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Running tranSMART for the Drug Development Marathon

By Kevin Davies

January 20, 2010
| If you sense a certain irresistible Lance Armstrong-like determination when meeting Centocor’s Eric Perakslis, it is not a coincidence. Perakslis, the VP of R&D Informatics at Centocor R&D (and newly appointed member of the Corporate Office of Science and Technology at J&J) is a cancer survivor—he was diagnosed with stage III kidney cancer at 38—and has run marathons in support of Armstrong’s LiveStrong Foundation.

Once every other month, Centocor graciously lets Perakslis travel to Jordan where he volunteers as the CIO and head of Biomedical Engineering of the King Hussein Institute of Biotechnology and Cancer. It’s a noble gesture given that Perakslis has his hands full at Centocor R&D—the biotechnology, immunology and oncology research arm of Johnson & Johnson (J&J). Trained as a biochemical engineer, Perakslis has spent the past decade in handling a variety of IT and lab responsibilities. “You’ve got to understand yours skills and weaknesses and then just kind of go where the fun is,” he says.

Amazingly Advanced
The latest Perakslis project has been to spearhead the development of tranSMART (Translational Medicine Mart), a powerful new translational informatics enterprise data warehouse that went live at J&J in June 2009. TranSMART helps investigators mine drug target, gene and clinical trial data to aid in predictive biomarker discovery, chiefly in immunology and oncology. Perakslis says it is an “amazingly advanced” data warehouse that compares favorably with many such efforts he’s seen in the pharma world.

TranSMART is a full translational medicine warehouse, says Perakslis. When he was considering the project, Perakslis insisted that a different approach was needed. “If I’m going to be the head of informatics, all the data has to be mine—I don’t care where it is, what [J&J subsidiary] it’s in, I don’t care if its drug discovery or clinical or post-marketing—in order to do informatics well, all the data has to be in scope.” Few pharmas follow that practice. “When I started recruiting, I could find some good bioinformaticists, but none of them had ever seen clinical data—because they weren’t allowed!” It also meant changing the mindset that sees some R&D leaders more worried about their peers seeing, and potentially misunderstanding their data, than a rival pharma executive.

Breaking down those silos is like developing an internal informatics-without-borders ecosystem. “We take all the resources and capabilities and direct it toward the largest questions facing the organization.” Instead of a traditional bioinformatician only supporting a process like target identification, Perakslis puts them all in one team to apply some scientific and medical rigor to the key strategic decisions facing the development teams and R&D leadership.

The goal is an informatics package that combines all the different ‘omics technologies and informatics disciplines to support or guide a decision. “It is still early days and, at first, we added a lot of value by ruling things out. I can’t tell [the team leader] what indications to pick, but out of five disease indications we’re considering for a novel therapeutic, I have evidence that three are a bad idea. How’s that to start? We are then able to stop debating the five and focus on evolving the thinking about the two that were left.”

Perakslis partnered with Recombinant Data to build tranSMART. He wanted a partner who knew how to assemble data warehouses. Head architect Bruce Johnson worked on clinical data warehousing at the Mayo Clinic, but before that, he worked on railroads. “He just understands data warehousing and doesn’t care what sort of data it is,” says Perakslis. The Boston firm has worked with Partners Healthcare in designing and building i2B2. “Technology-wise, tranSMART is very basic. We haven’t brought in a lot of third-party software or heavy analytics. The system is about the data and the technology is based on open stuff. I don’t owe people millions of dollars a year in contracts.” The closest commercial competition is probably InforSense, says Perakslis. In addition, the system is the first production system from J&J to be hosted externally on the Amazon cloud.

“IT isn’t always a profession that gets the respect it deserves. Sometimes, the MD on staff thinks he can do IT better than the IT staff, [but] I wanted to assemble a team that knew it down cold.” For example, Sandor Szalma, the project manager for tranSMART, brings the needed mix of R&D knowledge, vision, software and social engineering experience and tenacity to the team. Perakslis is currently having discussions about a Red Hat approach where a lot of the advanced analytics is made open source. “I’m not running a commercial software company,” he says. He’s already offered the software to Guna Rajagopal, a colleague at the Cancer Institute of New Jersey. In addition, St Jude Children’s Research Hospital, UCSF and other centers are all considering the adoption of the i2b2-based platform.

Unlike another prominent and excellent J&J informatics resource, ABCD (see, “ABCD: The Relentless Pursuit of Perfection,” Bio•IT World, Nov 2007), Perakslis says is very focused on the chemistry and computational technologies, tranSMART handles large molecules and everything else, capable of providing access to every trial the company has ever run, and allowing clinicians to test hypotheses that enable the design of better clinical trials. In an effort to reinvent as little as possible, tranSMART integrates information from numerous existing vendors at Centocor/J&J, including Jubilant, Ariadne, Ingenuity and GeneGo. There are links to public repositories such as Gene Cards and PubMed as well as direct links to many key internal systems across J&J.

Perakslis has loaded several years of clinical trial data into tranSMART, which can be searched for screening data, lab data, you name it. “We have not had a lot of success in asthma yet but we feel the disease is strategic and we must keep trying. If the PI in asthma says, ‘I just saw a new signature or a new gene in a paper. I wonder if that gene was amplified in any of the patients we’ve seen in our studies?’ That’s an instant search.” 

All Kinds of Data
The data warehouse can be searched by almost anything—compound, disease, gene, gene list, pathway, gene signature. Type in a gene, and a researcher can see every relevant clinical trial, gene expression datasets where expression of that gene was significantly altered, literature results, pathway analysis, and more.

Perakslis says he is incorporating all kinds of data into the warehouse. “When we add new trials, we use data diversity as a selection criteria. If a certain trial will bring a new and necessary data modality, great. We’re growing the mart and growing the content.” While it is meaningless and too expensive to do a whole genome on everybody right now, he says most trials are underpowered with respect to sampling for molecular profiling. “So what is just right? What is enough data from a trial to meet objectives but learn something about the biology or the compound that helps you design the next one in the event this one fails?”

Since tranSMART went live last summer, the accolades have been glowing, particularly from the clinicians and scientists who have changed their study designs because of the data warehouse. For example, J&J’s Elliot Barnathan, executive director of clinical immunology research, says, “tranSMART gives the pharmaceutical physician/researcher the ability to use data already obtained internally or from the public domain at his or her desktop to ask and quickly answer questions with ease.” Hans Winkler, senior director of oncology biomarkers, says tranSMART will transform the way his team analyzes data. “Cross-trial meta-analyses and combined pre-clinical and clinical data analyses are at our fingertips,” he says. Direct cross-referencing with the literature and multiple visualization tools down-stream are all available instantly. This is clearly a quantum leap in our ability to extract knowledge from data.”

A big reason for tranSMART’s success is the social engineering—getting the datasets released, having a QA process, informed consent, etc. As a past CIO for Centocor R&D, Perakslis had written a lot of those policies, on records management, the FDA Gateway project, eCTD, and knew where a lot of that stuff was. But he admits: “The truth is, there’s nothing you could do in this warehouse you couldn’t do anyway if you had the time to do it.”

Perakslis is trying to encourage the Google approach, spending a portion of one’s time thinking creatively about something other than your job. “In pharma, when things are tough and people get busy, they tend to start acting like technicians. They run the models they know how to run… This is about efficiency and innovation. It does save time and money—if people are thinking differently and running better experiments, the quality of decision making should go up.”

Perakslis praises J&J CIO John Reynders for being supportive and “getting out of the way and removing barriers, that’s one of the best things he could do.” As good a tool as tranSMART is, Perakslis says, “it’s only good because we built all our processes around it. If you dropped that in an organization, if you don’t have central agreement about data standards, data availability, compliance and protection of patient rights, it’s not any use.” 

This article also appeared in the January-February 2010 issue of Bio-IT World Magazine.
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