Drug discovery and development is a vigorous process that hops with the recent advances in pharmaceutical field, which requires understanding of pharmacokinetic, pharmacodynamics, pharmacogenomic profile of the drug. Development of new drugs is of prodigious importance for many clinical conditions but rising cost of drug development leads to decrease in number of drugs getting marketing approval. Additionally, drug development is a long, complex and expensive procedure. New technologies are disrupting all industries, including health care and drug development. Technological novelties increase efficiency and productivity using inventive outcomes, increased patient engagement, reduced patient burden, and improved trial management.

The ‘new data’ Age has given companies access to Big Data that is gradually emerging.  The Pharmaceutical industry is also pursuing ways to effectually consume this data-outburst to their advantage to overcome obstacles like – increasing R&D costs, long drug development time, patenting and decreasing R&D pipeline. 

The clinical research networks now have access to all data like biological data, data from clinical trials, data from electronic health records (EHRs) and hospital data. Accurate use of this huge data storehouse through data-driven analytics and acumens has the probability to modernize clinical research. Data analytics assistances pharmaceutical companies in drug development procedure. Data analytics has enabled companies to mend up clinical trials, manage risks efficiently, and increase patient safety. Data analytics in clinical trial augments efficiency of clinical trials, expands sales and marketing, and helps in early detection of diseases.

A study suggests that the failure of AstraZeneca's blood thinner Brilinta, for which clinical trials were conducted in 43 countries, to win approval from U.S. regulators -highlights the importance of Analytics in Clinical Trials. This drug was rejected pending additional data analysis to understand the differences in outcomes between North American patients and those in other parts of the world. Such delays of potential blockbuster drugs in major markets, of course, aren't good for revenue growth, and certainly not at a time when a company's existing best-selling drugs are facing the pain of generics competition.

Big data approach builds better tools for doctors, medical insurance companies and consumers. It will lead to improved recruitment rates, as patients will be selected from multiple data sources. Real-time monitoring of trials will improve safety procedures and make trials more efficient. In a study in Wales, researchers relied on electronically recorded data for five years after the original randomized controlled trial examining how probiotics used during pregnancy affect childhood asthma and eczema.

Pharmaceutical companies in India have also streamlined clinical research processes by joining hands with IT Industry. They have initiated holistic programs focused on process reengineering and IT validation, and make the IT landscape slenderer, smoother, accessible and future-ready. Implementation of enterprise data lakes, and investing in building capabilities in advanced analytics, and be focused to improve data quality and accuracy by implementing standard methodologies and next-generation technologies. Pharmaceutical industries have also collaborated with technology vendors, CROs, for better trial outcomes. They have also adopted a progressive and risk management strategies, and redefined and formalized data management policies, procedures and SOPs etc. Invested comprehensively and nurtured new skillsets such as big data, artificial intelligence, machine learning, cloud infrastructure management etc. They have also build fulproof data governance structures to ensure privacy, security and ethical handling of clinical data including genomics data, Health economics and outcomes research (HEOR) data.

The clinical research industry has accelerated digital transformation of systems and tools to better process large volumes of data captured from multiple sources. Innovation in technology and advanced predictive analytics across the clinical data will effectively reduce the time taken in the process of data capturing to reporting, fast-track the regulatory submissions and approval process, and ultimately lessen the time and cost of bringing new drugs and devices to the market.