Innovation in clinical trials with open source

We were recently joined by Eric Nantz, Director at Eli Lilly and Company.

Eric shared his view on the biggest changes in Pharma over the past 12 years:

A lot of change that happened was an initiative many years ago where we tried to minimize the time from a treatment’s discovery in the lab to when we can actually get that treatment out to patients to benefit from.

To do that, we had to do a lot of things differently. There have been reorgs in terms of how trials are designed and more emphasis into other functionalities but within statistics, it actually empowered us quite a bit to push new cutting-edge algorithms for designing, for simulation, and to not just do the traditional analysis for a clinical outcome.

The fact that we got this mandate to shorten the time that we’re in the research phase, then we had to really put all hands on deck to put out new solutions.

That brought innovation out of necessity but it also opened the door for those in my group at the time to really think differently of how we’re leveraging R in the design space, and become one of the industry leaders in clinical simulation.

We definitely have relied on a lot of the functionalities that my colleagues have made. I’m not going to come here and say I know all the ins and outs of every statistical method. That’s why we have a team. Everybody can specialize in their key areas. But we’ve all been able to pitch in and be able to bring that innovation to more novel designs that can shorten that time that a patient has to be in a trial.

The industry itself still has a ways to go, but just that emphasis on getting these treatments out to patients sooner organically then brought some new innovations that we were doing in statistics and it really gave us a voice at the table that we could bring some really innovative change to how we were doing things in the past.

So certainly that’s been one of the higher-level changes I’ve seen.