Lilly Reduces White Space For Quicker Regulatory Approvals
By Ed Miseta, Chief Editor, Clinical Leader
The time that elapses between phases of a clinical trial can be problematic for pharma companies. Known throughout the industry as “white space”, these delays can extend the trial process, drive up the cost of studies, and delay needed medicines from reaching patients. It is also an area in which Eli Lilly and Company is focused in an attempt to cut trial timelines.
Anne White, VP of next generation development & portfolio management at Lilly, notes this is an area of interest for her personally. White has spent many years working with oncology patients and knows that getting a medicine to patients just three or four months sooner can make a big difference in their lives. In some cases, it can save lives.
“A lot of time can be spent waiting for the next phase of a trial to begin,” says White. “For example, there is the time between when you have the results for the Phase 2 trial and when you are able to start the Phase 3 trial. Another example is the delay between when a company has the results of the Phase 3 trial and the submission of that data to a regulator for approval. If we want to find new ways of cutting down on the time and cost it takes to put a drug through clinical trials, we have to look at reducing that white space.”
White space does not necessarily refer to time that is wasted or unproductive. In fact, White notes there are valuable actions that take place between trials. Companies use this time to interact with regulators to get feedback, which helps with future studies. Companies also use this time to review data internally to make decisions on future actions. Still, reducing this time benefits both the company and its patients.
Analytics Play A Key Role
Lilly has embarked on a mission to reduce the time it took for the company to move from first patient dosed to product launch. Key to that campaign were making patients aware of trials, making it easier for them to access trials, and engaging with advocacy groups. At the same time, the company took aim at white space.
One source of time savings was better use of analytics. Lilly has a chief analytics officer and an analytics team that is now modeling the potential outcomes of a study. A proprietary technology designed by Lilly allows its analytics team to look at all potential outcomes of a particular study. The team will then focus on the outcomes that are most likely to occur. For each of those scenarios, the company will decide what the next course of action should be.
“We are proactively making decisions that we know will have to be made at some point in the future,” says White. “Later on, when we have the actual results of the trial, we have already thought through what the required next steps will be. We do not have to spend a lot of time thinking through what our options are and making a decision on them. By making those decisions proactively, we can more quickly move a medicine into the next phase of development.”
When Lilly first began discussing this concept, White admits she was skeptical how much impact this forward planning would have. She has spent more than 20 years in the clinical space, and was unsure how much value there would be in this type of assessment before the data from the previous study was in hand. In hindsight, she is impressed by what the analytics team has accomplished. The technology is able to do things that many would have thought impossible just a few years ago. Today White can sit in a room and watch the analytics team make it possible for the team to make these decisions live. She notes it is an amazing exercise to watch.
For example, one focus of the analytics team is dosage strength. By looking at the different scenarios for various dosage strengths, researchers can determine the likelihood of success for each dosage and use that information to start planning for the next phase of the trial.
“Possible outcomes of the trial are modelled in front of me in real-time,” she says. “In the past, it would take several months just to do the programming required for these models. Researchers can also begin to see what the next phase of a trial would look like, before they even have data from the previous phase. It’s amazing what this technology has done for the speed of decision making at Lilly. As a result, I am no longer a skeptic. I am now a believer and can see the value in what we are doing.”
Investments In Infrastructure
Reducing the down time between trials also means getting good data from patients and getting it in a timely manner. Lilly is making investments in infrastructure to make that happen. The company is putting solutions such as eSource in place to facilitate gathering data from patients. The company is also putting a focus on gathering data directly from labs and connected devices.
“We live in an era where patients can enter data in their phones,” says White. “Regardless of how the data is coming in, our focus is on getting that data quickly and directly. Doing it any other way slows the process and creates delays. We now have real examples of situations where we were able to lock down our data just days after the last patient was in a clinic. That is simply not possible if someone has to manually re-enter a lot of that data. This may not sound as exciting as some other things we do, but it is incredibly important when you're trying to reduce the wasted days between trials. We have to lock the data before we can analyze it and decide what the next step would be.”
While many companies average eight or ten months from last patient visit to data submission, Lilly has reduced that timeframe to just under four months. When you know that your drug is successful, those days leading up to submission are very valuable. They determine how quickly you can begin to market the therapy if the drug is approved and how quickly patients can begin to benefit from it. White notes patients and caregivers get very excited about the medicine and will often call to check on the status of the drug. She is proud of the speed Lily’s development team has attained.
In most cases, decreasing white space has reduced development times for Lilly by four to five months. In some cases, the time savings amounted to more than 8 months. Combined with advancements made in reducing trial start-up, Lilly has reduced total development time from over 10 years to 8 years.
“We are incredibly proud of those timeframes, considering that we are involved in some intense, high-need disease states,” says White. “We continue to work to take even more months and years off those timelines. We believe it is our responsibility to do so. When a patient is ill and in need of a treatment, it’s very difficult to tell them they have to wait a few more months.”