Ever since Prospect Ventures handed back $150M of committed money to its limited partners, there has been plenty written on the lack of venture capital funding for the life sciences.

However, a deeper dive provides a better picture. Bruce Booth has done the diving, and he wrote a blog post about it.

His findings are similar to what we found when digging up research for a news analysis, scheduled for publication in the December issue of Nature Biotechnology. That piece looks at new funding models for today’s startups, and I’ll get it removed from behind our firewall and post a link on the blog next week, after embargo lifts. Until then, you can read Bruce Booth’s piece here.

Brady Huggett

I read Bruce Booth’s blog, Life Sci VC, when I get the chance, and he’s often lent his skills to Nature Biotechnology. We had him into our offices as part of our Meet the Author series, for example, where he discussed his article on biotech IPOs.

We’ve been cross-posting relevant material from his blog on Trade Secrets, rebuilding the posts from scratch. The truth is, they never look quite as good rebuilt as the do in the original, so I’m providing the link this time. He’s written an interesting piece on funding for early stage biotech. Read it here.

Brady Huggett

Earlier this week the Startup Genome project released a report on the DNA of internet startups. Essentially what attributes lead to success or failure. One of the things they found was that 74% of startups failed because of “premature scaling”. Sounds like an unfortunate medical condition. Its when internet startups build their companies too fast and spend too much money before they really know what they have – their product, customer, market, etc…

While reading it, and my Tech partner Fred Destin’s blog on it, I couldn’t help but think about the issue of premature scaling in life science startups. *Spending too much, growing too fast – not an uncommon characteristic in Biotech. It almost always leads to shareholder pain and a loss of invested capital.

Here are four types of premature scaling (or inappropriate scaling) I can think of in biotech, and we try to avoid them all:

1. Building a Big Science story too fast. This is the “Go big or go bust” strategy with a group of Nobel laureates: raise enormous amounts of capital to fund a novel discovery or research platform without enough evidence of target validation in a disease setting, confidence in chemical (or biological) tractability, progress on a lead program, etc… This generates big teams, big footprints, big stories – and massive burns. If the substance, and in particular the rapid progress on product development, doesn’t get in line quickly, a big gap in valuation emerges that can crush these investments. I can think of a few that are active right now but will leave names out to protect the innocent. The right way to build a Big Science story today involves scaling consistent with a science-led, capital efficient approach: build a sound platform with 15-20 FTEs on modest equity raises, find partners to help offset the growth and validation of that platform, and then grow into the Big Science story as R&D evolves. The wrong way to build these is through rapid scaling around a hype-led fundraising machine. More often than not, investors get burnt with these. Synta is a good rapid scaling example. They have raised and spent $350M, had at one time a team of 150+ FTEs or more, and built a big broad portfolio, but their investors have suffered considerably. Story is far from over, but at the 10-year point its looking tough for the early investors. Sometimes this model works, at least for investors. If the company can achieve escape velocity with enough hype and buzz in the market, they can get public or acquired early. Sirtris is a good example of a high escape velocity ‘big science’ deal that made it pubic and was acquired; its fair to say that many spectators wonder if GSK is regretting its $720M acquisition, but at the time the story had a ton of public relations momentum.

2. Building a big company when it’s really a project. Lots of venture money is wasted building “companies” when they are really just product development vehicles. I covered this theme under a prior blog around new liquidity theses. By stapling multiple programs together, building a big team especially on G&A, and running multiple studies at once, investors often think they’ve diversified their risk. Most of the time they’ve just raised the capital intensity of their deal such that one product bump and the whole thing gets revalued enormously. Big Pharma buys these plays for single programs typically and so if a company is lucky enough to have two winners, say a Phase 2 and preclinical program, they leave real value on the table. If you’ve got an interesting asset, then develop it. But there’s little reason to put the expensive trappings of a bigger company around it. Leverage a part-time group where possible; you probably don’t need a CFO or god forbid an HR person. Focus on lean product development. Stromedix and Zafgen are great examples in our portfolio.

3. Building too fast on back of a partnership. Biotechs often get seduced in premature scaling by the siren song of partnering: they do a big deal on their platform, and then expand their organization and footprint, and try to work on more projects – all increasing their net burn. In short, its often an illusion that the partnership actually brought non-dilutive runway extension to the company. Sadly, when the sugar daddy partner terminates the deal, the biotech is left way out of balance and has to RIF its staff. In the public markets, this has recently happened to Alnylam with Novartis and Targecept with AZ. Its much more painful for private companies with weaker cash positions. This strategy – of aggressively funding internal burn rather than buying runway – can work if the company is lucky enough to develop some interesting assets with the free cash from their partner. But there’s alot of luck involved (true of all of biotech, I guess). The alternative is to truly scale your organization to the partnership. Vitae has managed this reasonably well. It last raised equity in 2004, and has used its pair of deals with Boeringher to extend its runway while selectively advancing internal projects. Plexxikon was similarly successful; hadn’t raised equity for years before it was bought for >$800M by Daiichi.

4. Building out before a big outcome. Drug approval, for instance. In Big Pharma, having product to sell into the channel the day after approval is the goal for most blockbusters; in the event of a CRL rejection, they can eat the costs. But in cash-strapped biotech, this tends not to work. Small companies that build out aggressively before an approval more often than not get crushed. Vicuron a few years back. Adolor. ARCA. All hired sales reps prior to a pending approval, failed to get approval, and had to RIF large numbers of their employees. This is not only tragic for those sales folks, but it also exacts a huge tax on the capital intensity of these businesses (especially the small ones). Hubris and excessive optimism are the typical causes of this one, but sadly Boards still let this happen. Horizon Pharma *recently did it right – kept the company under 20 FTEs through approval of its new drug Duexa in April 2011. Its now public and working on the sales & marketing organization.

The counterpoint to premature scaling is what we at Atlas coined P/B/S. Its not Phosphate Buffered Saline. It’s Prove/Build/Scale. Thinking through small bets to prove a hypothesis, slightly more to test the programs, when to spend to grow a company, etc… Most of our seed investing is done to Prove concepts. Building requires partners (which is where we often exit). And scaling requires functioning capital markets so rarely happens today.

Premature scaling can kill companies and investments. Worth keeping that in mind for the next budget cycle.

Reposted with permission from the LifeSciVC blog.

Bruce Booth

I thought I’d tackle the question of what are the actual return distributions of venture capital investments in biotech startups (e.g., how many losers, how many winners) to set some context.

As a community, we’re full of faith-based believers in the biotech startup world – we all always believe the next one we start or invest in is going to be the big win. Along with that optimism, there’s a ton of mythology out there about which venture-backed biotech deals drove 20x returns, mostly nostalgic for the 1980-1990s. “Raise as much as you can, when you can” and other untrue axioms became dogma during those days. Lots of snippets of anecdotal evidence and hand-waving don’t overcome the reality though.

Gary Pisano at Harvard has written a good deal on overall public biotech returns and the sector’s underperformance, in part due to the certainty of scientific uncertainty. But on the private biotech side, we’re all so protective of specific deal returns and often bound by confidentiality, very little actually gets public. I’ve not seen a good piece of literature on venture-backed biotech distributions so I’ve done a quick-n-dirty analysis and compiled it with some Cambridge Associates data that Pete Mooradian helped provide me with.

To get to a credible dataset, I looked at 270+ biotechs formed between 1996-2003 and the amount they raised, and then made some simplifying assumptions to get to guesstimate multiples on invested capital (ignored liquidation preferences, step-ups or down-rounds, common holdings). It’s by no means a comprehensive review. But what reassures me is that it’s in the ballpark and nearly perfectly traces Cambridge Associates data. They tracked over 1600 individual biotechs from the year of first investment and the returns. As you can see below, the curves almost totally overlap.

Some conclusions:

■As if we needed to be reminded of this, roughly half of venture-backed biotech’s lose money. The total losses for the recent cohort are over-estimated as I didn’t have the detailed data on salvage values, but both sets of data have about 50% with a loss of capital.

■Real winners above 5x make up about 12-15% of biotech deals. So roughly 1 out of 6-8 deals. Not a bad hit rate.

■The failure rate hasn’t changed much. See the chart below. While the post-bubble 2000′s have had slightly higher failure rate, the 1990s were nearly as bad. The curve for the recent vintage is slightly up-shifted but not sure how statistically relevant that is. [What has probably changed, and I don’t have the data here, is that the winners in the 1990s were more likely to be above 10x invested capital, whereas today that’s a far less common experience. We’re trying to change that, but the numbers are what they are.]

An obvious question then arises – what are the characteristics of the outlier returns in the top two deciles? The biggest driver I can tell is the inverse correlation between capital intensity and returns. If you can achieve a successful exit and still spend less equity capital, you’re likely to generate a much better return. Seems intuitive to some degree, but only if you assume that the exit values are largely capped. Reality in biotech is most “successful” exits are in the $200-500M range, despite the occasional outlier like the recent Plexxikon deal. Raising $150M+ in equity capital to get there isn’t so interesting. Raising $15-30M on the other hand…. But this cap on returns with capital intensity isn’t always the rule on the Tech side of the venture business. It is for some (like capital equipment plays, semi’s, etc..), but many number of their business models can just keep scaling. Facebook and Groupon have all raised a ton, but are worth gazillions more than that now. Biotech just isn’t scalable over the same time horizons as Info Tech. I won’t belabor the topic here, or go through the analytics, but if you’re interested it’s a prior article in Nature Biotech.

I think there are a few implications for early stage biotech investment strategies:

1.Be conscious of gravity. Within the existing set of business models, failure rates have been a relative constant like gravity, given the reasonably unchanged 20 year hit rate. Investors should assume half their biotech deals will fail, and 15% are real hits; and entrepreneurs should at least know the odds. Channeling more capital to the 15% and less to the 50% is a key to success.

2.We’ve got to do something radically different to change the model. Everyone says biotech takes a lot of money because its “regulated drug development” etc… We need to figure out how to do it differently, while improving the odds that winners emerge with more limited capital. We’re experimenting with ultra-virtual models, tighter links with pharma, deeper academic links, new corporate structures, etc… (Lots of good substrate for blog posts in the future).

3.Improve the existing models. If #2 doesn’t work and we’ve got to keep building bricks-and-mortar biotech companies, we need to figure out how to live with the gravity of #1 by spending less equity capital to get to the “no-go” decision and shut down unsuccessful deals. Use other sources of capital like partnering dollars. Kill the losers fast, as often as required, and hopefully cheaply. And try to preserve a large piece of your winners so you can invest more in them.

In some ways, successful early stage biotech venture investing today is all about balancing a portfolio between smarter approaches to the realities of gravity and an appreciation of new potentially ‘zero gravity’ virtual worlds.

Hence the subtitle of my blog. A biotech optimist fighting gravity.

Reposted with permission from the LifeSciVC blog.

Bruce Booth