“Big Data” is a term that refers to collections of data containing details that traditional database applications cannot process on time. Big Data features three distinct characteristics:
The primary use of Big Data in pharmaceutical and life sciences companies is to help them to make better-informed decisions for their business operations and make their operational environment less complex.
With Big Data, companies can quickly make collective decisions that help them serve their customers better and faster and boost their market share by analyzing large data volumes generated by various sources, including patients, doctors, and retailers. Tapping into the large data volumes that conventional Business Intelligence (BI) systems cannot exploit effectively, life sciences companies can quickly make sound business decisions.
Additionally, data analytics are used extensively by sales and marketing teams to optimize sales force planning and design and territory management. As a result, companies can effectively establish the best ways to balance their representatives’ workloads and improve sales.
Life Sciences and Pharma companies continue to deliver customized healthcare solutions by accessing the millions of broad, deep, and loosely interconnected data from patient years of information collected by genomics, imaging, EHR, and digital data to get meaningful insights.
Through analysis of large and diverse data sets, Pharma and Life Sciences organizations are trying to obtain a higher-resolution overview of each patient that they serve to offer highly personalized, effective treatments. There are three common big data use cases for these companies to achieve their goals:
The Life Sciences industry is highly fragile and dynamic. Accurate risk assessments help the industry curb the spread of epidemics and pandemics, prevent fatalities, and increase overall life expectancy. Advances in Big Data are now making it easier for players in the industry to notice dangerous trends quickly. As a result, Life Sciences and Pharma organizations can create quick and lasting solutions to a health crisis before a situation spirals out of control.
Thanks to Big Data, a company can:
One of the pillars of the drug discovery process for the Pharma industry is the clinical trial. Clinical trials establish whether a treatment or device is suitable for use in humans. Companies conduct tests to:
With global data pharma, Life Sciences, and pharmaceutical companies can make clinical trials and Electronic Medical Records (EMRs) more effective. Big Data offers possibilities like effective engagement, better results, and more efficient practices. Companies can use the information gleaned from Big Data to improve their predictive modeling of biological processes and drugs.
The current medical practice relies on a “standards of care” model based on mass responses and clinical trials.
However, with the benefit of Big Data, Life Sciences organizations can offer personalized care (also called precision medicine) to treat patients based on their unique characteristics, including height and weight, age, gender, among others. Through genetic testing, organizations can collect data on how diseases or conditions increase the risk of particular genetic profiles.
What’s more, the data helps biopharmaceutical companies to carry out innovative research to establish what effect genetic variation has on specific treatments.
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Our platform is 100 times faster at processing large volumes of life sciences data than a traditional Business Intelligence solution. With our purpose-built system tailored to the Life Sciences, we provide instant answers to your questions and allow you to quickly drill into billions of records with your desired level of granularity.
Best of all, our AI-powered solution is highly accessible, letting you ask questions via app, text, or talk, making it as simple as asking a colleague.
Contact us today for a free demo, and let us help you get the instant answers you need as you do a quarterly review or walk into a sales meeting.