There’s lots of discussion about lab monitoring, the Smart Lab and the next generation of technologies, including promised benefits for both lab operations staff and scientists. The top-of-mind question for many is how real-world teams are using these platforms today? Here’s a snapshot of one.
Thoughts from the team
SynBioBeta is an annual conference — now in its sixth year — that brings together experts and innovators in synthetic biology, ranging from academia to entrepreneurs to industry. In addition to being a great place to cross paths with dear friends from previous chapters of my career and hear from luminaries like George Church, what is always most striking to me is the intellectual horsepower in this industry that is being applied to humanity’s biggest challenges — from sustainably feeding, clothing and accommodating a growing global population to improving human health.
People love surveys, and we’re no exception. After all, data from a pool of respondents on an interesting topic lets you pattern match to see if your profile matches your cohort. So, being the curious types that we are, Elemental Machines conducted a survey of lab managers and other science professionals to:
- Learn more about their experiences and monitoring priorities,
- Understand how they think about strategic uses of the data, and
- Know what they do with the data and where they store it.
Here’s what we found.
When it comes to lab equipment maintenance strategies, there are two prevalent options. The first is the tried-and-true preventative maintenance, and the other (often preferred) is planned maintenance optimization (PMO). Smart Lab technologies can help with both.
The IoT — Internet of Things — is an omnipresent part of our lives, supporting everyday tasks across home, work, fitness and more. Distributed sensors, wireless networking and cloud computing enable us to control lights, monitor security systems, and manage entertainment and HVAC systems, all from our smart phones. In our work lives, smart building technologies sense how many people are in a conference room and automatically adjust lower the thermostat set point, dim smart windows to block out sunlight, and more. Along the way, these systems are gathering and using critical data that can be analyzed to optimize the systems and provide users with valuable insights.
We speak with many customers about their lab-monitoring strategies and goals. Every day. And it’s becoming very clear that the concept of the Smart Lab is taking hold. There are, however, two distinct camps.
We work with a variety of teams and see Smart Lab projects that run the gamut from simple equipment monitoring to sophisticated analysis of multiple data streams. Equipment and lab monitoring gives teams visibility into operational issues and ambient conditions to ensure that everything is operating as expected, while Smart Lab technologies can also help teams understand the other factors that often contribute to repeatability in their work.
Imagine showing up to work on Monday morning only to find that all of your work for the last year has been erased by a malfunctioning freezer. Now, imagine that you had also started monitoring some equipment in your lab, but had decided that the malfunctioning freezer wasn’t quite important enough to justify the expense of monitoring it. That would be a painful moment.
The IoT – Internet of Things — has become an accepted part of our daily lives. Distributed sensors, wireless networking and cloud computing enable us to control lights and HVAC systems from our smart phones, either from home or from a hotel room while on a business trip. More recently for scientific professionals the same IoT technology stack applied to the lab has spawned the concept of the IoLT – the Internet of Lab Things – and just as the IoT enables the Smart Home, the IoLT enables the enables the Smart Lab.
I wanted to take a break from our regularly scheduled programming to highlight a recent true user success story, which illustrates the importance of collecting all the data – whether you think you need it or not.
This particular academic user- a student researcher – was doing growth studies on a specific model plant organism (Pisum sativum var. saccharatum), testing the effect of various experimental soil amendments on germination and seedling growth. The experiment was conducted indoors under ostensibly climate controlled conditions, using natural light exposure. Germination in non-dormant seeds is triggered by the presence of water – which re-hydrates stored food within the seed and activates hydrolytic enzymes – and oxygen. Under normal conditions, P. sativum is expected to germinate between 7-9 days after planting. The entire experiment was scheduled with a 9-day germination budget as this was a time-critical study and previous trials had yielded germination times in as little as 6 days. Almost as an afterthought, an Elemental Machines Element-A already in the general lab area was placed directly in the experiment pod to monitor light, humidity and temperature. (For reference, Element-As monitor ambient temperature, humidity, air pressure and light levels. )