/ Lab Monitoring

Why (and how) you should collect “unnecessary” experimental data

I used to have a professor whose recipe for scientific success boiled down to the adage: you need to work hard, and you need a little bit of luck. While it might be true, this little bit of luck can seem tantalizingly out of reach to the laboring scientist staring at their trendless data.

What we should be doing, rather than relying on luck, is gathering more data points. When you have daily microscope images, notes on when you opened a new bottle of reagent, and the temperature of your sample (when tested), then you increase your likelihood of identifying trends.

But how do we do it?

The ideal laboratory vs reality

Imagine this ideal experimental laboratory. Every variable can be controlled. Everything is monitored. When your experiment spits out seemingly meaningless results, you can analyze every condition at the tip of your fingers. You can look at temperature, pH, and humidity, or watch your sample’s morphological changes over time. Then you get your eureka moment- some previously unimportant condition has affected your sample, and you have figured it out!

Now back to the real laboratories where we work:

Your freezers, refrigerators, incubators, and water baths vary in temperatures. This negatively effects your supposedly bioactive samples, prevents growth of a cell population, or causes the decomposition of your sample.

Your equipment isn’t enclosed in environmentally regulated conditions. They are subject to the whims of a valiant A/C system that can’t compete with the rising humidity of a Boston summer, the forgetfulness of a visiting technician who leaves a door open too long, or a well-meaning janitor who accidentally unplugs an instrument.

Lastly, as people who need sleep and occasionally need hours away from the laboratory, we cannot monitor our experiment 24/7. In these realistic but non-ideal situations, how can we fully monitor our experiment and the environment in which it occurs?

The “work harder” approach

One way to address this issue is to work harder. I tried this method. Instead of running a pilot experiment with only a few samples and a single readout, every experiment became the full experiment.

I ran every control, took images and samples daily and had multiple readouts. It sounded really good on paper, and even better to my boss. I did end up with more data, which was very helpful. However, all of this data that I collected, was a lot of work and not a scalable, or even repeatable, process.

Don’t get me wrong, work is not a bad thing. But I should be spending my time on high-value activities like data analysis and less time on mindless aspects of science, such as sitting next to a plate reader and recording it’s temperature in a notebook.

The other issue with this method is that I was deciding what to monitor, and the conditions that I deemed unimportant did not get logged. The problem with that is we do not always know which condition is the one affecting our experiment.

The technology approach

Fortunately, this is 2016, almost 2017, and we have technology! Specifically, we have technology that can constantly monitor environmental parameters - whether it is the temperature, pH, humidity etc, and it can automate data capture directly from our experiments. We are getting far closer to our fantasy lab than you might think.

When we incorporate solutions for instrument monitoring and data collection into our laboratories, we collect a wealth of information we may not have even thought we needed.

Take a case I had with a lab electrospinner. This was an earlier model, constructed in house and lacked any fancy environmental controls for temperature and humidity. During the aforementioned humid Boston summers and rainy days, I noticed the faithful electrospinners were getting different results.

If my equipment had sensors that monitored humidity, I would have discovered crucial insights. I could have compared humidity data between previous days to identify an emerging trend, and prevent an instrument failure. Previously useless data would have new life breathed into it, rather than requiring me to repeat an experiment needlessly.

With the support of new technology, scientists are able to invest their time into the critical thinking portion of science, and away from the mindless tasks. (Not to mention that tech doesn’t sleep or complain - like, say, interns)

Consider incorporating lab monitoring, lab scheduling and data collection solutions to get you one step closer to your ideal laboratory! Learn more about how TetraScience can help.

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Kristie Tevis

Kristie Tevis

Kristie holds a PhD for Biomedical Engineering from Boston University and has over a decade of research experience. She is currently working in protocol development and IP data organization.

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