Managing director for life sciences for data storage computing company Dell EMC, Jean-Paul France outlines his thoughts on the pharmaceutical industry’s access to data and the changes needed to improve research and development outcomes.
If I were to choose a buzzword that sums up 2016 it would be digital transformation. We have seen some incredibly inspiring and innovative projects taking place across job titles, business units and industries such as banking and retail. There is one industry however that is not as prominent in the digital transformation debate and that is pharmaceutical. It doesn’t appear to be from a lack of interest; in fact, almost every conversation that I have with pharmaceutical companies focuses on the role that technology and digital capabilities could play in helping the industry overcome some of its biggest challenges.
Digital transformation means different things to different people. To me, it’s the ability to use technology to communicate any asset or piece of information in a simplified manner. Pharma is an information industry and the people in it spend a huge amount of their time trying to access, manage and extract information from the huge amount of data that they have at their fingertips.
Unfortunately, information management is a huge challenge for the industry and a big part of that is down to no integration or data flow internally within different business units or externally between organisations. Although the technology to facilitate is easily accessible, data still exists within silos, providing insight only to the people that have access to it. That could be one organisation or even one business unit within an organisation such as R&D or marketing.
As an industry, pharma needs to get better at three things – trust, transparency and governance. With the skyrocketing cost of clinical trials and health data available for companies to acquire, anonymise and sell on for big money, the industry is in dire need of investing in and nurturing a culture that is based on collaboration. What is needed is a change in mindset.
There is still too much anxiety that sharing information amongst companies will result in a loss of profit. In fact, sharing information could significantly reduce overheads and costs. The use of pre-competitive information (and agreeing on what information each are prepared and happy to share) could also accelerate the journey to successful outcomes.
Access to data: the most valuable data to pharma companies is structured treatment information that can be accessed in real time; currently extremely hard to come by and only for extortionate prices. By putting in place a federated collaboration between pharma companies and hospitals, this barrier is significantly reduced or even removed altogether.
Clinical trials: the costs associated with the traditional large clinical trial model have become unwieldy and unrealistic. A huge proportion of the cost of clinical trials goes towards the manual task of sifting through data pools. Pre-competitive information exchange could significantly lower this cost. The good news is that the industry is going in the right direction with the recent introduction of the new clinical trials transparency initiative which provides much needed transparency around clinical data.
Improved outcomes: being able to use other people’s data will help to take the guesswork out of product development and allow pharma companies to better understand the value of their medicine compared to competitors. It will also give pharma companies a better shot at getting it right first time. By collaborating on research, companies could have access to an easily-searchable database of information relating to preclinical “probes”, current pipeline candidates and “deprioritised” clinical-stage drugs. It would also open up the genome process and molecular libraries, providing an overview of broader compound sets.
For example, many are looking to ‘re-engineer’ already profitable and licensed products to create new therapy types. They do this by re-developing the raw materials with a view to treating different conditions with the same basic drug, either delivered or composed in a different way. R&D teams are driving the use of big data and IoT to prove this approach. The key is to take an already profitable production line back through early stage trials with the raw composition almost ‘paying for itself’, with the R&D process taking a significant amount of cost out of the process. I’ve recently spoken to several R&D directors who are looking to achieve this. They believe internal collaboration of R&D data and processes is key to executing this successfully.
Changing a culture is no mean feat. However, we are already seeing some fantastic examples of best practice where collaboration between companies has delivered inspiring results. Companies need to start from the inside and work their way out; changing their internal culture by breaking down existing silos. The technology is there to make it happen, if they’re willing to embrace change.