Integrating Infrastructure for Clinical Trials

[ eClinical Technologies ] Medidata on the cloud, ‘omics, and personalized medicine. 

By Kevin Davies 

January 10, 2012 | Glen de Vries thought he would be teaching biology or chemistry in college, but somewhere en route to a satisfying career in academic research, he got distracted. He became exposed to clinical research while working on a molecular biology project at the Columbia Presbyterian Medical Center. Together with a friend and medical resident in the same lab, he ended up quitting to pursue Medidata Solutions Worldwide full-time. De Vries is currently president of Medidata Solutions, a provider of clinical technology solutions that believes in “optimizing clinical trials from concept to conclusion.” He was the original architect of the Medidata Rave electronic data capture (EDC) and clinical data management system (CDMS).  

Bio•IT World chief editor Kevin Davies spoke to de Vries about the progress of Medidata and the state of e-clinical technology in general. 

Bio•IT World: Glen, what was the original goal of Medidata?  

de Vries: Medidata was founded because we’d been talking over ideas about taking data management during a clinical trial to the Web. We found someone who thought it would be a great idea for a clinical trial he was running. We wound up taking the bed out of my one-bedroom apartment and converting it into a studio apartment with an office, and that’s how the company was born! The sponsor of the trial, when they heard that our systems were being run out of a closet, said that makes no sense. We’ve got to be serious about creating an infrastructure that people would trust. That was in 1997.  

By 1999, we had all our ducks in a row and really opened the doors on Medidata. At that point, we met Tarek Sherif, the other co-founder [and chairman/CEO]. Culturally, it’s still useful to think [the way we thought back then]—a combination of thinking about basic science, practical aspects of providing health care, being a clinical trial site and a sponsor, and a healthy dose of business realities. We’re not just a technology vendor but one working in the world of services that get outsourced. 

Would you call yourselves a CRO (contract research organization)? 

We are not a CRO. In its most extracted pure form, we’re trying to provide a platform—the technology infrastructure—that pharma, biotech, and medical devices will need in the future. I’d stress that we’re trying to build for the future state. 

Over the last 15 years, most people have approached clinical trial technology infrastructure by taking individual paper processes and automating them. Sometimes you can make it more efficient, but nobody has really tried to take an approach similar to the ERP (Enterprise Resource Planning) industry. If you look outside life sciences, companies would have different departments to manage individual processes (manufacturing, sales, customer support etc.), then companies like SAP developed platforms that fall under ERP—bringing all the functions in a company together in one central software base (e.g. ordering a custom computer over the Internet). There hasn’t been an ERP-like platform in clinical development.   

We see that as an opportunity—instead of replacing individual systems, many of which are 30 years old, we’re trying to think about how to connect all the different people, from the executive in charge of an entire drug program or research portfolio to the patients who volunteer to be the subjects in a clinical trial. Can we create much more modern, efficient business processes in a clinical trial that demonstrates safety and efficacy, present it to a regulator, and get permission to bring it to the marketplace? 

How does that translate into your core mission now? 

We’re trying to build that platform to accommodate as many of our customers’ needs today. If you look at Rave, which is one of our core solutions, there’s an interesting illustration of that idea. We never bought into the idea that an EDC system that handles the data in a CRF [case report form] should be separate from a clinical data management system that integrates CRF data with lab data and with randomization data. We thought that should be one system, and that’s what we built. We’ve gotten people in the industry to change their expectations around that. It used to be that people said, “Those things used to be two things. I can’t manage all that data.” Well, it is 2011. I think you can manage that way! 

Our customers who are doing this are creating much more efficient processes, getting visibility into their data earlier. And we hope to deliver for them a real competitive advantage.  

When we think of a technology stack or a business process… we see ourselves as the bottom tier of a stack of layers focused on running the most efficient clinical trial today and in the future. We try to support our sponsors and CRO partners by getting their people on top of that platform. 

How much have you been able to integrate into your platform and where are some of the remaining holes or opportunities? 

We don’t see any finish line where we’ll be done with our platform. The idea is to always think of what people will need in the future and to invest in things that will be useful for those clinical trial processes. If you look at companies in a similar position to us, you’d see something like five percent revenue being put back into R&D. We put more than 15 percent revenue back into R&D. We see so much change coming in managing the clinical development process that we want to make sure we stay on top of those future requirements. 

How far have we come? With Rave, we started to deliver EDC and CDMS in a new, hopefully better, way. To categorize some of the system types, we’ve added randomization and drug logistics [IVRS]. We’ve recently added capabilities in CTMS (clinical trial management system). We think we’re defining a category that didn’t exist in terms of structured protocol design—leveraging a database system to ensure you’re designing the best protocol possible, and using that structured design to inform other activities, like budgeting the clinical trial and managing the way you deal with site grants.  

We’re constantly looking for opportunities to integrate technologies we don’t have. We talk about ‘new, different, and better’—it’s our job to show it’s better. 

Do you typically build new capabilities internally or acquire new technologies as you need them? 

We build a lot, and building technologies is one of our core competencies. We think software development is an art form and we’re proud of the way we do it. But we will, and just did, make a tuck-in acquisition, if we find something compatible philosophically with the technologies we have to date.  

We just acquired a company called Clinical Force, which has capabilities in the CTMS category. There’s a philosophy we have—that we applied to Clinical Force and Fast Track Systems, another company we acquired—that we’re not interested in just assembling a suite of software that meets industry requirements. It must be something that provides value in the platform context. Each individual part needs to add value if used alone, because it’s a great EDC system or investigator payment administration system, but, when used in conjunction with the other parts of our platform, it has to be part of a seamless flow of data between the pieces of the platform. We’re big believers in open interfaces, so when we build or integrate an acquired technology, the way we connect them is with the same set of tools we provide to partners and effectively the general public. We have a website called Developer Central, where anyone can get access to all our documents and APIs. Those are the same tools that our internal developers are using… That openness is key. How can we make any new system part of our platform in a very holistic way?  

Any other significant new acquisitions we should be aware of? 

Clinical Force has put us into the CTMS space. The way CTMS has been implemented by many sponsors, it’s often provided on top of a heavyweight, legacy on-premise system, often highly customized, very costly to upgrade. A lot of people are talking about a better business process to attack trial management activities, requiring a change to the CTMS. But the systems people think it would be too expensive or time-consuming to upgrade their CTMS. My thought is, isn’t the technology supposed to be there to make it easier to implement a better business process? We think, “Great, here’s an opportunity.”  

We’re firm believers in software-as-a-service—not just hosting the application for customers, but making it so they don’t have to worry about implementing the application. We try to make everything as self-service as possible. Our approach to CTMS is to provide it in a similar fashion—consume the modules you need, when you need them, easily over the web. If you’re using them with other systems, use a set of open interfaces. 

What is your stance on cloud computing? Are clinical data incompatible with the cloud? 

If you’re looking at the world of clinical development—I wouldn’t just place Medidata into this category—we are the cloud for clinical data. In the very first days of Medidata Solutions, when we first started doing EDC, the vast majority of sponsors and CROs had no infrastructure to run an over-the-firewall e-commerce application. Their networks were buttoned up because they were used to running in a very conservative pharma-IT environment.  

From the first days, we were in the business of hosting EDC, then other systems, for our customers. They just access them over the web. The [clinical] sites’ doctors and nurses access the software over the web, then via the web they download the data. That is effectively the cloud business model. 

The term cloud is thrown around a lot in various contexts in marketing and other agendas. We think today the cloud is business as usual for us, as it has been for 12 years. We think the way the entire world of IT is going is based on the same concept. The end user shouldn’t have to worry about the infrastructure being used to deliver the functionality you need; you should just be able to consume that functionality. 

Here’s an analogy: Income tax software started with a paper process. You’d have to sit down with your receipts and transcribe onto paper, just like a CRF. So what happened? People sold you software to transcribe your data into a computer… Now, you don’t even have to buy a CD anymore—you just go to the web and purchase the functionality you need and enter your data. That’s become a cloud service. Putting your information into these sites means the software you’re interacting with can give you real-time feedback on how well you’re doing… It’s leveraging a much larger body of data.  

This is not so different from how we think clinical data should be managed. We started with paper, people started building heavy client software, it moved to the web… We’ve been showing demonstrations on how to load data from electronic health record systems into the Medidata platform, effectively bypassing the EDC data entry process entirely. What better way to collect clinical data than to have it happen that way?! 

  It’s fair to say that big pharma’s productivity has been pretty mediocre for the past several years. What is your view on the potential impact and application of new technology, including ‘omics technology, on improving clinical research through things such as biomarker discovery and patient stratification?  

Let’s start with the availability of real integrated platforms such as ours—this will help people get much more effective at the general people-based processes of designing and managing clinical trials. There is just a spectacular opportunity for making this not just more efficient but more effective. 

When ERP came around, the next thing that happened was everybody started trying to design new business processes based on the new capabilities provided by these new technology platforms. Then they realized they needed to effectively measure how well those new processes were working. A whole industry of business intelligence was born, based on that end user requirement. People wanted to have the right dashboards and predictive capabilities to manage their businesses much more aggressively. 

Right now I think we’re living through the same transformation in clinical trials. If you look at the huge amounts of incremental data that we think will help life sciences get new drugs approved, or new combinations, we can’t just throw resources at the problem and expect it to work. We’re talking about an exponentially increasing amount of data we need to wrap our minds around and associate with labeling claims we want regulatory agencies to approve. There is no way to add that capacity at our current level of efficiency. 

We need to use more sophisticated transactional capabilities. We need to layer on the right analytics—we feel passionately about benchmarking as the key to analytics—so companies can look at their own performance, compare their performance to peers and get more effective. Then we’ll have the ability to put more and more data through the clinical research pipeline and answer more sophisticated questions. 

But what about personalizing medicine through new technologies and strategies? 

From the perspective of a patient getting better medical care, personalized medicine is inherently a great idea. As the industry takes the words personalized and medicine though, the two ideas don’t scale very well in their current state. Now we’re trying to put them together, we know we need to do that, but it won’t be possible until we really wrap our minds around how to leverage technology.  

If we do that, there’s an exciting, healthy future for personalized medicine and leveraging new genomic data. If you look back at the Human Genome Project, there was a somewhat naïve view in the general public that all of a sudden, we could understand and cure a lot more diseases. The reality is a lot more complicated. Just having access to a ton more data doesn’t make the data more useful. The relationship between genotypic data and phenotypic data and the vast range of combinations for any given patient mean this is a really different class of problem. I think we’ll be able to equip people to tackle those data but we need to start with basic blocking and tackling.  

Is the ROI Medidata provides principally saving sponsors money, increasing efficiency, expediting trials, or failing ineffective drugs sooner?  

We see ROI coming from two main angles. First, if you’re spending money on Medidata technology, you should be able to save money in the operational component of your clinical trial. For every dollar spent on technology in a clinical trial, there’s more than 25 spent on the operations and supplies required (manufacturing test drug, distribution, monitoring, compensation etc.). Our premise is, if we can help redesign your processes so steps can be automated, or change other business processes, there’s definitely the financial ROI. 

But if you think about changing business processes, eliminating or automating steps, another key ROI is the speed by which you’ll be able to access and leverage the information you’ve collected. You’ll be able to do an interim analysis that much faster, or identify safety or efficacy clinical data earlier to figure out where you might have a problem or whether to change course. From an operational perspective, how quickly can I identify sites that are giving me high-quality data and other sites giving me low-quality data that I might want to spend more time on? 

The third piece of ROI is harder to measure in a tangible time or dollar sense, but it’s being ready for what is going to be the future state of clinical trials. If you look to the forefront of the commercial and academic worlds, they are not just thought leaders but they are designing and running studies that are incredibly progressive in terms of finding combinations of therapies that are most effective, looking for ways to expose as few patients as necessary to harmful doses, etc. These are studies that are difficult or impossible to execute if you don’t have the right kind of integrated infrastructure. I cannot scale up commercially doing hybrid Phase II/III studies if I’ve taken a traditional view of how clinical trial systems work. So we think a key ROI with Medidata is—by putting your operation on top of our platform, we’re there to help make sure you’re ready for the future state. And we look to our customers to help us make sure we know what that future state is going to be.  

Any final thoughts that we haven’t touched on? 

Yes. There’s an interesting dynamic in what’s happening in higher echelons in clinical trial management that sit above Medidata right now. We think about the technology infrastructure. If you look at what’s happening in the sponsor/CRO world, there’s interest in more and more outsourcing, so CROs are getting more aggressive about distinguishing their offerings. Can a CRO provide value beyond just executing on traditional requirements of data management or clinical monitoring? I think that’s a really exciting thing in our industry, because when you shift responsibilities between two parties, it creates an environment where people are looking for new ways to provide that service. That’s dynamic and we think that’s great for our business. 

Hopefully the result is sponsors getting their trials done more efficiently, running their programs faster. CROs are building healthy businesses and looking to distinguish themselves. When you get to the bottom of this, there are companies like us benefiting from people demanding more and better functionality.  • 

This article also appeared in the January 2012 issue of Bio-IT World magazine.