Biotech Models: Virtual Reality vs Virtual Mythology

Posted in Capital efficiency, New business models

Virtual research-stage biotechs seem to be all the rage these days.  And they do offer interesting investment theses in some settings and with particular assets.  But there are a bunch of myths about going virtual that deserve attention.

But before going into a few of those, some definitions.  From my vantage point, “virtual biotechs” are ones without labs and with lean internal staffs that rely on external collaborators for the “wet” lab work.  Clinical-stage virtual biotechs have been around for a decade, and have had a lot of success.  As the ecosystem of early stage CROs and collaborators has matured, its become increasingly viable to “go virtual” in drug discovery and early development.  That’s the focus the myths below

 “Innovation can’t happen” Myth.  I’ve often heard critics of virtual companies claim you can’t do innovative work virtually; based on lots of data points, this certainly isn’t the case.  Fundamentally there are different types of innovation that are more (or less) amenable to virtual models, but lots of room to create novel, high value discoveries.  Working on poorly validated biological pathways is probably a bad place to go virtual.  If you need significant bespoke cell-based assays or animal model development, its probably not a great fit.  But drug discovery against hot, and preclinically validated targets where the gold standard animal models of disease are relevant and accessible, or where phenotypic or pathway-based cellular assays are available, can make for very tractable virtual drug discovery, providing your internal team includes experienced drug hunters.  Generating differentiated chemistry against well-known targets is very much in scope, though the competitive bar may be much higher  In some ways, it all comes down to subtle differences in the type of innovation and how value is captured from it.  If the business model is to sell assets (drug candidates), virtual can work.  If there’s a proprietary platform with a special sauce or new drug modality, it becomes harder to do that virtually.  But even there, the virtualization toolbox can be accessed for non-core activities.

“Its cheaper” Myth.  Reality is in many cases the direct R&D costs aren’t cheaper. They can be, and in aggregate the project’s costs are often less, but it truly depends on the experimental challenges.  Much of the benefit comes from having variable costs that can be dialed up to tackle problems quickly (and then back down), rather than fixed internal team and lab costs.  And certianly G&A organization costs are much less. A corollary to this myth is the “Its cheaper in China” myth.  Some things are cheaper, like chemistry (though prices are increasing fast), but others – like specialty preclinical models – are frequently as expensive offshore as here in US with focused vendors.  Furthermore, the logistical and ‘frictional’ cost of import-export into China, such as accessing reagents in a timely fashion, can take a toll of productivity.  For many virtual teams, there’s highly valuable know-how their networks and in the working knowledge around which vendors to use, where, for what, and at what price.  Optimizing the triad of cost, time, and quality with different external labs is more art than science and takes well-connected, experienced people.

The “Lower quality” Myth.  If you are throwing your project over a wall to a partner, how can one be assured of the quality – or so the criticism goes.  This is a big concern when entering partnering discussions as a virtual company; will Pharma trust the data if they can’t see it in your lab notebook?  But just like an internal project, this quality argument depends on who is working on it.  In our experience, often the quality is higher because our teams go to the best-of-breed external partners who don’t have to ‘learn’ a specific assay or model.  Audited study reports from drug discovery partners are increasingly accepted today, just as external toxicology reports have clearly been the norm for years.

“My Team is Under-Leveraged” Myth.  Many prospective CEOs worry that in a virtual team where there’s only half-a-dozen or fewer employees, that they’ll be under-leveraged.  I can think of a few instances where this is the case, but in most circumstances I don’t think its true.  For sure, an executive’s bandwidth is no longer consumed with things like HR meetings, governance committees, etc… – so it may feel different.  But it actually means an executive spends more time on managing issues around the science, medicine, and problem-solving (rather than crisis management).  This may be why in most cases virtual companies are led by scientists.  In single asset companies, the risk of under-utilization of the team is obviously far greater than in multi-asset companies, but even in the former its possible to structure part-time relationships to enable talent diversification.  Most of our virtual startups have significant amounts of fractional FTE commitments from part-time domain experts, not only with regard to some scientific lines like toxicology but certainly finance and HR as well.  The other thing to note about teams is that everyone wears multiple hats, and needs to be comfortable telescoping from 60K into the minutiae of a project and back.  A CEO is also often the janitor, and the ability of the CSO to make a great cup of coffee is part of the job description.

“Its lonely discussing with yourself” Myth.  Without a larger organization to bounce ideas of off, this myth says that a virtual company will suffer from not having the creative debate and office idea spontaneity.  While the water-cooler may be far less crowded, the virtual companies we know well find ways to mix it up with far more people than most conventional biotechs.  Success for a virtual company depends on bringing a lot of great thinkers together frequently to champion and challenge the project, across science, medicine, finance, business development, etc…  Tom Hughes at Zafgen has noted that his “circle” of people that he interacts with on our obesity program is far bigger and more diverse than it was in his prior Pharma role (where 90% of his time for years was spent in meetings with the same ~100 people).  And since almost all of the inputs come from external supposedly objective people, the internal bias common in conventional biotechs of drinking your own Koolaid is often less likely to occur.

Virtual biotechs aren’t easy and are fraught with challenges.  Fire drills can be costly, as teams are too small and spread across tasks to withstand too many alarms at once. Further, there might not be anyone in-house with the right expertise.  Since there’s a huge reliance on external CROs, there’s also the “Trust but verify” challenge: making sure CROs are being good stewards of your science and your dollars. But on the whole, with the right type of project and right team configuration, they can make for very lean startups and efficient value creation.

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  • http://twitter.com/sciencescanner David Grainger

    The biggest challenge to being a virtual VC (says the CSO of a virtual biotech, who ought to know!) is being an expert customer for CROs across such a wide range of disciplines.

    One solution is to bring in experts for as long as you need them inside the company to make sure they can properly monitor the CRO in their domain.  They can ask all the difficult questions, they can sniff out where the CRO is cutting corners, they can check the reports coming out are not pulling the wool over the customers eyes.  If you have the right people to help you, this model can ensure quality even when you are out-sourcing all your R&D.

    BUT there is a snag.  It means that virtual biotechs have a bigger need for senior management than an organisation with an in-house team.  The key to a virtual biotech is to have a cadre of senior people with drug development exercise across the whole gamut of areas you expect to need to operate in.  By contrast, an experienced internal development team can be managed by a skeleton senior team.  The practical impact?  The management overheads look higher as a percentage of the total spend in a virtual company than in a “real” one.  On the face of it, that seems odd – how can you need a bigger management team when there isn’t a team to manage?

    As a result, VCs – particularly those who have not gone the virtual route before – tend to baulk at a business plan loaded with senior management (and with overheads that might be 30% of total spend).  Benchmarrked against the ‘real’ companies they have worked with before, the overheads look gold-plated.  But as DrugBaron noted previously (http://www.tcpinnovations.com/drugbaron/?p=28) having such a team is the sine qua non for success in the virtual model.

    Making a success of the virtual company, then critically depends on the management team having the experience of working in virtual mode, and being large enough to have INSIDE the company the core expertise needed to be an expert customer across the whole range of disciplines required.  Management teams who don’t see that need not apply – and VCs that don’t understand should stick to financing “real” companies.

  • KE Merten

    Great post as usual Bruce.  I love your support of the virtual model!  To your first point and in my own experience, the basic understanding and maturity of the asset or target at company inception is key.  Virtual D (development) is highly practical and capital efficient.  Virtual R (research) on the other hand is quite the opposite.

  • Anonymous

    Agree on Dev-stage virtual companies but we have also seen plenty of success with research/discovery virtual company examples recently, such as our very own Nimbus Discovery (www.nimbusdiscovery.com)

  • Anonymous

    Thanks David. Certainly agree in principle that the core team in a virtual company need to be seasoned veterans of R&D – a very important ingredient for success

  • Lance Stewart

    Bruce, I’m glad you wrote on this topic !  In my view, the Virtual Research model, enabled in part by modern communication tools, is one of the most exciting modes of new IP generation and will be a powerful force for new drug discovery EVEN in areas of new biology.  

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