Science fiction has given us many views of what the science labs of the future will look like. The Star Trek medical bay (depending on the series) features needleless drug delivery, teleportation replacing baby delivery, and non-invasive rewriting of the genetic code in every cell. Minority Report had an endlessly interactive computer system to interpret predictions of future crimes. Even the slightly more realistic Contagion showed how science could be performed through automation and coordination of robots.
Star Trek Sickbay
But what will research labs look like in the next 5 to 20 years? What environment will the next generation of scientists grow up in? Looking at my graduate mentor’s lab notebooks, I cannot fathom the genetics work of the mid 1990s before the Human Genome Project data was freely available on Ensembl, when genes had to be cloned and sequenced on huge gels. Graduate students in the next decade will look back at our labs and wonder, “How in the world did they get anything done without *blank*?”
Internet of Things
Enter modern technology. WiFi networks, smart phones, and the cloud are starting to change the face of science labs. The Internet of Things is a term for connecting inanimate objects to the local ethernet and world-wide internet. Everyday examples are TVs, lamps, security systems, and even refrigerators and ovens that can help you save energy, make a grocery list, and protect your house. Now developers are starting to apply the same model to the parts and equipment of research lab.
Traditionally, each person in a lab maintains a lab notebook as a repository of their experiments, data, and ideas. But lab notebooks are decidedly analog: everything is written on paper, nothing is linked, information is easily buried and lost, and important details can be omitted. Even when using computer files on lab servers, documents and spreadsheets can easily become disarrayed.
To fill the gap are apps such as ZappyLab’s Bench Tools. My favorite feature of this app is that you can enter in your step-by-step protocol, and then use it like a checklist for any samples or experiments you are running. You can even embed timers into particular steps. If your lab is short on timers, or you want to bring your timer with you to lunch, there is a quadruple timer in this app as well. You can also add notes and write down your results in the journal feature. A related service from ZappyLab is PubChase, which purports to be a better search engine for the scientific literature and can help you find more relevant papers to your work. ZappyLab is currently running a Kickstarter campaign to expand their services.
Paid services offer even more options. Lab Guru coordinates nearly everything for a lab, including literature libraries, protocols, sample databases and trackers, storage locations, linking experiments, inventory, orders, and much more. Used well, you’d never forget where that box of specimens is, what concentration of buffer you need, or what the results of the last time you ran that western.
Collaboration and sharing data can have their own problems, especially when your data sets, images, videos, etc. exceed the confines of standard cloud services like Dropbox. Websites such as figshare are trying to meet the need of the Big Data movement in science. They also offer a means of publishing your data, though how this type of open publication fits into academia is yet to be determined.
Bucking the traditional publication trend are open access journals such as PeerJ. PeerJ’s model is to charge users a modest fee to join, and members can publish as many articles for peer review and publication as they like for free. All articles are then made freely available to the public.
The Future of Labs
From my point of view, the trend in science is that over time, as new technologies make experiments easier and faster, the bar for publication rises. In 1953 Watson and Crick published their famous paper elucidating the structure of DNA. This famous article is about one page long with two figures (a drawing and a barely comprehensible X-ray diffraction image). Doubtlessly, generating these data involved a tremendous amount of dedication, hard-work, and insight. In the future, as our technologies improve, the expectation may mean that you have to have a genetics screen, sequencing for mutations, crystal structure, animal models, and small molecule inhibition studies just to be sent out for review.
We need to start considering how to apply these changes to undergraduate education. After all, if we want our current students to be ready to work in a technology-aided laboratory, then they should gain experience in their lab courses. For instance, undergraduates are expected to maintain lab notebooks. What if they kept track of their protocols and data on tablets or smart phones instead? They could include their own pictures and videos, which would also make for a more rewarding lab experience. Sharing data with classmates is also easily achievable. Where once lab courses were focused on an individual or group’s data, now sections of 12-24 students can work in concert to generate robust, and potentially useful, data sets. These rich lab experiences could increase student retention and even entice more students toward careers in research.