Improving the speed and quality of bi-directional learning between the patient and the drug discovery process has been a central strategy for life sciences firms in the last few years. However, their ability to do this effectively has been hampered by poor data access and data quality issues. As best practice in data strategy (including governance and architecture) continues to move through the industry we can expect the value unlocked by such translational medicine to accelerate.
3. As risks and inefficiencies continue to dog many life science supply chains globally, the employment of new technologies such as block chain offers the potential to radically improve levels of control and quality measurement whilst at the same time reducing overall costs for infrastructure.
4. As new branches of science deepen our knowledge of genomics and the broader implications of epigenomics, opportunities for utilizing AI to gain previously impenetrable insights are emerging over the horizon. Although still very much at the research stage, indications are that these techniques will increasingly impact fields such as oncology.
5. With all the different fields of study opening up beyond genomics and epigenomics (proteomics, metabolomics, transcriptomic, et al), it's important to remember the wise words of Prof John Quackenbush of the Dana-Farber Cancer Institute, "At the end of the day, the most important 'omics of them all is economics." Accessing and analyzing the right data to deliver sustainable business value remains the central purpose for life sciences firms.

We have known for a long time how a single drug can affect parts of the population in different ways. With hospital Electronic Medical Records (EMRs) providing an increasingly comprehensive view of each patient, the ways in which, privacy issues notwithstanding, researchers can gain insights from this data into how their therapies are performing at a more granular level will be increasingly crucial to the performance of life sciences firms as they fine tune the delivery and pricing of medication to where it is most effective for patient need and the corporate bottom line. Opportunities for profitable learning will accelerate further as EMRs and clinical trial technologies become increasingly integrated as we move beyond 2018.
Whatever the coming year holds, one thing is beyond doubt: Exciting new ways to create value and improve patient care await those firms willing to exploit the data tools and techniques that are now emerging.

WorldBI Author