The recent Bio-IT World meeting featured some exciting forecasts about disruptive healthcare advances from advanced computing technology. We’re closer than ever to process streamlining, artificial intelligence and combining the best ideas from other industries. Many themes I like to blog about — clinical decision support, data visualization, patient-entered health data — were addressed provocatively in the talks. Here are some trends I’m watching.
• New data visualization systems will increase scientific productivity. Keynote speaker Bryn Roberts of Hoffmann-La Roche demoed a futuristic, multi-touch tool for reviewing and designing compound molecules, built with the help of Accelrys. The working surface is at least ten times the size of a computer screen. It allows chemists to visualize molecules by rotating them and zooming in, add notes or different chemistry groups sift through different sets of molecules and organize them in clusters, and email pieces of information to team members for review. Watching the video, I could see that this system beckoned a new type of human interface interaction. The tool reminded me of the virtual imaging technology used in Star Wars to depict the Death Star and other three dimensional objects. The large screen draws the eye to structurally important features of the molecules, and images can be explored using one’s hands. The information is easier to organize. Playing with the demo at the Accelerys booth, I wished they’d design an interface to manage my social networks. I could add notes, see global trends and establish relationships between objects much more easily than I do now. Maybe in Facebook 2.0.?
• Patients become empowered by sharing their own data. Speaking of social networks, I was excited to learn more about PatientsLikeMe from founder Ben Heywood. PatientsLikeMe is a website that allows patients with similar diagnoses to connect and share experiences and ideas, helping them achieve the best possible outcomes and quality of life. The information offered by the site goes far beyond what two users can share in a web conversation. Beautiful, brightly colored graphical tools allow patients to visualize trends in the data – their own and that of others with similar diagnoses — potentially providing additional wisdom not currently offered by conventional medicine. One interesting screen shot compared the frequency of side effects reported during the clinical trial for a particular medication with the significantly higher frequency reported by users of PatientsLikeMe. It will be interesting to follow this platform’s progress and see how it and other health social networks begin to integrate, providing a more centralized means of obtaining health advice.
• Knowledge engines will inform about disease, using crowd-sourced health data. Stephen Wolfram, creator of Mathematica, believes we’ll soon have the tools to use health data to model a patient’s disease, anticipate adverse events or suggest personalized treatment options. His new knowledge engine, Wolfram|Alpha, could be loaded with high volumes of data, much of it coming from patients themselves. Individual users could query the system, drawing upon the models it generates, and receive support for healthcare-related decisions. As users begin to load data directly from wearable, automated sensors, rather than entering it manually, the messiness typically associated with crowd-sourced data will begin to dissolve. Also, because patients will be voluntarily entering information, their data would not be subject to the privacy rules governing data collected by a health institution.
Compared with the banking and consumer product industries, healthcare has been a dinosaur when it comes to using advanced computational approaches. But I think in the near future we will see measurable change. I hope the healthcare and pharma industries will be dramatically different by the time I reach my old age – if so, we’ll have these three leaders and others I met at the conference to thank.