What distinguishes Health Decisions’ technology system?
The other systems that are available today don’t focus on a study management basis. CTMS and CDMS integrate some pieces of data but not all. You have to open different systems, different documents and it’s up to you to make those things work. Our system allows different users to see what they want to see. We developed our architecture around a very flexible system so that we can have any form of data input. But, our focus is on taking a lot of raw data and converting it to information and then into knowledge and then to making sure that knowledge is available very quickly. That’s the basis for decision-making. I think we-based EDC is a dead-end technology. One reason is inherent in the system, and one is not. What’s inherent is that somebody has to sit in front of the keyboard and enter data. Until that happens, youknow nothing. The second reason is that those systems do not have study management capabilities, the ability to monitor performance metrics, such as enrollment, or to make continuous adjustments.
Despite all the discussion about adaptive clinical trial design that’s going on right now, you’re always hindered to some degree by not having all the data that has been generated at the site available to make decisions. For example, enrollment is a huge issue in this industry and if you ask, “How’s your enrollment strategy going, how is each site doing?” the answer is, “I don’t know, but I can tell you when the study is done.” In contrast, our systems allow us to track study enrollment in real time. I can open up my computer, and if a patient were randomized or screened 30 seconds ago, it will show up. For a manager it means you can look at the sites that are working well and the sites that aren’t working well and figure out what the differences are between those. With that information, you can decide how to manage the situation. My big issue with commercial systems right now is that you can’t do that.
The other thing about commercial EDC systems is that they depend a lot on the hands in which they’re used. I have seen some companies, and they tend to put $10 to $15 million around the support of systems. So they’re big and expensive, and the expense that’s involved here reflects the complexity of the systems. From a technology standpoint, the best systems are the simplest.
Tell me about SmartPen
The SmartPen takes one-third the effort of a web-based EDC system. Sites that generally hate doing data entry don’t have to do that. But the best part is that two minutes after the patient walks out the door, I have that data available to me. Wew’ve found typical delays with commercial EDC systems between a couple of days and a couple of weeks. When you’re trying to manage a study during that couple of weeks, you don’t have the benefit of knowing what’s going on with the data or anything else at the site. With the SmartPen system, the query rate is far lower and thus the site burden is lower than commercial web-based systems. As an example, we hve a study going on right now with 4,000 patients and 107 sites, and our query rate on that is less than half a percent.
From a patient perspective, the nice thing about the SmartPen is that you give the patient a questionnaire and a pen and they take it home, fill out the diary, bring it back, and we have the information immediately. The other thing is that you can tell exactly when each keystroke was made. We conduct many of our studies in elderly populations. Older folks have a hard time with the stylus and with seeing the screen of a PDA. What we’ve got is very simple. You take a pen and a piece of paper home. That simplicity makes things a lot easier for the patients and for us in terms of being able to handle the data and for the sponsor in terms of being able to see that. You have to listen to users and you have to regard the process as one of continual refinement. There are a lot of levels of looking at that, down around the user level to things such as return on investment.
What cost savings can your technology system offer?
For a study we were involved with for Roche, we were able to cut 1.6 years off a five-year timeline and save them $32 million in direct costs from a $100 million budget. Another example is we worked on a drug that’s on the market now for metastatic breast cancer. We use a very simple adaptive strategy to re-estimate sample size. We got that drug to market nine months earlier than it otherwise would have gotten there. That simple piece put an extra $366 million in the client’s pocket.
The benefit of our technology is that we can implement it in a way that allows us to know what’s going on anywhere in the world within seconds. One of the other economic consequences of that is that we can do by computer what most people have to do by sending monitors out to the site to do. We can monitor more effectively at a frequency of about half what the industry is used to. A lot of our monitoring goes out at every 12 weeks or longer. The usual industry interval is about four to six weeks, so it saves a lot in travel expenses and work.
What challenges do you face?
There’s such a disconnect between this strategic need to improve efficiency and what people do on a day-to-day level. Our biggest issue has been the need to access the strategic level of companies. Our technology and processes work on two different levels—one is a strategic, adaptive level and the other is a day-to-day study management level. It allows us to look at what’s going on every single day. It’s the immediacy of performance metrics as well as data that enables the kind of decision making that underlies adaptive on the strategic as well as the day-to-day level. Without the real-time knowledge, you’re always impaired to some degree, crippled in some cases. A lot of the inefficiency in the industry right now reflects a lack of structure and decision making capability that is part of the continuous improvement model. Technology forces companies to add structure and processes.
What industry changes have you observed?
With adaptive trial design, the era of planning a study—crossing our fingers and waiting to see the data until the end—is over. Adaptive design gives you much more information and much more choice. The thing that’s made this possible is the FDA’s [U.S. Food and Drug Administration’s] and the EMEA’s [European Medicines Agency’s] recognition of the benefits. They actually encourage companies to do this. We’ve run over 100 of these adaptive studies. I think the industry has been offered an incredibly useful tool, but some companies are afraid to touch it. It is a tremendously useful tool, if it’s used well, and the industry needs to start using it and learn how to use it well. Adaptive clinical trials are a very important opportunity for those pharma companies that can realize these lessons and put them to good use. Those companies that do stand to have a huge advantage over companies that are less agile. Big companies are traditionally slowest to change, but unless they do, you’re going to see a changing of the guard. If I ran a big pharma company, I would take a pathfinder group and tell them, ‘Your job is to think about how we’re going to be operating 10 years from now.’ There is no question these systems and an adaptive approach to both the strategic as well as tactical aspects of study and program conduction are the future for this industry.