Big data and pharma

Mailen Agüero – Business Development Analyst
Francisco Stefano – Director

The use of new tools to explore Big Data sets has accelerated their use in the field of health.

Big Data is a collection of data, structured or not, that can be explored (mined) to be used by processes such as machine learning, predictive modeling, or other types of advanced analytical applications.

The use of new and powerful tools to explore Big Data sets has accelerated their use in health care and the pharmaceutical industry.

The benefits that the application of Big Data can have on the pharmaceutical industry are varied:

  • Reduces the cost of research and development
  • Best clinical trials
  • Drug discovery
  • Drug reaction monitoring
  • Precision Medicine

Big Data can help speed up the research process, with the help of artificial intelligence, to minimize the time needed for clinical trials. This will reduce the amount of research needed and, therefore, reduce the cost of medication in the long run.

There can be many applications of Big Data analytics in conducting clinical trials. It can help design flowcharts to join and recruit more patients into clinical trials, which, in turn, will increase the success rate of the drug. A different predictive model can help analyze new product competitors based on various clinical and business scenarios. Big Data models can also prevent the company from adverse situations, which can be caused by operational inefficiencies or other unsafe measures.

With the help of Big Data analytics, researchers use predictive models to analyze drug toxicity, interactions, and inhibition. These models use historical data collected from various sources, such as clinical studies, drug trials, etc., to obtain more accurate predictions.

Real-world scenarios are replicated to test the harmful effects of drugs in their clinical trials, aided by predictive models. Data mining on social media platforms and medical forums is done alongside sentiment analysis to gain insights into adverse drug reactions (ADRs).

The DATA SPHERE project is an example worth considering. A set of Institutions, Medical Centers and Pharmaceutical Companies have agreed to freely share the data obtained by the participants, in the research carried out in the field of oncology. In the conviction that breaking down the barriers of individual interests by establishing a common platform for historical data shows a global resource that will facilitate the work of the group.


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