The Birth of the Laboratory Operating System

And How Startups Conceived It

By: Spencer Weiss (Penn ‘20)

Steve Jobs presenting the iPhone

The modern biology laboratory shares many characteristics with backpacks before the release of the first iPhone: a device to store your music, a device to send messages and take calls, and a device to surf the internet. In 2007, Steve Jobs took to the stage to announce three devices, one for each of these functions, and at the end presented the iPhone to raucous applause, declaring that it would do all three. Much of the advancement that enabled the creation of this product can be attributed to hardware development, but an equal amount should be apportioned to the integration of the functions of separate electronics into a mobile operating system, the impact of which needs no hyperbole. In the years since the introduction of the first-generation iPhone, our backpacks have grown lighter with the integration of separate electronics into smartphone operating systems, and the capabilities of the individual tools has only grown. Likewise, the laboratory has begun its transition into an integrated operating system, albeit in a less theatrical fashion.

Operating Systems as Platforms

Throughout 2017, it has become commonplace to declare various emerging technologies to be the operating systems of their respective arenas. Voice has been called the operating system of the home for capitalizing on the budding internet of things and there are various claimants to the be the operating system of the car. A key distinction must be made, however, between these and the laboratory. In each of these areas, the applications that will take advantage of the OS do not exist yet, for the most part, but the applications for the laboratory exist, and in some cases, have existed for many years. The lab, therefore, is waiting for its proverbial “iPhone moment,” when a platform begins to aggregate the functionalities of laboratory tools, an opportunity that has been a focus for startups of late.

Laboratories moved past manual data transfer many years ago, with results for many experiments now directly uploaded to computers for analysis. While an improvement over a notebook and an abacus, this is not an ideal solution, since many laboratory devices require proprietary software that does not integrate well with other applications. This leaves researchers with large fees and a time-intensive workflow in order to make sense of their results.

Integration and Aggregation

Benchling, one of the primary new players in the laboratory space, is taking advantage of non-proprietary data sources to allow researchers to streamline their workflows. For example, it is possible to import and assemble plasmids, search by DNA or amino acid sequence and analyze protein structures using the platform, which would have been cumbersome, expensive or impossible otherwise. Moreover, Benchling offers features for storing online lab notebook information and for sharing protocols between researchers, making it the ideal platform around which to organize a lab.

Benchling’s Interface

Because of these varied productivity features, Benchling has been analogized as the Google Docs for life sciences, but its aspirations are larger. With incoming integrations from popular open-source tools like the plasmid repository AddGene, Benchling will be even more integrated into the workflows of researchers, and as its user base grows, device manufacturers will be under more pressure to integrate as well. This will ultimately benefit users, who will be have access to better tools at a lower price. In this way, Benchling isn’t Google Docs, it’s an operating system.

The company is doing all that it can to encourage this virtuous cycle of aggregation onto its platform. While industry and enterprise groups like pharmaceutical companies must pay to use the product, it is free for academia, students and individuals. The more users and tool integrators that self-select onto the platform, the more compelling the product will be for potential users.

The benefits of aggregation for users of Benchling are already starting to manifest. A few common, tedious laboratory processes have begun to be automated, such as determining the chemical characteristics of protein sequences and identifying exon regions of RNA sequences. This allows researchers to make more informed predictions about the characteristics of genes before actually running experiments, which can cut costs by making tests more targeted to specific genes.

Scientific Commodification

As the locus of differentiation in the laboratory becomes one where scientific tools are aggregated onto platforms, another effect is that the machines used to generate data become commoditized. As long as your sequencer, flow cytometer and electroporator perform well enough, don’t cost too much and are compatible with your operating system, they are good enough. This will force manufacturers to continue to develop improved versions of their technology and to offer them at more reasonable prices, a boon for researchers and the progression of science as a whole.

The falling cost of genetic sequencing since the Human Genome Project, plotted on a logarithmic scale.

This has already started to occur in genetic sequencing, where prices are falling at a rate outpacing Moore’s Law. As other processes start to follow the same pattern, more powerful tools will be available to researchers at lower prices.

At the Weiss Tech House Innovation Fund, we are excited about these promising trends in biotechnology and have been lucky enough to fund multiple companies that have taken advantage of this landscape. BioBots has developed a 3D bioprinter, which can print tissue types not feasible with traditional methods. Its capability to print tissues based on computer models makes it an excellent candidate for eventual integration into laboratory operating systems. We hope that laboratory OS makes future research and development smoother for such companies, and that they allow more ideas in biotechnology to come to market.

Spencer is an Innovation Fund Project Manager and our team’s Director of Sourcing. He is in Penn’s M&T Program. Spencer has previously published research on cancer immunotherapy through Georgetown University.

Weiss Tech House Innovation Fund is dedicated to funding, promoting, cultivating, and supporting student entrepreneurship in the UPenn community. Working on a startup? Interested in partnering? Want to get involved? Drop us a line at