How Pharma Companies Can Ensure Success with Data Analytics

Pharma Tech Outlook: Pharma Tech Magazine

How Pharma Companies Can Ensure Success with Data Analytics

Stacey Smith, Pharma Tech Outlook | Wednesday, March 11, 2020

Advanced analytics presents a significant and real advantage for the pharma business to gather data and frame models for turning insights into impacts.

FREMONT, CA: Like every other sector, things are changing very fast in the pharmaceutical industry. Pharma companies are now under pressure to adopt groundbreaking technologies and enterprise-wide change to diversify the product portfolio to maintain the revenue stream. In today’s context, due to the increasing competition, the pharma market has started utilizing highly advanced data analytics tools to accelerate market shares and build powerful commercial value in the market. Below is a compilation of the multiple advantages of using data analytics in the pharma industry.

• Accelerate Drug Discovery 

The cost to put forth a new drug into the market is accelerating, and with the patents for drugs expiring, the pharma industry is looking to speed up this process of bringing a drug to market.  By searching through massive datasets and by running predictive algorithms through these immense data, pharmaceutical companies can make more intelligent decisions to boost the process of data discovery. Innovation in drug discovery is going to be a vital strategy in leading to improved financial performance.

• Improve the Efficiency of Clinical Trials

Big data can assist pharmaceutical businesses to mitigate the cost and speed up clinical trials by identifying and analyzing several data points like the participants’ demographic and historical data, remote patient monitoring data, and by evaluating past clinical trial data. By optimizing this whole process and identifying test sites with high patient availability, firms can accelerate disease diagnosis and design more efficient control and clinical trials.

Personalized Medications

Every individual has specific genomic makeup, and medicine should be personalized to everyone. However, it is daunting to use current biology and technology to handle complex data to make effective results.  Data analytics can solve this problem by combing through data of genomic sequencing, medical sensor data, and electronic health records.  By effectively utilizing data analytics technologies to sift through unstructured data, pharma firms can spot patterns to create a more effective and personalized medication for their patients.

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