Researchers at the Stanford University School of Medicine and Intel have developed a new, grid-like array of short pieces of a protein on silicon chips capable of identifying patients with a severe form of the autoimmune disease lupus.

The chips have numerous potential applications. They may be usable as real-time, point-of-care diagnostics tools; as tools to speed drug development; or even—as in the case of this study—to identify patients with a particular subset of disease for the purposes of better targeting in clinical trials.

“This method could potentially be used to identify only those patients likely to benefit (from an experimental therapy), and aid in the identification of effective drugs,” says Stanford associate professor of medicine Paul Utz, a co-author of the research, which was published in the August 19 issue of the journal Nature Medicine.

“When I see patients in the clinic right now, I may know they have arthritis, but I don’t know which of the 20 or 30 types of the disease they have,” says Utz. “Now we can measure thousands of protein interactions at a time, integrate this information to diagnose the disease and even determine how severe it may be.”

Utz and his colleagues worked with Intel’s Integrated Biosystems Laboratory. Intel scientists created the protein array for the Stanford researchers to study and helped pay for the work.

When Intel approached Utz with the idea for the chips about four years ago, he thought it wouldn’t work. But with proof in hand, the researchers are already exploring new ways to use the technique, such as in designing flu vaccines that can elicit a strong immune response, as well as ways to incorporate the three-dimensional folding involved in most protein interactions.

“The development of highly multiplex, inexpensive proteomics tools is crucial to deliver on the promise of individualized medicine and point-of-care diagnosis,” the authors wrote in Nature Medicine.

The Stanford-Intel team is not the first to explore array-based approaches. Other research groups have used microarrays to make discoveries in cancer, neurodegenerative disease, aging, and allergy. But while other techniques have developed at a rapid pace, they say, “technological innovation has yet to produce adequate tools for the proteome-level assessment of biological and clinical samples on the small and rapid scale that point-of-care medicine demands.”

While great progress has been made in the field of monoclonal antibody development and other protein engineering technologies, it will be necessary to develop rapid, multiplex, cost-effective testing platforms to determine precise targets for antibodies and uncover more detailed information about molecular interactions, the authors write.

The researchers hope to eventually embed an integrated semiconductor circuit within the silicon chip to create a computer that could take the guesswork out of many clinical processes and identify which treatments are most likely to be effective for a particular disease.