The ongoing expectations for tomorrow’s health—maybe today’s health in some cases—often include something wireless that will make a difference. To get some idea of the wireless possibilities for medicine, watch Eric Topol talk at TedMed:
Although the technology seems doable enough, I don’t see much of it getting done. I’ve been in hospitals more than usual lately to help someone close to me get through treatments. I’m not seeing much wireless medicine there. In fact, I’m barely seeing electronic medicine. In these particular cases, I’ve found that medical records end up scattered between computer files and written notes, and the two often fail to align properly.
Beyond that, I attended a medical devices conference a couple years ago, and a device designer mentioned that most hospitals start with the idea of adding wireless to a new device, but soon reject that in favor of a less-expensive design.
So maybe we can use wireless capabilities to improve medicine, but will it really happen any time soon?
Many recent stories and reports suggest that mobile phones could improve healthcare. For one thing, an increasing number of resources deliver healthcare-related items to smartphones. For example, GE’s Morsel supplies daily tips for living healthier lives. In addition, the data clearly show the rocket-like climb of cell-phone subscribers. For example, the International Telecommunications Union expects the number of subscribers to hit five billion this year, and that’s up from fewer than one billion subscribers in 2000. Five billion cell phone subscribers is incredible in a world with only about 6.8 billion people.
Certainly, mobile devices in general could be used in healthcare. For example, a phone could remind people about medical appointments or the time to take a medication. Likewise, it’s easy enough to find the calories in a meal before you order it at a restaurant by plugging it into some app. These uses seems valuable, but a bit pedestrian.
For a real advance from a new piece of technology in a certain area, though, it takes a killer application—something with incredible value that can only be done with the technology in question. I can imagine such an application of mobile devices for healthcare. For example, it would be amazing if my phone could snap an image of every bite that I consume during a day and calculate the calories, all while also keeping track of how many calories I burn. From that, my device should then tell me what exercise I need to balance my day. I suspect that such a killer app is not far away.
By coordinating data gathering in PET images with a patient’s breathing, Guoping Chang and his colleagues developed a new technique that improves the ability to track lung and thoracic tumors, as described in Implementation of an Automated Respiratory Amplitude Gating Technique for PET/CT: Clinical Evaluation. In short, PET images take a few minutes to gather, and a patient’s breathing makes an image look noisy. By timing the PET data collection with a specific point in a patient’s breathing cycle, Chang increases an image’s resolution, as shown here:
The image on the left (ungated) does not include any adjustment for breathing, but the one on the right (gated) does, which improves the resolution of tumor imaging (Credit: Journal of Nuclear Medicine).
These higher resolution PET images could be used to track tumor progression or to assess the efficacy of a treatment.
In most cases, biotech means genes. At least, most of the publicized applications seem to lean toward genes in some way—typically a pretty tight fit, in fact. Nonetheless, if we focus on anything biological that turns into technology, the possibilities expand considerably. For example, Eric Warrant learned how to improve night vision from his work on dung beetles. If you’d like to learn more about that work, see Dung beetles’ secret superpower: ultimate night sight in New Scientist. To see how night vision might improve from such work, watch this video:
In fact, lots of biology beyond genes can surely create technology. It’s just a matter of—forgive the pun—keeping our eyes open.
With the ongoing rush to bring social media into seemingly every aspect of modern life, I still ask myself: Can social media spur real science? So far, tweets and other social-media messages do not seem to make it any easier to mine the useful from the frivolous. But maybe—just maybe—that is already changing.
But maybe large groups of independent researchers could impact the future of drug discovery and development. That’s the hypothesis offered in Drug discovery in the era of Facebook— new tools for scientific networking, which comes from BioVillage. Also, this article goes far beyond Facebook and mentions many networking tools developed specifically for experts interested in drug discovery. Moreover, this article points out techniques for making such networking tools more useful:
Community networking sites should be more than a passive list of members and their contact details. They should have features that encourage the scientist to visit frequently, despite the information overload that afflicts us all.
It’s easy to believe what is supposedly true. For example, many gardeners say:
Don’t water plants when it is sunny, because the water droplets can focus sunlight, which burns the leaves.
Is that true? Gabor Horvath of Eotvos University in Hungary realized that this rule of thumb had not been tested. So Horvath and colleagues reported on their tests in Optics of sunlit water drops on leaves: conditions under which sunburn is possible, which was published in New Phytologist. If a leaf’s surface is smooth, Horvath et al. report, sun through a water droplet does not cause a burn.
So instead of assuming, ask the data. In fact, looking more closely at anything can reveal unexpected surprises. When I took the photograph above, for example, I just wanted a droplet on a leaf to illustrate this post. I poured a little water on a leaf of an ivy plant in my front yard, snapped the photo, and—only when looking at the photos later—I noticed a spider hiding under the leaf.
So we must always turn to data when asking scientific questions. We never know what we might find.
Even after covering the biotechnology and pharmaceutical industries for years, many steps in drug development and approval remained mysteries to me. But Lawrence T. Friedhoff took me behind the scenes through his book:
In this book, Friedhoff takes readers along a journey that includes many anecdotes along with the details. Although this would not make light reading to everyone, anyone interested in drug development and the approval process at the U.S. Food and Drug Administration will find this book intriguing.
Beyond the scientific and regulatory steps, Friedhoff also covers the business. For example, he writes:
Successful development of a major new pharmaceutical product typically returns revenue that is approximately 500 times the development investment.
Nonetheless, Friedhoff still describes this field as one of continual risk assessment. After reading this book, you will know far more about where the risks lie, as well as where they do not.
In general, medicine already uses the combined results of panels of biomarkers. A physician determines a patient’s health based on a range of markers, such as body temperature, blood pressure, levels of various blood components, and so on. To predict drug safety, however, researchers will need panels of chemical or molecular markers. As this workshop summary states:
No one biomarker is likely to have all of the characteristics necessary to provide a robust understanding of response. As a result, future use of combinations of multiple biomarkers to enable improved prediction of drug efficacy and safety is likely.
To develop such biomarker panels, researchers will need extensive resources—more resources than a single organization possesses. So researchers need ‘big science,’ which will include high-tech tools for data collection and analysis, as well as large populations to discover and validate the biomarkers. Getting all of that will take teamwork, such as academia, government, and industry working together.
The Internet makes many people seasoned comparison shoppers. We can assess the pros and cons of anything from bicycles and cell phones to running shoes and travel destinations. Although we can find mountains of data on such products, the same cannot be said for healthcare options. To decide which treatment might work best for a specific medical problem, you’d turn to comparative effectiveness research, but there’s not much to find. In Initial National Priorities for Comparative Effectiveness Research, published by the National Academies Press, the authors write:
Today, when a patient and physician, perhaps with other clinicians and family caregivers, are discussing the best course of treatment for the patient’s medical condition, they often do not have the scientific evidence they need to make a determination.
They continue:
At present, the translation of research findings into practice is slow and incomplete.
As a result, the authors of this publication polled experts on the areas most in need of further comparative effectiveness research, and here is a graph of the results:
Given all of the resources and efforts that go into current healthcare research, it would seem that more should go into comparing which treatments or techniques work the best.
U-2 OS cells were transduced with Cellular Lights Actin-RFP and Cellular Lights Tubilin-GFP and imaged the next day. Cells were imaged in McCoys media with a 40X objective and acquired at 5 minute intervals over a period of 9 hours. Fluorescence was detected using the appropriate filters (FITC/TRITC). (Image courtesy of Life Technologies.)
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