Vishal Pratap Singh | Thursday, 20 January 2022
In today’s dynamic and quickly changing time, majority of pharmaceutical companies are scrambling to emerge on top and boost their performance without adding to their total cost of operations.
There is a rise of innovative technologies such as artificial intelligence, Robotic Process Automation (RPA) and Data Analytics in the Pharmaceutical Industry.
It requires pharmaceutical companies to innovate rapidly in order to gain a competitive edge and to harness the opportunities in the market landscape. The global Pharmaceutical Industry is projected to have a market worth $1170 billion by 2022, growing yearly at 5.8 per cent from 2017. “Data Analytics can offer several benefits to the pharmaceutical firms such as the ability to perform in-depth competitor analysis and monitoring”, says Venkat Viswanathan, CEO, LatentView Analytics.
Also, it helps to improve the in-house processes with data backed insights. With new viruses surfacing every year, Data Analytics plays a crucial role in drug and vaccine development. The data collected from COVID-19 hit countries like the recovery rates, intensive care requirement, number of deaths and the total number of case generate valuable insight into spread, recovery, affected demographic and aided in administration.
Increases the Efficacy
Data Analytics in Pharmaceutical Industry can help pharmaceutical businesses to reduce the cost and speed up the clinical trials by identifying and analysing various data points. These data points include participants’ demographic and historical data, remote patient monitoring data and by examining past clinical trial events data. Industry experts believe that by optimizing this whole process and identifying test sites with high patient availability, pharmaceutical companies can use this data analysis to speed up disease diagnosis and design more efficient control groups and clinical trials.
Helps in Personalized Medication
Every individual living on this planet has a unique genomic makeup and ideally medicine should be personalized to everyone. However, it is challenging to use current biology and technology to handle complex data to make effective decisions.
Data Analytics in Pharmaceutical Industry has the potential to solve this problem by combing through data of genomic sequencing, patient’s medical sensor data which is a device that can be worn to track physical changes in an individual during treatment and electronic medical records.
By effectively utilizing data analytics technologies to sift through unstructured genomic data, pharmaceutical companies can spot patterns to help create a more effective and personalized medication for their parents.
Helps to Increase Revenue
With increasing pressure on the pharmacy operating margins, it becomes essential to increase the efficiency of the whole process. Granular analysis of key metrics such as average ingredient cost per prescription, rebate as a percentage of total drug spending, drug utilization review savings per member per year, will help pharmaceutical businesses make smarter decisions to increase revenue and reduce costs by using pharmaceutical analysis.
Useful in Clinical Trials
It has been observed that the healthcare industry doesn’t work on the concept of one size fits all. During the clinical trials of medicine, data collected can be processed to generate insight on its outcome on individuals as per medical history, gender, age and others.
The medical practitioners need to look at the existing ailments and history of the patient before recommending any drug. Having a system in place to track actual and existent ailments and earlier prescribed drugs can generate a method to differentiate on individual treatment.
By using Data Analytics, the pharmaceutical companies can advise the physicians on how a particular medicine would fit within an individual’s treatment plan.
Utilizes Unstructured Data
According to a survey done by Forbes in 2013, the total cost of bringing a new drug to the market can reach $5 billion. Fast tracking drug discovery and development can minimize this cost. Combing through unstructured data of patents, clinical trials and scientific publications efficiently is only possible by applying predictive data analysis to the search parameters. Many pharmaceutical companies are still thinking about how to use this unstructured data for effective means.
Predicts Health Risk in Advance
Signals coming from social media platforms, google searches, personal wearable devices can warn pharmaceutical companies about the health risks and product safety of new drugs. There are many experts who 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. This practice can identify risk factors and ameliorate side effects long before they become a reality.
Future of Data Analytics in Pharmaceutical Industry
Data Analytics can boost the overall performance of pharmaceutical companies without increasing their cost of operations. In fact, pharmaceutical companies are now planning to utilize data analytics to capture patient information, scan health records and keep a track on the performance of drugs in the clinical trial phases or initial market introduction phase to optimize their cost of development and production.
Pharmaceutical companies are expecting enhanced sales and more efficient marketing through the use of patient analysis data and patient trends, the adoption of data science and data analytics frameworks in the near future.
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