The life science sector is applying big data to increase its efficiency and reduce risk during operations.
FREMONT, CA: Industries such as banking, finance, automotive, and manufacturing have already implemented technology to their business operation in the last couple of decades. However, the life science industry has been slow in implementing technology and big data in that respect. However, with the increased efficiency, cost-effectiveness, diversity in application, and importance of big data technology, it is becoming unlikely for the life science and pharmaceutical companies to ignore the big data wave.
The life science and pharmaceutical industry is a fragile industry with higher regulations and higher costs associated along with it. With big data, the companies are using trend analysis and data analysis to access the risk related to business operations to safeguard business continuity and increase profit margins of life science and pharmaceutical companies. These analyses are also used for budgeting and sales forecasts. This assists the sales and marketing team in enhancing product promotion and marketing for the life science companies.
Effectiveness of clinical trials
Life science and pharmaceutical companies invest significant resources in the development of new products and drugs. The potential new products or medicines need to clear clinical trials before they can be commercially launched successfully. Big data technology is extensively being in clinical trials to increase the research scope and reduce the turnaround time as clinical trials tenures at present ranges from two to seven years. Contract research organizations use big data to collect, store, and analyze patient data for clinical trial operations.
Personalization of medicine
A different formulation of drugs has a different impact on people with a wide range of genetic composition. Hence, life science and pharmaceutical companies are using genetics to develop personalized drugs to target patients. Genetics is the study of each individual's genetic composition, which stores an enormous pool of information. This analysis is highly ineffective and less cost-efficient without the use of big data for commercial success. Big data software is used to analyze the genetic composition and understand the impact of drug formulation in the target patient's body.