By Christopher Vaughan
Imagine for a moment a not-too-distant future and you are in your doctor's office getting disturbing news. A biopsy taken during the last visit shows that you have a type of pancreatic cancer that has virtually always been fatal. There are no FDA-approved treatments.
Yet there is glimmer of hope. Thanks to advances in the fusion of computing with clinical practice, the doctor is able to search medical records, and compare your biopsy results for possible matches with ongoing research protocols. A few queries of the genomics and proteomics databases show something promising.
Recently, a researcher used a supercomputer to model a key protein involved in cell growth. He then compared the model with a database containing millions of compounds to identify any that interfered with that protein. One compound stood out; it had originally been tested as an anticancer agent in the 1980s, but only three percent of the tumors had responded to it — a clinical failure by most measures. But by looking further and doing a genetic screen of all those in the trial, the researchers discovered the drug was 95 percent effective against cancer for those with an “atypical” genetic profile, such as yours. As a result of your doctor’s analysis, you are enrolled in a new clinical trial and your cancer is brought under control.
For ASU researchers like Sethuraman “Panch” Panchanathan, director of the School of Computing and Informatics at ASU, this vision is not science fiction. This blending of biological, computing and information sciences with clinical practice is the inevitable future of medicine. The only thing standing between the vision and the reality, the pivot around which everything turns, is the ability to access, interpret and use information. In the future, information will become the life-blood of medicine, linking research with virtually every aspect of healthcare.
“There is a convergence of information science, biological science and clinical science,” Panchanathan says. “People with backgrounds in the sciences and engineering, medicine, computing and informatics will come together to create what we call personalized medicine.”
The study of information — how it is gathered, stored, manipulated, accessed, transferred, given meaning and presented — has itself become so large and important that it has been given its own terminology: informatics. With ASU’s strengths in computing, engineering, and biological sciences, the university has bet that it can do big things in this arena. ASU is forming a new transdisciplinary biomedical informatics program, which will partner with the Biodesign Institute and others to define the future of personalized medicine. This program is part of the larger School of Computing and Informatics.
The biomedical informatics program at ASU will offer doctoral and master’s degrees, as well as continuing education for healthcare providers, according to Elizabeth Kittrie, associate director of biomedical informatics. Kittrie explained that for clinicians who wish to broaden their skills and improve career prospects, the program will provide a state-of-the-art education in the theory and practice of electronic medical recordkeeping, clinical decision making, and the management of information systems in healthcare. For scientists and engineers, the program will offer interdisciplinary courses and research opportunities that will enable them to occupy leadership roles in designing and implementing the next generation of biotechnology systems, pharmaceutical development, integrative biology, and translational research.
Panchanathan said the interdisciplinary nature of informatics requires strong bonds and collaborations between the new department and existing schools, colleges and departments. “We will have a number of joint appointments inside and outside of ASU,” he noted, “With partners such as the Biodesign Institute, International Institute of Sustainability, School of Life Sciences, Colleges of Nursing, and Departments of Mathematics and Statistics, Health Policy, Economics, and Center for Law, Science and Technology.”
Many of those outside ASU think that many factors make Phoenix a fertile ground for an effort in biomedicine. The collective strengths of internal ASU collaborators complement local business strengths in computing and communication, and leverage the strengths of medical institutions like the Translational Genomics Research Institute (known as TGen), the University of Arizona College of Medicine, Phoenix Program, Barrow Neurological Institute, Mayo Clinic and Hospital and Banner Health.
“Those of us involved in informatics look with some envy at the opportunities ASU has ahead of it,” says J. Robert Beck, vice president of technology at the Fox Chase Cancer Center in Philadelphia. “Biomedical informatics has grown like Topsy from a number of domains, and now is the time to start a program like this.”
The Power of Information
The use of computers in biology and medicine is not new. Computing has been critical in analyzing data since the days of SUV-size machines using stacks of punch-cards. During the 1960s, the National Library of Medicine began to form a discipline called “computers in medicine,” but the use of computers was limited both by tradition and by a lack of computing power. Physicians and researchers often used computers as glorified calculators or library card catalogs that simply extended capabilities they already had. “In the 1970s, hospitals were buying computers, but mostly using them for fiscal and administrative matters,” says Edward Shortliffe, chair of the department of biomedical informatics at Columbia University.
Everything really began to change in the 1980s and 1990s. Until that time, the process of finding the order of the chemical compounds that make up the DNA “blueprints” of every organism, a process called gene sequencing, had been very slow. However, at that point the process became so efficient that scientists began to dream about sequencing the entire human genome, which is comprised of three billion chemical base pairs. To actually do this, and then to make sense of the resulting sequences, required collaborations between researchers, clinicians and computer scientists to create sophisticated mathematical models as well as find the best ways to harness the massive computing power needed to do the job.
At the same time as the genome work was being attempted, the application of computing to research and clinical practice, large increases in the number and variety of new medical therapies, along with HMO efforts to control health care costs, prompted investigators to use computers to analyze what procedures were done, and to help tell when and how they were effective. This “evidence-based” medicine has become a rallying point among health care specialists who want to increase the efficiency and effectiveness of medicine. ASU recently created its own Center for the Advancement of Evidence-Based Practice, which aims to facilitate the integration of research and practice across multiple settings to improve healthcare, patient outcomes, and systems.
“Studies show that when practitioners use evidence-based care, the outcomes are 28 percent better,” says Bernadette Melnyk, dean of the College of Nursing at ASU, which houses the center.
These developments, paired with the increased power and pervasiveness of computers, has opened the door to a new type of personalized medicine, one that can be tailored for individual differences in genetics, lifestyle, diet and biochemistry. Clinicians will have the power to track how their patients are doing in ways that weren’t imaginable 20 years ago. The big thinkers in the field say that the coming changes in medical care are even hard for people to imagine even now. The changes will provide vast rewards, but the shift won’t be without risk, they say.
“I don’t think people have any idea how disconcerting the future of health care will be,” says George Poste, director of the Biodesign Institute at ASU. “We are going to have data streams coming at us from all levels. We are going to have to embrace the convergence between the life sciences, health sciences, the ubiquitous presence of computing, electronic miniaturization, neurobiology and brain-machine interactions. It’s going to be daunting.”
For all the concerns he notes, Poste also thinks such rapid progress is absolutely necessary and can’t come too soon. “The challenge for health care is the growing imbalance between the resources we have and the infinite demand we’ll see in the future. The baby boomers are a large cohort of individuals who are selfish about health care,” Poste says. Their demands for all the best care available can only be met with drastic improvements in the efficiencies of medicine, he adds – efficiencies that will come in large part from biomedical informatics.
Bench to Bedside and Beyond
Once biomedical informatics takes off, it will change medicine completely, researchers say.
“What we are doing is taking advanced computing ideas and applying them to the whole range of medical issues, from understanding gene structure to clinical activities,” says Jeremy Rowe, director of research, strategic planning and policy for information technology at ASU and associate director of the School of Computing and Informatics.
To spend just a little time with those who think deeply about the future of medicine is to get a vision of a complete transformation of the field at every level.
Basic Research on Biological Systems
This is one area in which informatics already has a strong foothold. Now that the human genome has been sequenced, investigators are busy searching the data for patterns that will illuminate how it functions. The field has become so mathematically complex that some biologists complain that they have a hard time understanding what their colleagues are doing.
At the same time, other researchers are trying to “map” the other –omes like the proteome (all the proteins in the body), the transcriptome (the collection of RNA molecules in a cell), and metabolome (the small molecules in a cell). Each of these processes takes massive computing power to analyze.
The ultimate goal is create a picture of how these components interact with each other within the whole system. This “systems biology” approach requires even greater computing power. Once researchers understand biological systems at this level it will completely change the nature of their work, researchers say. When researchers are able to construct a schematic diagram of cell function, they will be able to program cells like computer engineers program microchips.
Drug Discovery
Right now, drug discovery is a very inefficient, hit-or-miss affair. Researchers guess about the type of compounds that might work, or modify those that are already known to work. They may screen thousands of compounds before they find one that might have promise. And companies will spend years and hundreds of millions of dollars attempting to bring each of these to market, knowing full well that only 10 percent of the most promising candidates will make it.
As researchers begin to understand how cells work mechanically, they will be able to design molecules that switch on or off specific activities in particular kinds of cells. If antibiotics were “magic bullets,” these molecules will be smart bombs, taking out only the problems cells while leaving other cells intact.
With massive computing power, drug companies will also able to take the opposite tack in drug research: throw everything against the wall and see what sticks. With microchips that can analyze thousand of genes or compounds and robotic assay systems, they can test far more drug candidates than ever before.
Diagnosis
It’s common sense to think that each disease will affect one’s body differently, but even two individuals with the “same” disease are affected differently. The virus that causes influenza is best known for coming in many changing strains and varieties, but all pathogens have subtle genetic variations that cause them to act differently. To compound the confusion, the same strain of the “same” disease can even act differently in each person that they affect, because we all have individual genetic variations. One of the reasons that cancer is so hard to fight is that each cancer has its own biological profile. Cells on one side of a tumor can behave in a completely different manner than cells on the other side of the same tumor.
Advances in personalized medicine, driven by the power of biomedical informatics, will facilitate accurate diagnosis of disease states by providing a complete understanding of how individual pathogens act at the molecular level in each person. Screening may involve looking at the activities of hundreds of proteins, enzymes and genes in various kinds of cells.
At other times, physicians will have no idea there is a problem, but will find disease by screening millions of cells and molecules in the body for patterns that are disease markers. Researchers in California, for example, recently announced that they had trained dogs
to detect lung cancer by smelling telltale molecules on the breath of those afflicted. Dogs naturally have olfactory organs that are extremely sensitive to such odors, but there is no reason that a microchip couldn’t be created to detect similar molecular patterns for each cancer.
Monitoring
In the future, George Poste says, technology will allow physicians to get medical information about everyone, everywhere, all the time. This development will be an important part of caring for the aging baby boomers. “Right now we have only 13 percent of the nursing homes we will need,” Poste says. “Remote monitoring will allow people to live at home and have their health monitored from afar.”
Monitoring devices may take the form of implanted microsensors that relay real time information about vital statistics like blood sugar, oxygenation, body temperature and blood enzyme levels to facilities that watch for anything amiss. Or such devices may be a simple as chips attached to bottles of medication.
“Right now, an estimated 80 percent of medications are not taken as prescribed,” Poste says. “A chip that costs about as much as a jelly bean could be attached to the medicine container and transmit real-time information about when the bottle is opened and how many pills are taken out.”
Telemedicine
Once medical tests and radiological images are stored and transmitted in standard formats, specialists will be able to diagnose and even treat people who are half way around the world. Some medical schools are already experimenting with high-definition video and data that allow neurologists to diagnose stroke from afar. Others are working on robots that perform surgery while under the direct control of a surgeon hundreds of miles away.
Making it Happen
Much of the discussion about biomedical informatics is couched in the future tense, but at many Phoenix-area institutes, the future is happening now. TGen in particular has had tremendous success pulling basic research into the clinical world. In a few cases, their work has already saved people who were deemed beyond the reach of modern medicine.
Since its founding four years ago, TGen’s goal has been to take the vast amount of information that we have or can get about the most basic biological structures and to translate that into technologies that can actually treat disease.
For TGen’s president and chief scientific officer Jeffrey Trent, the question comes down to this: How do you define a disease at the molecular level, and then use that information to find a targeted therapy? In answering that question, “we are taking a systems biology approach to medicine,” Trent says.
TGen screens hundreds or thousands of genes to find the few that have mutations than contribute to diseases like prostate cancer, for instance. In one experiment they screened 2,000 segments of RNA to see if any of them would interfere with the growth of cancer cells.
The massive numbers of tests that are necessary demonstrate why gathering and analyzing information has to be automated, Trent says. A single experiment, for example, required that over 80,000 samples be run through a series of manipulations. “That’s why you need robots,” Trent says. “You can’t do that on the backs of graduate students.”
A recent case demonstrated how powerful such an approach can be. TGen scientists heard from a 63 year-old woman from New Jersey who had adenoid cystic carcinoma, a cancer for which there is no established treatment. She had been on a number of experimental therapies, but none had worked. With no therapies left to try and facing certain death, she turned to TGen.
For Trent and the TGen scientists, the challenge was to find out what made this particular tumor vulnerable. “Patients are individuals, and so are their tumors,” Trent says.
They first obtained a biopsy sample of the tumor from New Jersey, and then set about screening 20,000 genes in the tumor to find possible therapeutic targets. The solution was surprisingly commonplace. “It turned out that the tumor was covered with vitamin D receptors,” Trent says. “By putting her on a regimen of vitamin D we were able to control the tumor.”
One year later, the woman approached TGen again. The vitamin D was controlling the growth of the tumor, but the mass was still causing a great deal of bone pain. The scientists went back to work, once again sorting through tens of thousands of gene products in search of a different therapeutic target. What they found this time was that the tumor had elevated production of a growth-promoting protein called platelet-derived growth factor. This was good — an FDA approved drug called Gleevec is well known to short-circuit this molecule. A prescription for Gleevec made the pain disappear.
A Lot of Knowledge is a Dangerous Thing
The potential downside of making so much medical information easily available is that very personal information can be sent around the world in digital form at the speed of light. The questions of who will have access to that information, and how they will make decisions using the information for individuals and groups raise many moral and ethical issues. The new ASU biomedical informatics program has included medical ethics as an important part of its mission.
“We are going to make bioethics an important part of the curriculum and we are linking faculty and students up to ethical practices review boards in clinical and hospitals,” says Rowe. “It will be very important to educate computer scientists and engineers who may not be used to thinking about ethical issues, and to give physicians an idea of the potential problems they might encounter.”
Congress has recently passed a few laws regulating the control of medical information, but medical ethicists feel that a lot more remains to be done. A perennial concern is how insurance companies may use genetic information to limit coverage. In some cases the companies deny health or life insurance coverage based on information that the patient may not even be aware of. For instance, a one hair with root attached may reveal that you are destined to get Huntington’s disease, a fatal, inherited disease that strikes in mid-life.
Much of the challenge of informatics will be in balancing the need for easy access to information for those who need it against the need to regulate that access so information doesn’t fall into the wrong hands. The same information that an insurance company might use to deny coverage is the same information that a pharmacist might use to avoid an adverse reaction in a prescribed drug. How to balance these seemingly conflicting interests are key issues that need to be explored.
Sometimes the flood of available information brings up completely unexpected quandaries. At a recent ASU symposium on biomedical informatics, a physician in the audience told about a recent dilemma he had faced. “I had a 67-year old patient with two kids, whose wife had passed away,” the physician said. A test revealed that the man had Klinefelter’s syndrome — a chromosomal disorder that imparts infertility — his whole life and hadn’t known it. “Do I tell him the kids are not his, or do I decide to withhold that information from him?”
With some estimates of such cases of non-paternity running as high as 10 percent nationally, widespread genetic testing would likely lead to many explosive family situations. “These are issues that our society hasn’t worked out yet, but we have to,” says Joyce Mitchell, chair of the Department of Biomedical informatics at the University of Utah.
Putting it All Together
Such a broad range of challenges and resources would be difficult for any
university to bring together successfully, but Panchanathan and the university leadership are convinced that the initial components are in place to make it happen. The biomedical informatics program is currently hiring its faculty and developing new curricula; Kittrie expects the degree programs will be ready for students as early as the fall of 2007.
“An important part of this is the zeitgeist of the Phoenix area,” Rowe says. “We have the clinical support in the medical clinics and institutes, the intellectual support of our universities, the business support in the region, and a growing population of older individuals. We have the opportunity to build and leverage on all of these things.”
Rowe notes that one of the main advantages that ASU has is that the program can be designed from the start as a unified biomedical informatics department. “We have the opportunity to start from scratch and try something different, to learn from what other programs have done and create a unique niche,” he says.
While other universities are also exploring informatics, their history is often rooted in either bioinformatics or medical informatics, says Mark Musen, head of Medical informatics at Stanford University and an advisor to the ASU program. “Bioinformatics and Medical informatics are still being set up as different programs, as if they are separate,” he says. “My message is that these are one field.”
Beck is one among many who are eager to see how it all turns out. “We’ve been saying for decades what needs to happen in this field in terms of data and communication,” Beck says. “Now these things are all coming together here, in a university with a president who is a capital-R Radical willing to throw out all the established orthodoxies to achieve something that is necessary and useful.”
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“The creation of the School of Computing and Informatics is a major step for ASU’s evolution in this critically important arena of innovation,” Crow says. “It’s a response to the increasingly important role that the acquisition, evaluation and utilization of massive amounts of data play in many aspects of modern life.”