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Prepping for Future Demand, SAS Adds JMP Genomic Tools to Its Drug Development Suite


As part of a strategy to align with the long-term goals of its pharmaceutical customers, SAS this week said that it has added genomic and proteomic analysis capabilities to its SAS Drug Development software platform, which is primarily targeted to clinical development.

Laurie Rose, director of global health and life science for SAS, said that the integrated system is geared toward researchers who are "breaking down the walls between discovery and development" to bring biomarker and molecular information into their clinical analysis.

Rose conceded, however, that this target market is still fairly small and that the company has not yet implemented the integrated platform at any customer sites.

"There are probably more people who are talking about that as the direction they want to go than are doing it, so the demand is at the lower end of the curve right now," she said. Nevertheless, she noted, "there are people out there that we've been working with either on the SAS Drug Development side or the genomic analysis side who have really driven us to bring those two platforms together."

SAS Drug Development is a centralized repository for clinical research data that is validatable under the US Food and Drug Administration's 21 CFR Part 11 regulations for electronic signatures.

The company's genomics software, meanwhile, was originally developed as part of SAS Scientific Discovery Solutions, an enterprise-scale system that included a centralized data repository called SAS Research Data Management, along with SAS Microarray, SAS Genetic Marker, and SAS Proteomics.

In March, SAS relaunched the genomics tools through its JMP business unit, which specializes in data visualization and user-friendly desktop implementations of analytical software tools [BioInform 03-24-06].

The products were rebranded JMP Genetics, JMP Microarray, and JMP Proteomics, while the remaining components of SAS Scientific Discovery were rolled into SAS Drug Development.

Now, SAS is giving customers the option to bring these two platforms together in order to analyze molecular information in a CFR 11-compliant environment.

Researchers using the JMP tools in the desktop environment have the flexibility of an interactive environment for discovery, "but once it is in that SAS Drug Development environment, everything is tracked," Rose said.

One driver for bringing the two software families together was the FDA's Critical Path Opportunities List, released in March [BioInform 03-24-06], which highlighted biomarker identification as one of its primary focus areas.

Rose said that SAS had already "started going down the path" toward integrating molecular data with its clinical research infrastructure, but added that the Critical Path has "influenced" the company's development strategy. "We were very interested in seeing what the opportunity areas were when they came out, and the fact that that whole first section was about biomarker qualification and different areas where they're looking for the industry to start making more sense of that information and applying it on the clinical side — that was a perfect fit for that direction that we had already decided we wanted to go in," she said.

While the market for this integrated platform is still not defined, "it is growing and we're seeing it growing," Rose said.

Certainly, SAS is not the first to ensure that its bioinformatics tools work in a CFR 11-compliant environment. A number of microarray-analysis firms, including Rosetta Biosoftware, Genedata, and Affymetrix, have enabled their software to be validated in 21 CFR 11-compliant environments.

"There are probably more people who are talking about that as the direction they want to go than are doing it, so the demand is at the lower end of the curve right now."

In addition, Insightful, a SAS competitor in the clinical research market, has its own microarray analysis tools as well as a nascent effort underway to develop biomarker-analysis software [BioInform 05-19-06].

Michael O'Connell, director of life science solutions for Insightful, said that even though the company is not yet seeing a great deal of demand for its ArrayAnalyzer software in the later stages of drug development, some of its pharma customers are using microarray data alongside clinical information in discovery. "We've seen more of the adoption of the combination of clinical microarray data in the early phase — people wanting to see if there are genes that affect drug absorption or drug bioavailability," he said. "In the early-phase stuff, we've seen a lot of traction, but it's been a little more exploratory."

While characterizing the FDA's Critical Path focus on biomarkers as a "megatrend" that should have a long-term impact on the industry, O'Connell said, "We haven't seen it translate into the market so much yet."

O'Connell noted that even though Insightful doesn't have "a formal product line" that integrates its genomics software with its clinical trial analysis tools, he said that ArrayAnalyzer is already integrated with the company's S-Plus platform, which can be validated under CFR 11.

Rose said that the SAS platform is one of the first integrated systems for merging genomic data with an FDA-compliant clinical research infrastructure. "There aren't a lot of solutions out there that provide that level of integration," she said, so researchers within pharmaceutical firms who are trying to exploit genomic data in clinical trials "have to do it themselves."

Rose noted that one barrier to adoption is likely to be the organizational "silos" that currently divide discovery from development within pharmaceutical firms. "They all have their walls up and they all just want to be very possessive with their data and what they're doing," she said. "We feel like even though there are still cultural barriers that exist, we have that technology platform to enable that sharing of research information, and I think that's going to become hugely important as people really start to better understand some of the implications of that genetic data and how it can affect the safety and efficacy of a drug as it moves downstream in the process."

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