5 ways how pharma companies are using data analytics

CIOL Bureau
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ways how pharma companies are using data analytics

The global pharmaceutical companies market has been growing at a rate of 5.8% since 2017 and by 2021, it should reach a size of $1,170 billion. Much of this growth has relied on empirical data, which has presented significant challenges over the last decade.


The utilization of data analytics to comb through available big data can offer valuable insight to pharma companies regarding the necessities, use, contraindications, market trends, and sales performance.

Here are five ways in which leading pharma companies are already using data analytics –

i. Using patient data for personal chronic disease management


Although India does not have a unified electronic health record (EHR) infrastructure, the increasing use of wearable technology that monitors vital stats and people’s preference for syncing data from their devices to the cloud can facilitate the development of programmes for tailored chronic disease management.

Chronic diseases can range from diabetes to heart problems, which are becoming more common in India by the day. Pharma companies can use data from patient healthcare records to offer tailored management solutions and healthcare tips to registered patients regularly.

However, the lack of a dedicated HER system currently makes it extremely challenging for healthcare professionals as well as pharmaceutical companies to gain access to patient history, case studies and healthcare references.


ii. Using big data to design targeted medications for patients, doctors, researchers and reviewers

Today, several Indian start-ups use AI and ML-based technology to assess huge volumes of data on healthcare, clinical trials and drug reviews from multiple sources.

For example, companies have dedicated cloud databases that collates data from major patent offices, regulatory bodies, clinical trials, and several other authentic sources. Pharma companies can access verified data on diagnosis, medication, treatment, and prognosis for making informed decisions within shorter periods.


iii. Utilizing unstructured data to accelerate drug discovery and development

The cost of bringing a new drug to the market can reach $5 billion as per a 2013 analysis by Forbes. Fast-tracking drug discovery and development can minimize cost. Combing through unstructured data of patents, clinical trials, and scientific publications efficiently is only possible by applying predictive analysis to the search parameters.

According to Phani Mitra, the VP of Dr. Reddy’s Lab, “the western markets are consolidating customer information at a tremendous speed. It has accelerated their rate of drug discovery, development, and approval from an average of 18 months to less than 6 months.” Indian pharmaceutical companies can utilize available information to accelerate the drug discovery and development process in the country. Pharma companies are leveraging data curated by AI and ML-based technologies to imbibe “quality in the process” of drug design.


iv. Using big data to predict health risk and manage safety concerns

Signals coming via social media, personal wearable devices, and Google searches can warn pharmaceutical companies about the health risks and product safety of new drugs. Currently, pharma companies are still thinking about how to use this unstructured data for effective means.

According to Dr. Ed Tucker, VP of Janssen Research and Development, “We intend to utilize posts based on various hits and analyse the data on the web. One can go through the chats and follow the public sentiments to capture the data of interest from the patient. It will also include safety-related info”.


This practice can identify risk factors and ameliorate side effects long before they become a reality. The only way to comb through millions of searches, and the petabytes of data coming from personal wearables is by leveraging data analytics to recognize specific words, and patterns in them.

v. Tracking drug performance and market response to fuel marketing and sales efficacy

Capturing the genomic data and recognizing patterns in the health-related data from electronic health records can enable pharma companies to identify new markets for their new drugs.


Analytics of available market data and patient data can aid better resource distribution decisions and effective capital reallocation. Pharmaceutical companies are experiencing enhanced sales and more efficient marketing through the use of patient analysis data and patient trends, and the adoption of data science and big data analytics frameworks.

Gaurav Gupta Co-founder, Navia Life Care Gaurav Gupta Co-founder, Navia Life Care

Currently, Pfizer works with SAS and Noux to capture actionable insights on sales and distribution data which were earlier present on thousands of excel spreadsheets. It now helps Pfizer track how often doctors prescribe certain medication, how frequently medicines are selling in one area, which individual sales reps are performing better than the others and track their competition.

Data analytics can boost the overall performance of pharmaceutical companies without increasing their costs of operations. In fact, pharma companies are now utilizing data analytics to capture patient information, scan health records and keep track on the performance of drugs in the clinical trial phases or initial market introduction phase to optimize their cost of development and production.