The right way to use data
We speak to Camille Diges, global director of life sciences at Unisys, who says that pharma needs to walk the walk with data and embrace its benefits if it truly wants a new golden age of research.
What does your current role involve?
At Unisys, I am the subject matter expert for all things science and pharmaceutical related, focusing on how technology innovations can be used to overcome current industry challenges. For instance, I’ve been exploring how cybersecurity can be implemented in the life science industry to make data sharing safe and secure. For scientists working in the pharmaceutical industry, who have to collaborate across different industries internally and with academia, this kind of technology advancement would be transformative for their work.
What lessons did you take from your time as a researcher into your current work?
From my time as a scientist, I wanted to handle as much data as I could, and to understand everything it could and couldn’t tell me in a bid to challenge hypotheses and create new ones. Today, I still apply these problem-solving skills of experiment design and thinking every day at work.
I also recognise that researchers can be one or even two steps removed from any given experiment, which means critical information on how that data was collected can be easily be lost, skewing the analysis of large combined data sets.
Having prior experience allows me to understand that just having data is not enough. Instead, scientists need to know their data at the most fundamental level before we can start moving forward, which is what my work now strives to achieve.
What are the main challenges in data sharing and data access at the moment?
The biggest challenge that has faced science between the 20th and 21st century is collaboration. We used to be able to link proteins back to certain diseases, which is why we know so much more than we did before about genomics, genetics, cell signalling, and microbiomes, allowing pharmaceutical companies to release their next blockbuster drug. Now that the industry focuses on much more complex diseases such as MS, dementia and schizophrenia, a greater degree of collaboration is required.
Why is it important for the industry to solve these challenges? What risks might emerge from leaving them be?
It’s paramount that the collaboration and sharing of data is facilitated so that scientists can understand how this data was generated, what was the criteria and what were the goals. That way, conversations can be had that challenge conclusions and scientists can work together to create a better hypothesis.
However, pharmaceutical companies are understandably driven by creating revenue, driving profit and protecting themselves legally. As such, there is concern over which pharma company will reap the rewards facilitated by numerous researchers. Therefore, these two entities are incompatible at present but until operating in a closed environment is eradicated, pharmaceutical companies will continue to see their revenue decline. Researchers on the other hand are naturally collaborative due to their academic upbringing – they are not thinking about IT issues or licensing issues down the road, they’re geared towards solving problems and saving lives.
How could collaboration and access to data aid with research?
In today’s science, as diseases increase in complexity, large data-driven results are incorporating new intricate methods, and as such, they cannot be reproduced by other scientists. That is why close collaboration and communication becomes of great importance to understand where the data comes from, and any potential pitfalls of that data. That way, researchers can challenge each other and create better hypotheses, leading to faster drug development and cheaper drugs for patients when they eventually go to market.
How would this benefit patients?
Ultimately, the cost of drug development would decrease. There is so much pressure to move from discovery to clinical trials that pharmaceutical companies often put pressure on researchers to cut the discovery phase short. This can mean data is not thoroughly looked at and a lot of money is lost when the drug fails at clinical trial. It’s better for the patient if we can make discovery research more thorough and quicker paced so scientists can be more confident in their work and develop better medicine for a cheaper price.
What kinds of cultural changes do companies need to implement to aid with greater data sharing/collection/access? Is it difficult to get researchers on board with these new techniques?
Researchers do not tend to think about legal processes or licensing issues, they are dedicated to helping people, solving problems and sharing knowledge. The cultural changes need to come from the business side, who have the agency to facilitate researchers in sharing data and talking openly about it with academics. Even internally it can be a challenge to see each other’s data and question each other’s work and hypotheses. There has to be a way to secure these conversations and make it very simple in the day to day workflow, like creating a community dedicated to the study of an aspect of MS for example. To get the business on board, the only way is to put forward a model based on a cost-benefit analysis.
By working in a collaborative environment, pharmaceutical companies can generate more revenue. However, until that bigger conversation is had, we’re going to continue to see high drug costs, delay in the release of the next drug, and overall a detrimental effect to all of society and science as a whole.
Are there any particular technologies/tools the industry can harness to facilitate this?
There are IT tools available that enable researchers to create secure groups of fellow researchers who are all working on the same project, to share their data in a secure environment while also being seen and used by business and legal. This allows the pharmaceutical companies themselves to sort out the licences and IP issues while the scientists can do their own work.
Secondly, while I do not think that blockchain solves everything, blockchain is always part of a solution. You are able to put all the results of an experiment in the blockchain and know who did what, when, where, how and why. You know what tools were used and how they travelled through the research and discovery process. This can provide a clear record for business and legal teams to go back through to predict what legal challenges may later arise based on what the researchers are doing. Of course, it also provides clarity for the researchers themselves who want to understand the chronological order for every experiment.
What role would you like to see data playing in the future of the industry?
There is a plethora of important experiments that have been conducted and the failures have not been documented, but it’s often this information that is most important so that scientists can stop repeating experiments.
I would like to see data, both positive and negative, shared and analysed collaboratively. Only that way can you move medicine forward, and improve treatment to patients.
About the interviewee
Camille Diges, PhD, is the global director of life sciences and healthcare at Unisys. She brings over 15 years of experience and deep knowledge of software and product development for biotechnology and alliance management for the life sciences industry.