Cloud Computing Can Help Life Sciences Catch Up Before It’s Too Late

Biotechnology has the power to fight global threats like pandemics and climate change, but outdated experimental and data collection methods are holding it back. Guy Levy-Yurista, CEO of experimentation platform developer Synthace, explains how cloud computing could accelerate biotech companies’ efforts to solve big problems.

There is a sundial in Redu, a sleepy village in rural Belgium, which is a warning to us all. Next to an engraving of the familiar DNA double helix, the words “tempus fugit, augebitur scientiaare carved in stone. Translated, it tells us that as time passes knowledge will increase.

It’s a feeling of optimism, but it’s also a warning. Yes, we will grow in our knowledge of the world around us over time, but the question that follows, at least for me, is: how quickly will this happen? Perhaps the current answer to this question is “not fast enough”.

Here is another way of asking the same question: will science reach its true potential before the end of this decade? My answer: only if we free him. We need to find a way to free science from all that is holding it back in order to tackle a host of crises facing society, including antibiotic resistance, pandemics and climate change.

And make no mistake, the challenge ahead of us is enormous. Our industry is under incredible and growing pressure to tackle biological complexity, move faster to scientific knowledge, and improve reproducibility of data. But we have to fight against the hard old ways; legacy technology and processes that can stifle the discoveries we know are at our fingertips.

If you don’t believe me, ask yourself: among all these challenges, are our biologists able to work in the best possible way? For now, I would say it’s the opposite. Researchers are limited by the need to be in one place – in the lab – tied down to their lab stations and to deal with demanding equipment that traps them in a vicious cycle of menial tasks. Science is too often fixed in one place and held hostage by the limitations that we, as mere humans, have imposed on it.

Why is it? Too much friction exists between the biologist and the science he wants to do. Too much relies on manual intervention, which introduces errors and strangles progress. If we’re going to deliver better drugs, better biotech, better climate tech, better food tech, we have to find a way to reduce that friction by removing our reliance on manual involvement. We need to decouple the imagination and creativity of our best minds from the limitations of the physical spaces we depend on right now. And the clock is ticking.

The sundial of Redu

The solution is all around us: the cloud. We need to take advantage of next-generation, cloud-based automation technologies by mending the missing link between these technologies and the physical world itself. To make that connection, we need a reliable way to represent biological work with code. If we can do that, then we can represent the experiences themselves in a digital format. Even better, we can digitize, and therefore liberate, science itself.

When we can do that, connections to all other digital media open up. The true power of artificial intelligence, machine learning, and ultimately quantum computing is becoming available to life sciences, enabling the realization of its full potential.

“Representing experiments with code” is easier said than done, however. It doesn’t happen overnight. Who should write this code? Is it the biologists? Are we asking them to become computer scientists? No, that would be a tragic mistake. Biologists don’t want to spend their time coding; they want to spend their time doing science.

At the most basic level, scientists need tools that reduce the steps between them and the goals they pursue in their experiments. The tools should be intuitive, guiding researchers to what they want to achieve, suggesting patterns to save time, and helping them discover creative new ways to do their work. Even better, they should help them produce the highest quality data, ready for cloud computing and all the other technologies that may be connected to it.

While there are many platforms currently helping to digitize record keeping or the purely automated elements of the experimental process, we have seen very few others move into the experiment digitization space of the same way we. Translating modular experiments into automation instructions, the platform our company is building bridges a yawning gap between experimental design and the context-rich data scientists need to move forward.

Every scientist is driven by the desire to find solutions to humanity’s most difficult problems. Today, they rarely have the best environment to translate their boldest ideas into scientific reality. Soon all that will change. Armed with next-generation cloud-native technology, they will quickly solve humanity’s most pressing problems.

To quote the poet EE Cummings, “all ignorance slides towards knowledge.“The joy of scientific discovery is one that should be encouraged, enhanced, and pursued with the strongest intentions. But the clock is still ticking. Tempus flees.

Guy Levy-Yurista has been CEO of Synthace since May 2021. He has over 20 years of experience in strategy, marketing and product leadership roles at startups and Fortune 500 companies.

Cover image via Elena Resko. Online image via Jean-Pol GRANDMONT via Creative Commons.

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