Steve McCoy from TetraScience talks about how his idealized high-tech perception of research was confronted by the low-tech reality he witnessed when entering the life sciences industry.
In 2016, millions of people worldwide invited a complete stranger into their homes, and immediately she made an impact for the better. Amazon recently announced that its Echo and Echo Dot – devices powered by the voice-controlled system Alexa, were best sellers for the retail giant over the recent holiday period; so popular, in fact, that the devices were on back order into 2017 .
If this isn’t a sign that connectivity is the new rising star of tech, I’m not sure what is. With smart tech continuing to expand rapidly, people now expect their home devices, gadgets, even their cars to sync seamlessly and with little effort. “Internet-of-Things”, “Smart Home”, “Wearables”, “Smart Cities”, and “Connected Car” are now everyday terms used to describe the collective concept of connected devices, and although still a relatively new phenomenon, connectivity has already made quite the impact.
And the positive implications of the adoption of this technology speaks for itself. Tech Times reported that employees using wearables reported an 8.5% increase in productivity. In fact, the US Department of Transportation is converting Columbus, Ohio into a smart city; complete with self-driving electric shuttles, high-speed WiFi stations, and better transportation to areas within the city. As this new technology is embraced in the gym, the city, and our automobiles, we should expect to see similar improvements made in our work environments as well, right?
Having entered the life sciences industry about 8 months ago, I expected smart technology to already have widespread adoption. Prior to joining TetraScience, my experience in labs was primarily limited to Hollywood depictions. While scientists are not currently extracting dinosaur DNA from mosquitoes trapped in petrified amber (we’re not far off), it is still hard to think of R&D as anything but the embodiment of innovation. 60 Minutes, VICE, and Business Insider continually delivers news on a weekly, if not daily basis, about all of the cool discoveries and processes R&D scientists are unearthing. Naturally, one would expect the instruments and technology employed in research to be a reflection of this cutting-edge image .
But, that assumption was only half correct. Scientific instruments are some of the coolest instruments I’ve seen, with capabilities that are simply mind-boggling for non-scientists. The technology that powers them, on the other hand, leaves plenty to be questioned. Freezers and refrigerators recording temperatures via circle paper graphs must be manually collected and physically filed (yet Kristen Bell and Dax Shepard have a fridge that can order food and provide a real-time view of their shelves). Analytical instruments that can cost upwards of $100,000 still require users download information onto a thumb drive before walking over to their work station for uploading onto a different computer. With thumb-drives becoming a tech relic, getting data from these instruments should not be so complicated.
How can an industry that has driven innovation in so many different arenas be content with such antiquated tech practices? Many I’ve spoken with in R&D cite the hundreds of different hardware manufacturers as the root cause, but with plenty of smart tech brands readily available, this issue should be easily remedied. Pen-and-paper methods should remain an option, but not the norm, but for many R&D labs and scientists, the opposite holds true, and for the most part, it’s become accepted.
But don’t be mistaken: as with connected devices in our daily lives, there are implications to life in the lab without connectivity. Deloitte’s annual study on pharmaceutical innovation showed that profits on cash investment for big pharma is at an all-time low (3.7%), due to shrinking profits and plateaued development costs. A shrinking ROI means that there’s less budget to invest in the latest instruments, additional staff, and/or new investigations & projects.
What did Deloitte cite as one of its three key findings to reduce R&D costs? Lifting the burden of data complexity. Downsizing the amount of time spent on low-value tasks, such as moving data from an instrument to an ELN (what we call “data-jockeying”), can help R&D personnel focus on the more technical complications of data management. An apathetic approach to getting more from technology providers, however, won’t let this initiative happen anytime soon.
Thankfully, there’s been a growing number companies addressing the need for connectivity in the lab. A few of those that come to mind are Benchling, LabGuru, and of course, TetraScience. To accelerate the availability and capabilities of technologies that those companies offer, scientists must demand the industry behemoths improve their own offerings. Change won’t come overnight, and it certainly won’t be without its faults (just ask Alexa), but it’s time that R&D labs catch-up with their public perception.