Driving Successful Clinical Trial Supply Management through Global Data Collaboration

An effective clinical trial is one of the most crucial stages in the creation of a new drug. The testing phase not only ensures the safety and effectiveness of the new product before it goes to market, but also allows researchers to refine it during the course of the trial, leading to a more effective medicine and sometimes even clinical breakthroughs.

However, clinical trials are lengthy, complicated processes; the typical drug lifecycle can take on average ten years to go from discovery to the chemist’s shelves. With the patent protection clock ticking during this time, anything that can reduce clinical trial process and reduce the hundreds of millions of dollars investment required to bring a drug to market is going to be welcome.  Moreover, of every 5,000 projects, only one completes the drug development process and, of those that do, only one in five actually returns its R&D investment.

Pharmaceutical companies are caught in the conundrum of navigating an increasingly complex global environment driven by competing market and consumer pressures, as well as regulatory changes. As such, driving continual innovation is imperative for the pharmaceutical companies as they seek to reduce the length of trials and improve their outcomes.

In the past five years, the advent of new technologies, such as big data analytics and cloud computing, has had a hugely positive impact on pharmaceutical companies’ ability to drive innovation. In particular, through the use of advanced analytics, mathematical modelling, simulation tools, and machine-based discovery technologies, companies have been able to mine terabytes of data to uncover new opportunities and predict the most profitable research outcomes. In addition, the flexible, scalable cloud environment has enabled them to streamline their IT operations and deliver a more effective global model.

However, to truly seize the innovation opportunities on offer, pharma companies need to look to ways to drive widespread collaboration which extends beyond traditional teams. In addition, they need to be investing in data standardisation, integration, and interoperability. For instance, the entire clinical development process generates an enormous amount of data, which is not often used to its full capacity. Rather than being held by the clinical team in silo, it should be integrated with data from the discovery phase, so that the company as a whole can garner insights that could result in new drugs or help avoid costly failures.

The boom in new technologies could not have come at a better time for the pharmaceutical industry, but these alone will not guarantee innovation within the clinical trial process. Alongside the use of big data analytics and cloud computing, pharma companies also need to address their internal processes, ensuring that data is shared effectively between teams and embrace new partnerships to help reduce the clinical trial process.

Ashish Goel, Vice President & Regional Head – Life Sciences, Europe at Infosys