Life science laboratory automation today is in the same position that computers were in the 1970s: about to move from niche novelty to mainstream ubiquity. This is the story of how the democratization of computers happened, and how laboratory automation is undergoing the same transformation today.

The concept of a "personal computer" (PC) first entered the mainstream in 1977, the year the Apple II was launched. Before the Apple II, the primary way people interacted with computers was through "time sharing" on centralized "mainframe" machines. People no longer have their own computers in front of them, but have a terminal connected to a central host, and multiple people can share the running time of one computer. Most people have never even seen a real computer, and it is so complex and mysterious that only very specialized engineers are allowed into the room where it is stored.

In the early days, this model worked well for large businesses and government organizations that used computers to handle large tasks such as payroll and taxes. In fact, it worked so well that Thomas Watson, chairman and CEO of IBM in the first half of the 20th century, once said: "I think the world market might need five computers." Outside large organizations The idea that anyone would need to use a computer—let alone own one (or more!) themselves—was considered impossible and undesirable.

Typical mainframe computer room

This is much the same way many people view laboratory automation today. Today’s laboratory robots are true “mainframe” machines—large, expensive, and requiring specialized automation engineers to run them in a central facility. They are ideal for batch processing of high-throughput experiments, but 90% of the world’s laboratories still do not have access to them.

Typical mainframe laboratory automation facility

For biologists who are lucky enough to have access to laboratory automation, it is often just a "time-sharing" approach reminiscent of a centralized mainframe. Whether you are in an academic lab or in industry, researchers often access automation through their institution's "core lab" rather than operating it themselves. And, just like mainframe operators of the past, core labs will assign the jobs researchers hand them and perform "batching" to efficiently distribute the core's automated capabilities among the jobs. A few days (or weeks, if you're not very lucky and/or have the funds) after submitting your assignment, you'll get your data back from the core lab.

Opentrons is on a mission to change this paradigm. While mainframes are great for high-throughput work, they shouldn't be the only option for automating laboratory work. Scientists should be able to automate their own work. We need a personal laboratory robot, a "laboratory automation computer" so that people can directly experience the accelerated workflow that laboratory robots provide. That’s why we make the OT-2, the world’s most affordable high-precision laboratory robot.

We believe there are three keys to building a truly “personal” laboratory automation platform.

1. The robot must be affordable so that small and medium-sized laboratories can purchase it themselves. 2. They need to be easy to use so that the average research scientist can operate them. 3. They need to remain flexible to work within the dynamic, collaborative workflow of scientists.

OT-2 can be mounted on half a laboratory bench

The OT-2 meets all these requirements. It starts at $5,000, which is less than most labs' discretionary spending budgets, meaning in most cases they don't even need bureaucratic approval to purchase the robot. We integrate the user experience (UX) processes of consumer technology companies, adhering to the same usability standards as Apple and Google. Our machines are the only fully modular laboratory automation platform on the market—features can be easily added or removed as needed for researcher workflows—and allow people to easily share their automation protocols with collaborators.

But just because we bring personal lab automation to market doesn’t mean it will become a workhorse in every life sciences lab. Computers' path from obscurity to ubiquity didn't happen because everyone was a nerd and wanted to play BASIC programming; it happened because people could do powerful things with their computers. This is the idea of ??a “killer app” – an application of a technology that causes the mainstream population (rather than the technology enthusiasts who were early adopters) to use it. For the Apple II, the killer app was VisiCalc, the first spreadsheet program. With VisiCalc installed, the Apple II became a game-changing tool for businesses to manage their finances. Suddenly, the world changed; not just the largest businesses needed computers, but every business needed computers.

This is why the Opentrons protocol library is so important. It provides access to applications that can be downloaded and run on the OT-2 laboratory robot. These applications (PCR setup, NGS library preparation, nucleic acid extraction, serial dilutions, etc.) are completed daily or weekly in life science laboratories around the world, and it can take hours each time a scientist manually runs them. Additionally, these apps are developed with our community of users and partners, meaning they are "for scientists, by scientists."

While personal laboratory automation is still in its early stages, we are already starting to see how it can change the way people perform laboratory work. Stanford's Keoni Gandall is able to generate 100x more genetic designs every week with his OT-2; Aiden's lab at Baylor College of Medicine is able to move away from NGS library preparation and focus on data analysis rather than spending most of its time transplanting solutions; researchers at the Chan Zuckerberg Biocenter have automated tedious cell culture steps so their researchers no longer have to worry about manual trypsin digestion — the list goes on. Scientists in 45 countries around the world, from big pharmaceutical companies to small startups, from MIT and Stanford to community colleges, are increasing productivity and moving towards scientific goals faster than imagined.

Where will we be in five or ten years, when every scientist has his or her own lab robot, just like we all have our own computers? Just as the rise of the personal computer transformed the possibilities for information processing and media, personal laboratory automation will transform the possibilities for the life sciences. When this happens, what will happen to our global bandwidth for life science research? Will we make new discoveries 10 times faster? 100 times? 1000 times? What will we create with ubiquitous automation that is now out of reach? I'm incredibly excited to see the world we can create when biologists are finally freed from the monotony of pipetting and given the tools to create their dreams—all the amazing treatments, products, and ecosystems we can create.