Breakthrough Medical Research Goes Electronic

Silicon chips used in medical research to detect, analyze protein interactions move beyond optical.

With current optical methods medical researchers consume valuable time understanding how proteins interact within the human body, but using semiconductors to synthesize and study disease-associated proteins can speed that process. Intel and Stanford University are now looking to advance that platform and compress research time even further.

Madoo Varma director of Intel Integrated Biosystems Laboratory

Madoo Varma, director of Intel's Integrated Biosystems Laboratory, contends that integrated targeted medicine is an answer to the rise of complex diseases partly due to an aging population.

“Imagine being a scientist at a desk or a doctor in a clinic,” said Paul Utz, Stanford associate professor of medicine. “Blood or some other material is analyzed, and instead of the scientist or physician interpreting the data, a computer spits out the disease, prognosis, likely outcomes from therapy and perhaps even next steps should the therapy fail.”

Utz co-authored a paper published last year in Nature Medicine about a proof-of-concept study in which scientists synthesized short segments of biological proteins, or peptides, on silicon wafers using sequential steps of light exposure, photolithography and other methods akin to semiconductor manufacturing.

Able to analyze thousands of protein interactions simultaneously, the chip can detect those that are associated with certain diseases and their variations, and at much higher speeds. The chip was used to identify patients with a particularly severe form of the autoimmune disease lupus, which can sometimes take years to diagnose.

The research resulted from collaboration between Stanford and Intel, which have been working on silicon-based peptide arrays since 2008 in hopes of proving them useful as a platform for applications including clinical research and point-of-care diagnostics.

Moving Beyond Optical Systems

Madoo Varma, a co-author of the paper and head of research and development at Intel’s Integrated Biosystems Laboratory in Santa Clara, Calif., said that research is already underway on the next phase of the platform that will be less costly and more portable.

“The obvious next steps are to take this platform electronic instead of optical,” said Varma. “Today, the platform is based on an optical system, which is the traditional way of doing biology, where you use tags and shine light to make them stand out. Electronics gets us to a label-less platform.”

Current methods for multiplex biological measurements are not feasible on a large scale using luminescence or fluorescence, according to Utz. As a result, more effective drugs can be designed by researchers and then prescribed by doctors.

Advanced Medicine for an Aging Population

Paul J Utz MD Stanford University

Dr. Paul Utz, Stanford University associate professor of medicine, is an expert in the study of human and murine autoantibodies and autoantigens, among other areas of immunology and rheumatology.

As the world’s population gets older, so must its medicine, according to Varma.

“The population is aging and chronic, complex diseases are on the rise,” she said. “The blockbuster drugs are ineffective 30 to 70 percent of the time and part of the reason is when pharmaceutical companies make drugs it’s hit-and-miss. They take these complex compounds, try them on people, determine it works to some degree and everyone gets the drugs.

“The bottom line is genetic compositions are different among the masses. People are now realizing that integrated targeted medicine is the answer.”

Varma said she and her team are thrilled to be part of this predicted paradigm shift, but the objective of their work is not for Intel to develop the technology for commercial and clinical purposes. Should Intel ever want go to market with a diagnostic tool deriving from the research, pending FDA clearance, the company would need to seek outside partners.

“Intel is not in that space — we’re not a life sciences company,” she said. “This is a research program and we’re taking a proof-of-concept perspective. Any commercial discussion is a long-term proposition.”

Even without plans to go to market with the research, Intel is making a significant contribution to the biometric world, according to Utz.

“Predictive medicine by a computer, driven by Intel arrays and computers powered by Intel chips …. The company has an opportunity here to transform how physicians like myself practice medicine.”

Breakthrough Medical Research Goes Electronic

Silicon chips used in medical research to detect, analyze protein interactions move beyond optical.

With current optical methods medical researchers consume valuable time understanding how proteins interact within the human body, but using semiconductors to synthesize and study disease-associated proteins can speed that process. Intel and Stanford University are now looking to advance that platform and compress research time even further.

Madoo Varma director of Intel Integrated Biosystems Laboratory

Madoo Varma, director of Intel's Integrated Biosystems Laboratory, contends that integrated targeted medicine is an answer to the rise of complex diseases partly due to an aging population.

“Imagine being a scientist at a desk or a doctor in a clinic,” said Paul Utz, Stanford associate professor of medicine. “Blood or some other material is analyzed, and instead of the scientist or physician interpreting the data, a computer spits out the disease, prognosis, likely outcomes from therapy and perhaps even next steps should the therapy fail.”

Utz co-authored a paper published last year in Nature Medicine about a proof-of-concept study in which scientists synthesized short segments of biological proteins, or peptides, on silicon wafers using sequential steps of light exposure, photolithography and other methods akin to semiconductor manufacturing.

Able to analyze thousands of protein interactions simultaneously, the chip can detect those that are associated with certain diseases and their variations, and at much higher speeds. The chip was used to identify patients with a particularly severe form of the autoimmune disease lupus, which can sometimes take years to diagnose.

The research resulted from collaboration between Stanford and Intel, which have been working on silicon-based peptide arrays since 2008 in hopes of proving them useful as a platform for applications including clinical research and point-of-care diagnostics.

Moving Beyond Optical Systems

Madoo Varma, a co-author of the paper and head of research and development at Intel’s Integrated Biosystems Laboratory in Santa Clara, Calif., said that research is already underway on the next phase of the platform that will be less costly and more portable.

“The obvious next steps are to take this platform electronic instead of optical,” said Varma. “Today, the platform is based on an optical system, which is the traditional way of doing biology, where you use tags and shine light to make them stand out. Electronics gets us to a label-less platform.”

Current methods for multiplex biological measurements are not feasible on a large scale using luminescence or fluorescence, according to Utz. As a result, more effective drugs can be designed by researchers and then prescribed by doctors.

Advanced Medicine for an Aging Population

Paul J Utz MD Stanford University

Dr. Paul Utz, Stanford University associate professor of medicine, is an expert in the study of human and murine autoantibodies and autoantigens, among other areas of immunology and rheumatology.

As the world’s population gets older, so must its medicine, according to Varma.

“The population is aging and chronic, complex diseases are on the rise,” she said. “The blockbuster drugs are ineffective 30 to 70 percent of the time and part of the reason is when pharmaceutical companies make drugs it’s hit-and-miss. They take these complex compounds, try them on people, determine it works to some degree and everyone gets the drugs.

“The bottom line is genetic compositions are different among the masses. People are now realizing that integrated targeted medicine is the answer.”

Varma said she and her team are thrilled to be part of this predicted paradigm shift, but the objective of their work is not for Intel to develop the technology for commercial and clinical purposes. Should Intel ever want go to market with a diagnostic tool deriving from the research, pending FDA clearance, the company would need to seek outside partners.

“Intel is not in that space — we’re not a life sciences company,” she said. “This is a research program and we’re taking a proof-of-concept perspective. Any commercial discussion is a long-term proposition.”

Even without plans to go to market with the research, Intel is making a significant contribution to the biometric world, according to Utz.

“Predictive medicine by a computer, driven by Intel arrays and computers powered by Intel chips …. The company has an opportunity here to transform how physicians like myself practice medicine.”