Sequencing technology is ready for a breakthrough, but the UX is broken – why the golden age of genomics is about to start

I’m really curious about the next decade of genomics. Why? Because DNA sequencing has repeated the history of computing only half a century later. Now, we seem to be where computers were in 1975, before Apple I. And that was a breakthrough decade.

To follow this train of thought, please join me for a detour into history.

The build-up of computing

The early computers of the 1940s and 1950s were massive racks of lights, switches, and vacuum tubes. These mainframes were incredibly expensive and had to be manually programmed with clunky switches. Still, they were well worth the trouble for some previously impossible tasks, like decrypting enemy codes during wartime.

In the 1960s, the invention of integrated circuits accelerated development on an exponential trajectory. Less expensive minicomputers started appearing in offices, helping with the most intensive calculations. Still, operating them was limited to computer specialists, giving office workers only indirect access to computing.

The era of personal computers started in the 1970s, when Intel and Motorola introduced single-chip CPUs for just a couple hundred dollars. As the chips became faster and cheaper, it seemed evident that computers would soon reach everyday use, and companies started racing to build low-cost microcomputers. But despite being affordable, early microcomputers with their switches-and-lights interfaces were far from being usable by the average individual. The demand for a computer that’s usable for the average human was building up, and Apple was the first company to build one.

The breakthrough in computing

Apple was not the first to build a personal computer. On the contrary, the whole idea for Apple I came when Steve Wozniak saw the Altair 8800 and knew he could do the same but better. And he did. The Apple I was a well-engineered integration of off-the-shelf components with a special emphasis on usability. For example, it was the first microcomputer with built-in support for a keyboard and a TV monitor (as unbelievable as it sounds, those weren’t included before that). The Apple II followed the same path, including color graphics and the ability to read external programs from floppy disks. One of the programs was VisiCalc, a spreadsheet program with the UI we all know from Excel.

VisiCalc’s magically simple interface enabled office workers to do real-time calculations without excessive computer skills. It became wildly popular, and is regarded as the killer app that made the Apple II a record-selling personal computer. While VisiCalc itself was soon outrun by its copycat, Lotus, it forever changed the everyday lives of white-collar workers – and helped Apple become the world’s most valuable company.

The build-up of DNA sequencing

In 1977, the same year Apple II was published, Frederik Sanger’s research group made a major discovery. They figured out how to read DNA by using modified fluorescent nucleotides and gel electrophoresis. The method, Sanger sequencing, was a breakthrough that enabled humankind to do something previously impossible: to explore life on a genetic level. And just like with the early computers, it was incredibly costly and arduous, limiting its use to the most prestigious scientific experiments. The most ambitious of them was the Human Genome Project, a project that took ten years and $3 billion and resulted in a near-complete human genome.

The rapid development of sequencing technology was ignited in 2000, when Lynx Therapeutics Company launched its first massively parallel sequencers. These next-generation sequencers radically reduced the cost of sequencing, just like the integrated circuit did for computing. In fact, the price of sequencing a human genome has decreased faster than Moore’s law, from $100 million in 2000 to $10,000 in 2011 and $1,000 in 2020.

As the price continues to drop with third-generation sequencing, it seems inevitable that sequencing will find its way into everyday clinical use. And the bottleneck has started shifting from sequencing devices to data interpretation, just like the computing industry’s focus shifted from hardware to software 50 years ago.

The breakthrough of DNA sequencing

The sequencing technology is ready for a breakthrough, but the UX is broken.

Sequencing data comes in huge files of hundreds or thousands of megabytes, which complicates even the simplest operations like transfer and storage. The files are currently analyzed by chaining command-line tools into pipelines, which require a bioinformatician to develop and operate. Sadly, doctors and researchers today need to request every analysis from a bioinformatician or learn command-line tools and Python scripting themselves – to tap into the potential of sequencing.

Clinicians and researchers deserve better tools. Something that allows them to explore genome sequencing data without moonlighting a computer science degree. In Solu, our mission is to build this tooling.

Of course, the breakthrough of a new technology requires both an enabling platform and a killer application. For personal computers, they were Apple II and VisiCalc. But what will be the killer app for DNA sequencing? It could be in clinical diagnostics, drug development, or monitoring the next pandemic. The truth is, we don’t yet know, but we intend to be the platform it runs on.

Do you want to be among the first to test our platform? Sign up for early access here.