Big Data Analytics in Pharma Industry

By May 27, 2021 Blog

In the current world, where COVID 19 has showcased the rate of transmission of a virus worldwide, there is a clear ask for innovative technology solutions to speed up the processing of drug discoveries. As pharma companies raced towards minimizing timelines for vaccine discovery, which usually takes 5-10 years, it has now been done within a couple of years. What changed exactly? The answer is Data Analytics.

Data has always been the pedestal for drug discoveries to identify the sequences and theories about the efficiency of the treatment. But as more and more factors are introduced in the picture and huge amounts of data are being generated, to an extent where it is humanly impossible to process it within smaller time frames, technology comes into play. The term is coined as ‘‘big data’’, which means large and complex data sets that are difficult to process using traditional database technology. But big data is not just about the size or amount of data, and it comprises 4 dimensions, Volume, Velocity, Veracity, and Variety.

The Four Dimensions of Big Data

Big data unlocks the true potential for data analytics, from accelerating drug discoveries to understanding patient trends and behavior. Big data unlocks the true potential for data analytics, from accelerating drug discoveries to understanding patient trends and behavior.

Here are 4 ways that pharma companies use Data Analytics to drive innovation.

1. Drug Discovery and Development

Applying predictive analytics to the search parameters should help them hone in on the relevant information and also get insight into which avenues are likely to yield the best results. Pharmaceutical Companies like AstraZeneca, Celgene, Bayer, Janssen Research and development, Sanofi, and Memorial Sloan Kettering Cancer Center, started a data-sharing initiative under the name Project Data Sphere to share previous research data on cancer to help experts in their research on treatments against the disease.

2. Targeting specific population segments

Scrutinizing data sets from various sources allows researchers to identify patterns that provide them with key feedback on how infections perform concerning specific population segments.

3. Customized patient care

Companies can leverage data from devices, which provides insights into the current patient behavior through analytics models. According to the formulated insights, the medical practitioner or companies can use this information to design services targeted to different demographics and curate treatments.

4. Streamlining Clinical Trials

Big data can assist the appropriate candidates for clinical trials by analyzing demographics and historical data, remote patient monitoring, due diligence of the previous trails track record, and even predicting outcomes of the trial. In addition, big data analytics can further narrow the patient funnel by considering more factors such as genetic information that help streamline clinical trials and drive down costs.

As the pharma companies are looking to drive maximum ROI before their patents expire, data analytics which substantially reduces timelines plays a key role in driving value. Not only does technology derive enhanced results, but it also provides a competitive advantage.