Big Data in Pharmaceutical: Top Trends Transforming Medicine

In this article, we point out the top trends related to Big Data in pharmaceutical that are disrupting the industry

After transforming the face of Marketing, Sales, and Service, Big Data is extending its reach and impact into other industries. While industries such as Automation, Oil and Gas, Metallurgy, Military, Education, and Hospitality have been faster than the rest in adopting and promoting Big Data applications, there are few that lag in the race. Until 2017, the pharmaceutical industry did not figure in any major Big Data-related innovation and adoption. However, things are changing for the industry as analysts and leading research institutes see a compelling opportunity in deploying Big Data to arrest the declining success rate of R&D in pharma. In 2019, we find Big Data and Data Analytics becoming the core of pharma and driving global innovations in healthcare, pharma, and radio-medicine.

In this article, we point out the top trends in pharma-related Big Data movement that is disrupting the industry.

Data Management to Optimize Neonatal Remedies

Even before the baby is born, Big Data would have made its impact on the new life. That’s the kind of technology we are talking about in 2019 and beyond. Neonatal pharma procedures would scale a new height with further adoption of Big Data and analytics for early detection of clinical deterioration and congenital disorders based on historical and real-time data gathered during the gestation phase. There are numerous novel projects that are utilizing and promoting Big Data applications and making NICUs more reliable and friendlier.

Patients and doctors could both know the various NICU complications and NICU medicines available in the inventory, in advance. Based on the patient’s history and genetics, pharma companies can personalize medicines to deal with all the future outcomes possible using recommendation analytics and predictive modeling, similar to current Big Data applications used in BI and non-medical fields.

Parents and newborn babies (including premature ones) would have a better chance to deal with any untoward incident that may arise down the line.

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Drones, Robots and Healthcare Apps for Remote Monitoring

According to a Dell EMC report, drones and healthcare apps would throw up 2,314 exabytes of healthcare data in 2020.

By 2020, Big Data in the pharmaceutical industry would drive major onboarding of drones, remote patient monitoring and diagnostics, healthcare-specific mobile apps and disaster management. You could expect a drone carrying a defibrillator or life-saving drug to a patient in a remote location before any ambulance, aero-ambulance or doctor could reach.

Machine Learning-based Next Generation Sequencing 

Next Generation Sequencing (NGS) technology is the fastest-moving trend in the healthcare industry, already demonstrating visible benefits in pharmaceutical and diagnostic sectors. Big Data Analytics and Cloud Computing sit at the center of pharmaceutical and biotech innovations, bringing together various medical technologies together, such as Pharmacogenomics; Precision medicine, Polypharmacology, Toxgnostic, and Pharmacoepidemiology.

NGS with Big Data holds the key in future drug designing and development.

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Drug Discovery

Big Data and pharma industries are connected by a common thread — they are involved in research and innovations for curing diseases in their respective ways. Big Data in Drug Discovery would drive the concept of personalized medicine for patients. It will be at the core of pharmaceutical innovations based on medical imaging, molecular sequencing, laboratory screening, gene therapy, mutational practices, and chemotherapy.

To complement medicine information, a host of historical information needs to be collected and analyzed. Drug Discovery with Big Data analytics would accelerate clinical trials, allowing repurposing of orphan drugs/ failed medicine for better use in the future.

The correct medicine for the treatment of rare diseases would be a thing of the past very soon.

Big Data for Post-Authorization Safety

According to the HMA-EMA (European Medicines Agency) Joint Big Data Taskforce – summary report, data will increasingly be used by regulators to assess the benefit-risk of medicines across their whole lifecycle.

Big Data can standardize the entire drug administration and post-authorization safety procedure by addressing all the highlighted challenges affecting the reputations of pharma companies. Big Data analytics would be an enabler in driving better collaboration across all stakeholders in the pharma industry, including research companies, HTA institutions, patients, academia and doctors.

The latest trend in drug safety standardization revolves around the evaluation of analytical tools such as Machine Learning and Predictive Forecasting that promote the expansion of pharmaco-vigilance efforts and enhance novel/ethical use of medicine.

With the drug industry maturing at an exponential rate, Big Data analytic vendors have already started developing and delivering customized end-to-end solutions to meet the present and future customer requirements. In the coming years, it would be data, not doctors, recommending medicines for you. Would you trust the data?

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