Software as a service (SaaS) is one of the great innovations of Web 2.0. SaaS enables flexibility and customized solutions. It reduces costs — the cost of entry, the cost of overhead, and as a result, the cost of experimentation. In doing so, it’s been instrumental in spurring innovation.
So, what if you were to apply the principles of SaaS to science? Perhaps we can facilitate scientific progress by streamlining the process. Science as a service (SciAAS?) will enable researchers to save time and money without compromising quality. Making specialized resources and institutional expertise available for hire gives researchers more flexibility. Core facilities that own equipment can rent it out during down time, helping to reduce their own costs. The promise of science as a service is a future in which research is more efficient, creative, and collaborative.
Outsourcing isn’t a new idea. Contract research organizations (CROs) appeared on the scene in the early 1980s, conducting experiments on a contract basis. Industrial science, especially pharmaceutical research, has been increasingly reliant on CROs; spending on CRO-run research increased from $1.6 billion in 1994 to $7.6 billion in 2004, and is projected to hit $20 billion in 2017. Alongside that trend is a corresponding decrease in the percentage of clinical trials run at academic centers — 63% to 23%. In big pharma, there has been a “strategic push away from the traditional strategies of Mergers & Acquisitions and licensing, toward partnering and outsourcing to acquire new drug candidates.”
Despite the steadily increasing involvement of CROs in industrial research, many academics and smaller researchers have found using outside labs to be cost prohibitive and opaque. For those researchers, the process of outsourcing a study involves googling to find service providers with specific expertise, contacting the provider to determine suitability and cost, and then going through a time-consuming reference check and quality verification process. Some simply don’t know what’s out there; they aren’t sure where to start the googling. For many university scientists, there’s an added layer of complexity in the form of purchase approvals for each facility. This process frustrates the scientist. It also results in many core facilities remaining underused.
Frustration has led a recent crop of enterprising startup founders — many of them scientists themselves — to apply IT “best practices” to science. Their goal is to disrupt the slow-moving pace and high cost of research. To do this, they’re applying innovative business models traditionally used by B2B and B2C startups — everything from the principles of collaborative consumption to decoupling service workers from their traditional places of employment.
One of these startups is Science Exchange, a marketplace that aims to increase transparency around experimental service provider cost and availability. Founded by a biologist, Science Exchange helps researchers source facilities or expertise that is unavailable in their own labs. The providers on the site offer everything from microarray analysis to microgravity experiments aboard the International Space Station. Customers search for a service, request an estimate, and pick a provider from the quotes that come in. Science Exchange handles purchase orders and payment transfers, and provides a project-management dashboard. Through the structure of the site, researchers become aware of new facilities, and providers may suggest new technologies. The relationship has the potential to be more collaborative than a typical provider-client relationship.
Science Exchange is the glue in a unique and developing ecosystem. Some of the providers on the site are themselves startups offering scientific experiments as a service. 3Scan, for example, offers a cutting-edge form of 3D microscopic scanning that produces high-resolution images in a fraction of the time of other methods. Researchers in need of this technique needn’t buy their own knife-edge scanning microscope; they can simply reserve the service.
Some SciAAS startups aim to disrupt CROs. Transcriptic, which describes itself as a “meticulously optimized, technology-enabled remote lab,” is working to change traditional wet lab biology by getting rid of infrastructure overhead. They’ve started with molecular cloning and are focused on reducing the time cost and error rate associated with running protocols by hand. Assay Depot has been called the “Home Depot for biology and medicine.” A researcher specifies the experiment he or she would like to see done, and labs submit bids to perform it.
The promise of applying big data technologies to biological research has led to SaaS data analysis tools built specifically with scientists in mind. SolveBio, a computational biology platform, enables researchers to have access to the latest in data-processing technology without having to maintain computing infrastructure or learn cumbersome tools. Collaborative Drug Discovery (CDD), which spun out of Eli Lilly, is a data platform that was built because the founder believed that the future of drug discovery would involve collaboration across specialized channels. Researchers can store and analyze their data with sophisticated tools, and can also open parts of their repository to others. The Gates Foundation and Novartis have been users. Benchling, a platform for life science data management, is also incorporating IT best practices via version control, aiming to create a “GitHub for biology.”
E-commerce principles underlie new marketplaces for scientific equipment. P212121 is helping SMB suppliers of chemical and laboratory reagents to bring their wares online. Their platform uses software to search and curate tens of thousands of products, and focuses on transparent pricing. Enabling labs to bypass behemoths such as Sigma and Fisher allows them to save money.
Startups are also tackling the problem of expertise by facilitating collaboration. Zombal is a job marketplace for contractors who need experts to meet freelance scientists. By outsourcing areas that are not core competencies, more resources are freed up to focus on what’s needed.
These facets of science as a service are just some of the ways that IT principles are being applied to the realm of research. There’s also exciting activity happening around crowdsourced science, open science, and crowdfunding for scientific research. If you’re a scientist, lab head, or SciAAS startup founder who’s reading this, we’d love to hear your thoughts on the changing face of scientific research in the comments below.