From Bikes to Lab Benches: The New Sharing Economy and Its Impact on Healthcare

September 3, 2014

Sharing is hard to do.  Be it a simple toy, a prized possession or even, in some cases, just an idea, when we share, we assume risk.  Risk that what we have will be taken, that what we share will be deemed flawed and critiqued, or the risk of losing control.  Yet, to share is unique to the human condition and to our cumulative culture.  We have built our world, layer by layer, upon of a foundation of sharing and emulation.

As taught in pediatrics, the capacity for children to share is expected to emerge at about four years of age.  At this point, children begin the act of sharing as an iterative learning process, in which the new recipient of a toy teaches the former how the toy might also be used; each learning from the other in the process.  Soon thereafter empathy-based sharing becomes expected, where the young child shares with another to experience the joy felt by the recipient, again a uniquely human quality and interaction, and one that drives and tightens our social structures.

Whether on the personal, societal or organizational level, sharing is also grounded in the premise of reciprocity.  The act of sharing involves an expectation of receiving something in exchange, if not immediately, eventually.  Even if the motivation for the act is merely goodwill, sharing depends on recognition.

Today, the asset classes, mediums, languages and currencies of sharing are exploding, to a point where many suggest that we are moving into a “sharing economy” and a world where ownership is highly fractional and consumption is collaborative.  And as we now link sharing with this type of economy we see that financial return becomes embedded in these exchanges.  A useful example of this evolution is found in the software community.  In the earliest days, those opposed to the proprietary and concealed approach being taken by many software companies gave birth to the “free software” movement, led by Richard Stallman.  But “free” in this setting did not mean to imply that these efforts should not involve the exchange of compensation.  Rather, “free” meant to encourage open collaboration on software, working together, with technology, to make society better – using “free” more in the context of “free speech” than in the context of “free lunch.”  In the late 90’s further evolution transformed these efforts into what has resulted in today’s open-source community.

The Rise of the Sharing EconomyWith new technologies to ease market access, engaged social networks to provide evidence of trust, and online transactional infrastructure to support secure payment exchange, today anyone, anywhere can share what they have, for a fee or in exchange for something they desire.  Gone are the days when a “time share” would seem to be an exotic means to vacation in diverse locations.  Today, while you vacation, you can rent your home to others or, better yet, you can elect to rent your home daily and simply share it all the time.  Same goes for the bike, the car, lawnmower, camera, violin, you name it; if you own it, you can share it and be compensated in the process.

When paired with a willingness to offer a related service, you see programs like Uber spring on to the scene, where individuals not only share their car but offer to actually drive you to where you need to be – a system that can provide taxi services at a fraction of the cost required to support a conventional taxi business.  Some of the savings being passed on to the customer, the rest kept to reward the micro-entrepreneur taxi driver.  This type of sharing, so-called “contingent work,” is emerging in many other settings as well.  Now armed with their own equipment, be it IT gear or otherwise, these self-employed sell their services on a fractional basis to a global pool of customers.

Using tools such as Waze, individuals are sharing their precise location and traffic information that, in turn, creates real-time data that was previously unavailable but, through crowd participation, generates a remarkable shared resource.

As I mentioned at the outset of this post, sharing does involve risk; it also requires decision-making.  Historically, both risk and decision-making are more easily processed by individuals than by corporations.  However, this too, is beginning to change; similar to what we see in humans sharing is a learned skill for corporations..

Companies such as Tesla are opening up their IP portfolios to allow others to innovate in ways that may springboard forward the entire electric car industry.  Examples that are resetting the tenants of how best to build proprietary products in ways that track attribution and set new standards on how best to “share” eventual economic benefits.

In the healthcare sector, companies, year-after-year, have invested billions in fixed assets and people, and have collected huge amounts of data.  This has led to the amassing of excesses and underutilized, albeit truly necessary and valuable, resources.  As a global society, we continue to face major healthcare challenges and severe unmet needs.  As industry continues to advance efforts to address these challenges and needs, the cost of drug development continues to rise, while pressure continues to mount to drive efficiencies while accelerating the pace of innovation.  In response to this complex landscape and as a potential solution, more and more attention is being paid to leveraging – i.e. sharing – existing investments in exchange for some form of return.

Still in its nascent stages, so-called “open science” or “collaborative R&D” is taking various shapes and forms, with models in some respect mirroring what we have seen in open-source settings.  For example, talent from big pharma is being made available for externally driven research programs.  Teams are emerging, comprised of start-up or even academic innovators and big company employees, all incentivized to collaborate.  Facilities, like Janssen Labs and Bayer’s CoLaborator, among others, are being retooled to serve as co-located incubators where the remarkable technical resources originally acquired to serve a single company are now shared by many, often on a pay-as-utilized basis.

In addition, the treasure troves of pharma data are being released for open analysis.  Originally collected with a specific set of hypotheses in mind, these detailed datasets may hold priceless clues on the diseases themselves or, in some cases, new ways to understand the drugs that were tested concurrent with their collection.  Hackathons on clinical trial-derived data are another new trend that will be really interesting to follow.

Multiple cross-industry “open science” efforts have popped up in recent years with many more likely to follow suit.  For example, Drugs for Neglected Diseases Initiative (DNDi) advances collaborative R&D projects that bring together the expertise and resources of the international research community, public sector and pharma to focus on neglected tropical diseases that continue to cause significant morbidity and mortality in the developing world.  TransCelerate BioPharma Inc., whose membership is comprised of virtually every big pharma, is a non-profit that is tackling global initiatives such as creating common clinical trial protocol templates, developing clinical trial networks for pediatric and minority populations, and establishing a global investigator registry.  The International Serious Adverse Event Consortium (iSAEC), which is comprised of big pharma companies, the Wellcome Trust, and academic institutions, is focused on identifying DNA-variants useful in understanding the risk of drug-related SAEs.  Another good example is the National Center for Advancing Translational Sciences (NCATS) program at the National Institutes of Health (NIH).  NCATS was established in December 2011 to transform the translational science process so that new treatments and cures for disease can be delivered to patients faster – programs that often rely on late-stage but shelved compounds provided or “shared” by pharma companies.

We’re certain to learn a great deal from observing the success, value and benefits derived from these new “sharing” models and efforts.  Perhaps the most important long-term driver that will motivate continued sharing will be evidence of reciprocity.

Sharing at scale is expensive and involves risk; thus, to be sustainable, sharing must be driven by the promise of a clear return.

Diverse healthcare corporations are beginning to understand the value proposition inherent in these activities.  Having external experts working on projects of shared interests, having globally distributed interdisciplinary talents working on problems that could not be tackled alone, building outcome sharing models that drive and sustain the passion of high-return collaborations are becoming the “new normal,” and offer a sneak peek into a vision of the future healthcare R&D model.  Today, we might share a bike with many; tomorrow, our healthcare solutions will be built in transparent, open source-like communities that are sharing the rewards of their specific and expert contributions – for the ultimate benefit of society.

Next up will be incentives.  Generally it is believed that we elect to do what we care about.  But in what ways do we truly care, and how do incentives and attribution contribute to these choices?