Taking a biotech invention from bench to market is an expensive undertaking. Starting with a promising drug target or device prototype, company founders face a series of hurdles relating to space, equipment, personnel and legal and accounting demands. Because the setting up of this infrastructure is capital and labor intensive, and it takes place before the achievement of key clinical milestones, the biotech model has traditionally relied on attracting a large initial round of investment to fence away intellectual property and support translation and commercialization.

Yet the business model for innovation by startup companies is undergoing a remarkable transformation. The past decade has witnessed advances in open-source software, cloud computing, rapid prototyping of hardware, logistics in transportation of goods worldwide and mobile communication, leading to the establishment of a 'sharing economy'. In the tech economy, startup companies can now access a co-working space, use cloud-based servers and collaborate with the larger community for coding needs. This sharing model is particularly effective when the resources involved are expensive, specialized or scarce1,7.

In the biotech industry, challenges to access such resources are amplified. Companies can benefit from shared access to a variety of resources, including chemical synthesis, molecular biology, cell biology, animal testing and assay development services, instrumentation, and hardware and software development—and this is sparking a proliferation of capital-efficient startups that tap into an expanding ecosystem of service companies. Moreover, with increasing competition for academic positions, industry jobs and research funding2, the talent pool of trained scientists who can offer their knowledge and skills to biotech startups on a freelance basis is growing. On the basis of the above evidence, we believe that a sharing model will become an increasingly popular one for biotech startups.

Mine and yours

Biotech companies are already relying on outsourcing for DNA sequencing and planning of clinical trials3. Today, there are four large areas emerging for biotech sharing: physical space, equipment and supplies, knowledge, and financing. In the sections below, we take each in turn.

Space. Securing a workspace can be difficult for any early-stage company, given a lack of credit history, dearth of acceptable space to rent and rapidly changing needs. For life science companies, finding a workspace can be doubly challenging owing to the need for specialized infrastructure, such as chemical fume hoods and biosafety cabinets, and the production of medical waste. To address this, some universities are opening incubators on campus with wet-lab space4, but such spaces are typically reserved just for startup companies generated by those institutions. In addition, there are also privately run co-working lab spaces5, but given the high market rents (especially in biotech hubs), even a small dedicated footprint can be unaffordable to companies that have not yet obtained institutional financing (Table 1).

Table 1 Shared lab spaces, including co-working labs and accelerators
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'Sharing' wet labs are also emerging, providing offerings at affordable prices and catering to early-stage companies6, including Harlem Biospace, a biotech incubator in New York City that we run (Box 1). The sharing at these types of places extends beyond physical space into operational costs (utilities and routine lab and office supplies), lab infrastructure (freezers, hoods, purified water and gas) and equipment (for microscopy and cell counting). Equally important for biotech companies are community programs that expand their professional networks and increase their chances of obtaining financing or revenue. Programs include office hours with mentors, guest lecturers and regular internal meetings of the member companies. This connection to peers and mentors can be a critical support network for the teams of early-stage ventures, especially for those starting their first companies.

There are also accelerator programs, which offer combinations of office space, lab space and access to mentors and networks in exchange for an equity investment (Table 1). An example is SOS Ventures (San Francisco, CA), whose IndieBio accelerator offers $250,000 and four months of community lab space in return for a fixed 8% equity share of supported ventures. There are others, such as Accelerator Corp (operating in Seattle and New York), which takes an active role in setting up a company in return for higher ownership stakes. For a biotech company, deciding among these programs can come down to whether founding scientists prefer to take the long path of building a company themselves versus serving as advisors to a team brought in with the help of investors.

Pharmaceutical industry players are also launching accelerators of their own to help identify future strategic investments or acquisitions. One example is Madison, NJ–based Johnson and Johnson, which runs Janssen Labs (JLabs; Table 1). Similarly, equipment vendors are experimenting with offering space, cash investments or in-kind equipment to build relationships with future clients and push the technical capabilities to propel product development. The Illumina (San Diego, CA) accelerator program is one of these, through which startup companies gain access to sophisticated genomics equipment. It is worth noting that these corporate programs usually require less equity than investor-run accelerators, and they can offer access to expertise and resources otherwise out of reach at an early stage. Care must be taken, however, to understand the objectives of the sponsoring corporation so as to ensure a strategic fit, as these companies will typically ask for long-term licensing rights should technical milestones be met.

Equipment, reagents, tools and services. Sharing of equipment, reagents, tools and services allows sellers to gain revenue from excess capacity of equipment and labor, and buyers to gain access to a wide array of capital-intensive and specialized resources (Table 2). Already, contract research organizations, animal facilities and sequencing labs have been offering outsourced resources and services. New models of open marketplaces are being developed that can empower startup companies to more efficiently offer and purchase specific lab equipment and services.

Table 2 Sharing of equipment, services, reagents and software
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Academic core facilities (such as animal facilities, clean rooms and microscopy facilities) offer shared resources that have traditionally been reserved for internal use, but are increasingly welcoming paying outside users to help make operations self-sustainable. Although these arrangements are often based on hourly usage rates, biotech companies must discover these facilities and contact their managers to gain access. Private facilities offering equipment are also becoming available. For example, TechShop (Menlo Park, CA) offers machine shops and hardware prototyping equipment in eight cities across the United States, with hourly usage and fixed membership cost models.

At present, individual labs often share equipment with labs at the same institution, especially where the researchers know each other well. This model could expand and is in fact changing, as database efforts, such as Kit-Catalogue (http://www.kit-catalogue.com/projectpages/), help institutions to internally take stock of and share equipment. Emerging open marketplaces, such as San Diego, CA–based Lab Fellows (http://labfellows.com/) and New York–based Synaptic (http://synaptic.bio a digital platform from Harlem Biospace; Table 3), could also enable efficient discovery of and access to equipment within and across institutions and private companies.

Table 3 Online platforms to enable collaboration
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In terms of research costs, a large driver, particularly in drug development, is the production and maintenance of specialized reagent libraries. Initiatives to share these resources across companies include the Molecular Libraries Small Molecule Repository (MLSMR; http://mli.nih.gov/mli/secondary-menu/mlscn/ml-small-molecule-repository/) in the United States and the European Lead Factory (ELF; https://www.europeanleadfactory.eu/) in Europe. These consortia of academic, private and government organizations share chemical libraries and best practices for high-throughput screening to increase the chances of picking the right targets to pursue for costly further development. Participants share the cost of establishing and maintaining libraries and then pay at cost for checking out compounds from the library.

Efficiency gains from sharing are not limited to physical resources such as reagents or equipment: open exchanges and collaborative development of software tools can produce dramatic impact. For example, when labs adopt versioning systems (such as git) or publish software and data to public repositories (such as github or bitbucket), other labs can incorporate the projects into their own experiments, in exchange for reviewing the code and suggesting improvements. Nonprofit research institutions such as Sage Bionetworks are helping to structure collaborations across institutions for disease research as well as providing open software tools for collaboration. Cooperative development does not preclude the original author from licensing the code. For example, Broad Center's (Cambridge, MA) Genome Analysis Toolkit (GATK) is open source and licensed, such that basic researchers can use it for free, whereas commercial users pay for use, which ensures funding to maintain the project.

Labs are also pooling data sets rather than holding onto private but redundant data collection. In certain cases, labs have decided that the benefit of obtaining a more complete pooled data set outweighs any competitive risks.For example, in the Accelerating Medicines Partnership (AMP), a public-private partnership also involving the US National Institutes of Health (Bethesda, MD) and Food and Drug Administration (Rockville, MD), pharma companies and nonprofit organizations share data toward identifying biomarkers and understanding the underlying mechanisms of neurodegenerative diseases.

Although certain types of experiments can be readily outsourced to dedicated third-party vendors, most experimental steps cannot. Yet increasingly, customized research protocols, too, can be shared. Science Exchange (https://www.scienceexchange.com/) offers a marketplace for industry and academic researchers to identify other researchers able to perform specialized or complex experiments, with a review system to ensure reliable providers. Experimental protocols that can be highly standardized, such companies as Transcriptic (Menlo Park, CA) and Emerald Cloud (S. San Francisco, CA) provide automated and programmable robotic laboratories that are capable of performing repeatable experiments for life science research.

For business services, in Avalon Venture's Community of Innovation (CoI), experienced scientists, chief financial officers and other senior talent are hired to split their time among the cohort of supported ventures. This arrangement enables ventures to access more senior or specialized talent than they could individually afford. On the other side of the table, the hired individuals can hedge their professional risk by getting to know a set of early-stage teams and, based on this perspective, picking one to eventually join full time.

Online platforms for collaboration. Collaborative research is on the rise to advance multidisciplinary subjects (consider the rising numbers of coauthors in research publications8). Online platforms for peer-to-peer exchange of expertise and ideas, specific to the needs of the biotech community, are also increasing (Table 4). Such tools as Mendeley (https://www.mendeley.com/), Authorea (https://www.authorea.com/), Academia.edu (https://www.academia.edu/) and Standard Analytics (http://www.standardanalytics.io/) enable collaboration based on sharing and authoring research publications, data visualization (for example, Plotly; https://plot.ly/), data analysis (for example, Benchling; https://benchling.com/) and data archiving (for example, Figshare; https://figshare.zendesk.com/hc/en-us—a service receiving funding from Digital Science of the Holtzbrinck Group, which is also an owner of Springer Nature, the publisher of Nature Biotechnology and Bioentrepreneur). In addition, online platforms, such as ResearchGate (http://www.researchgate.net/) and Synaptic (https://synaptic.bio/), are connecting researchers who share common interests or who have specialized expertise.

Table 4 Emerging funding options
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Financing. Beyond the pitching of biotech concepts to select groups of investors, the landscape for investing in biotech startup companies is also shifting9. Platforms such as the crowd-sourcing site Poliwogg (http://www.poliwogg.com/), FundersClub (https://fundersclub.com/) and AngelList (https://angel.co/) are emerging to facilitate matching of life science companies to accredited individual investors who desire to contribute to medical innovation but would otherwise have limited visibility into available opportunities (Table 4).

Small investments can be especially important when impactful, cost-effective milestones are identified10. In the earliest stage of a project, where there may be insufficient data to attract accredited investors, life science crowdfunding platforms, such as Medstartr (http://www.medstartr.com/) or Dodo Funding (http://dodofunding.com/), allow the general public to support a venture's product validation work with small donations. For funding basic research, Experiment.com (https://experiment.com/) connects scientists directly with donors who receive updates on the progress of the research, and the platform Thinkable (https://thinkable.org/) allows the public to be patrons of research by giving small amounts each month. Such direct, peer-to-peer marketplaces are expanding the pool of capital available for seed- and early-stage life science companies.

The revolution is now

This article has focused on the increasingly important role of sharing in biomedical innovation and commercialization. Many have argued that there are differences between business models for software, which are open, and those for biotech, which are usually closed. Compared with software development, in which online collaboration is common, biotech inventions are often patented and more difficult to replicate and steal, and thus there could be more to gain from sharing experiences and expertise.

To address the centrality of intellectual property in biotech innovation, sharing platforms can be structured in flexible manners and need not be exclusively open or closed. Open and private sharing models (for example, with embargoes on data release that allow patenting) can coexist to promote collaboration while safeguarding intellectual property. Indeed, venture and industry investors often share domain expertise among companies in their accelerators and among their portfolio companies.

The traditional route for biotech innovation limits innovation to a small number of individuals (typically, those with an established reputation or track record) whose ideas are selected by a small number of gatekeepers (that is, traditional venture capitalists). At the same time, more universities are participating in biomedical research and training PhD scientists11,12. These scientists have highly developed expertise but are competing for a small set of traditional academic and industry positions. The sharing model thus presents an opportunity for a larger number of scientists to pursue promising technical concepts funded by novel mechanisms (Box 2). As a result, more ideas with more technical data will have a chance to be vetted for further investment. Ultimately, the biggest winner could be the general public, which benefits from the pursuit of a large number of technical concepts for diagnostics, therapeutics and medical devices.