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Biologists and physicians are notorious for cyberphobia, but this year’s TR100 honorees in biotechnology and medicine are erasing that stereotype – and the boundaries between the life sciences and information technology along with it. Many are pioneering fields intimately connected with or influenced by computing, areas as diverse as bioinformatics and brain-computer interfaces. Some of the most exciting advances are happening in electronic health care, synthetic biology, and ultrasensitive diagnostics.

With the addition of computers, “I see the whole medical process being very different – much less haphazard, much more rational,” says Colin Hill, founder of Gene Network Sciences, which uses computer models of cells to predict how well potential drugs will work. “Ultimately, I see this future world of medicine where doctors can measure molecular activity in the body, feed it into a computer model, and determine the right treatment for the person.”

Even before that day arrives, mobile computing will change the nature of medical practice, says Vikram Kumar, a resident at Boston’s Brigham and Women’s Hospital. He believes that simple, portable computer programs can encourage people to adhere to treatment regimens – one of the biggest challenges in medicine today. As a medical student, Kumar started a company called Dimagi to develop such tools. One example is a PDA-based game that helps diabetic kids understand how their behavior affects their blood-glucose levels. Kumar hopes that one day his management systems, combined with cheap, at-home diagnostic tests that give patients up-to-the-minute data on their physical conditions, will keep people with chronic ailments from landing in the hospital. “The biggest dream I have is that one day we can close all the hospitals,” he says.

Lauren Meyers could help him empty them out, first. By modeling how people interact in schools, hospitals, and other settings, the University of Texas at Austin mathematician can make detailed predictions about how a disease will spread. She can also use those models to determine which interventions – vaccinating health-care workers or closing schools, for example – will most effectively halt an outbreak. The British Columbia Centre for Disease Control has enlisted her help to create control strategies for future outbreaks of SARS: her models have shown that using masks in hospitals, for instance, should be as effective as more drastic measures such as closing schools.

While researchers like Meyers and Kumar are using computers in a literal sense, others are using ideas borrowed from computing to understand and even “program” living cells. In this new field of synthetic biology, “we’re taking existing, well-characterized genes and putting them together in new combinations so that we get interesting behaviors,” says Caltech biophysicist Michael Elowitz. Synthetic biologists call these new gene combinations “genetic circuits,” because they provide a means of rewiring, or programming, a cell’s behavior. Ultimately, these researchers hope to program cells to perform crucial tasks. Boston University bioengineer Tim Gardner, for instance, wants to program bacteria to develop new antibiotics, clean up the environment, or generate electricity. In each case, he’s mapping the genetic pathways that control bacterial metabolism and then trying to manipulate them – to, say, turn toxins into harmless compounds.

Even in cutting-edge medical diagnostics, there are parallels to computing. Electrical engineers have found light to be the nearly perfect medium for transferring data quickly and precisely; similarly, biomedical engineers are using light to obtain information about the body on a finer scale than ever before possible – so that they can detect diseases much earlier and with greater sensitivity.

“The sooner you detect, the better,” says Vadim Backman, a bioengineer at Northwestern University. Many cancers are curable if doctors detect them early enough, and Backman aims to make sure they do. With his technique, a doctor simply shines light on biological tissue. By collecting and analyzing data about light’s wavelength, direction, and polarization as it bounces off different tissues, Backman has developed “fingerprints” of the minute structural changes in cancerous cells. This sensitivity has allowed him to detect colon cancer in rats earlier than with any other method; human tests have already begun. By inserting a probe only 1.5 millimeters wide just a few centimeters into a patient’s rectum, a doctor should be able to predict whether the patient has precancers in any part of the colon. Backman hopes this will provide a cheap, quick, and easy screen for colorectal cancer.

Vasilis Ntziachristos at Harvard Medical School has similar goals. He has developed the hardware and software needed to produce 3-D images that reveal the locations of telltale molecules, such as cancer-related proteins, deep inside the body. Monitoring such molecules could allow physicians to make earlier and more precise diagnoses than they can by examining the anatomical features detected by imaging techniques such as CT and MRI scans. Today, the technology, which is similar to a CT scan but uses fluorescent tags and beams of infrared and visible light instead of radioactive dyes and x-rays, is used to observe molecules at work in living animals, helping researchers decipher how cells normally function and what goes wrong in disease. Within a few years, doctors may be able to use such molecular-imaging tools to detect tumors smaller than one millimeter in size.

These researchers don’t think small, and some of their goals may take decades to reach. Yet within our lifetimes, says Kumar, electronic health care, synthetic biology, ultrasensitive diagnostics, and other technologies will combine to create a whole new way of practicing medicine, allowing doctors to personalize treatments and even prevent illnesses before they strike. Hill agrees. “It’s going to be profound, more so than a lot of the discoveries that happened in the physical sciences and computing sciences,” he says. “Science is finally about life now; it’s finally about us.”

TR100 Startups in Biotech + Medicine


Company Founded/Cofounded


Ryan Egeland

Oxamer (Oxford, England)

Supercheap DNA chips for research and diagnostics; produced using proprietary electrochemistry

Tim Gardner

Cellicon Biotechnologies (Boston, MA)

Precise mapping of bacterial gene pathways to discover novel antibiotics for treating resistant infections

Colin Hill

Gene Network Sciences (Ithaca, NY)

Predictive modeling of cells to speed drug discovery; raised about $9 million

Shana Kelley

GeneOhm Sciences (San Diego, CA)

Molecular diagnostics using electrochemical detection of DNA and RNA; plans to introduce first products in 2004

Gloria Kolb

Fossa Medical (Needham, MA)

Devices to treat the urinary and biliary tracts; four have received U.S. Food and Drug Administration approval

Vikram Kumar

Dimagi (Boston, MA)

Computer tools to help patients and health-care providers; PDA tools in use in India and South Africa

David Liu

Ensemble Discovery (Cambridge, MA)

Using DNA to direct the synthesis of drugs and other chemicals; raised $15 million in its first venture round

Ananth Natarajan

Infinite Biomedical Technologies (Baltimore, MD)

Neurology, cardiology, and gynecology devices; two in clinical trials; raised $9.5 million in government funding

Sandra Waugh Ruggles

Catalyst BioSciences (South San Francisco, CA)

Designing protein-cutting enzymes to treat cancer and inflammation; recently closed first venture round

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