Tell us about your role at Medidata.
I lead the Medidata team responsible for designing a platform of cloud-based solutions for clinical trials. All of our products are designed to modernize drug development, so the opportunity to work with people turning technology designs into real, impactful solutions transforming clinical trials has been incredible.
How long have you been in the life sciences industry?
I’ve been working in the life sciences industry since 1996. When I was at university I worked in a pharmacy, and then after completing my studies I joined the industry as a data manager. Over the course of seven years and in roles at two different big pharmaceutical companies, I experienced firsthand the burdensome work data managers struggle with because of outdated processes and systems.
Is it true that you were one of Medidata’s first 10 employees in the United Kingdom?
Yes, I was excited about what I thought could be done with Medidata’s technology and I wanted the opportunity to challenge the industry with new thinking and new ways of doing things. So in 2005, I went from being a Medidata customer to one of the company’s first 10 employees in the United Kingdom.
The technology areas that Medidata is developing are at the forefront of some of the industry’s most cutting edge solutions. What changes have you seen recently?
Recently, the most innovative changes I’ve seen are around the early steps the industry is taking to bring mHealth solutions into clinical trials.
Patients are far more likely to be compliant when participating in a clinical trial than in the “real world,” and mHealth provides unique opportunities to impact the behavior of patients. When brought into early clinical development, mHealth solutions allow life sciences companies to examine techniques to improve patient engagement and compliance prior to a drug’s commercialization. This provides the potential for early adjustments and interventions in the life cycle of a therapy, and ultimately enables patients to gain better therapeutic value.
Are there any essentials for life sciences companies to follow when dealing with so much access to data?
Having access to more data doesn’t necessarily make the data more useful. To be successful in the coming years, life sciences companies will need to implement comprehensive predictive analytics strategies. Leveraging the right data in real time will result in tremendous reductions to trial costs and timelines, as well as lower risk to patients. But to really benefit from these innovative cloud technologies, it’s essential that life sciences companies implement infrastructures that streamline processes and eliminate data silos. Viewing meaningful data across multiple studies and evaluating the data in a holistic fashion will provide life sciences organizations with the ability to explore different ideas and will open up a world of new possibilities for the industry.
What do executives at leading life sciences companies need to get right to capitalize on cloud technology?
It’s really all about embracing change. And, as we all know, change is difficult. Truly capitalizing on cloud technology means redesigning clinical trials, which takes a lot of time and tremendous effort.
For example, part of embracing meaningful change means committing to adopting and implementing cloud technology more efficiently to actually benefit from Software-as-a-service (SaaS) capabilities. While SaaS has matured quickly due to improvements in infrastructure and internet technologies, life sciences companies have typically been reluctant to embrace the delivery model for multiple reasons, including old thinking on testing and validation. However, that reluctance is dissipating among forward-thinking executives as they grapple with shrinking IT budgets, company-wide consolidation and heavy M&A activity.
Being able to quickly adapt to emerging and rapidly changing cloud technologies and adopt them wholeheartedly will be essential. Taking on these changes will enable leaders in the C-suite to lower development costs, mitigate risks, engage patients, reduce time to market, and, ultimately, increase the probability of trial success.
As pharma business models evolve, what do you see as the biggest barriers cloud technology can help the industry to overcome?
Pharmaceutical business models are being reshaped by the overall move to outcomes and value in healthcare. This shift is being led by payers and, in many ways, by patients as well. The emergence of big data and new patient-empowering technologies such as smartphone apps, wirelessly connected devices, sensors and social media are transforming the drug development landscape.
Pharma companies now find themselves wrestling with how to show the economic and real-world benefits of innovation. It’s a complex undertaking that requires different types of data. For example, regulators are looking for tightly controlled data to answer very specific safety and efficacy questions. However, even when a drug is approved, there is no guarantee that payers will cover its full cost. In considering a drug’s overall value, payers today are increasingly looking for data to prove that the drug is not only safe and effective, but also that it significantly improves quality of life and reduces the overall burden and cost of the disease. This poses a real challenge for pharmaceutical companies because they now need to run faster, leaner and more cost-effective trials, while collecting broader sets of data.
Today, with the maturation of technology solutions like cloud-based platforms, pharmaceutical companies are seeing real possibilities in a flexible, unified operating model that facilitates collaboration with research partners (such as CROs) to reduce the risks and costs of clinical development and accelerate its outcomes. We’re seeing life science companies introduce more efficient ways to share data among R&D teams, CRO partners and vendors. Organizations such as TransCelerate and Project Data Share are paving the way for companies to make their data assets even more valuable by looking at them across multiple studies. The technology behind these efforts aggregates clinical trial patient data across drug programs, and therefore allows life sciences companies to benefit from rapid and easy access to relevant, high-quality and analysis-ready data.