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Yearly Archives: 2015

September 29, 2015 no comments

Spotting Baby Unicorns

Valuing biotech assets, whether an early-stage private investment in a preclinical molecule or a substantial trade in a public stock, is notoriously challenging. Both the length and the complexity of drug development, with multiple parallel risks, are unusual and extreme compared with most other sectors.

 

This multiplicity of risks, leading to high failure rates, has led to the ‘unicorn hunting’ model of biotech investing: searching for billion-dollar winners that deliver an overall investment return, even after paying for all the losers in the portfolio. Which begs the question “what does a baby unicorn look like?”

 

Its easy to suppose that a sufficiently deep understanding of the underlying science and technology would give you a better chance of finding these elusive beasts than the next investor. But sadly, a formula to spot baby unicorns before they grow their eponymous horn, and everyone else can spot them too, is the 21st Century equivalent of alchemy: highly desirably but entirely unobtainable.

 

The flaw in that logic is the assumption that unicorns, like mortal beasts, are defined by their DNA rather than their environment (of course, environment causes variations between individuals, but it is wholly down to DNA that makes a zebra different from a horse). If unicorns developed because of their DNA (that is, factors entirely intrinsic to them) then it would, at least in principle, be possible to identify them as babies. If we had better “DNA sequencers” (metaphor for technological understanding) we would surely be able to spot those unicorns at birth.

 

Unfortunately, though, unicorns are made not born. And the factors that make them are almost entirely environmental. The nature of the technology itself determines the difference between bad and good, but it is outside factors that promote the merely good to great.

 

Consider a molecule in mid-stage clinical development. If the Phase 2 clinical trial reads out negative, it is probably worth nothing (or, at least, it would be if markets were rational – experience with anti-amyloid antibodies for Alzheimer’s Disease among other examples suggests that when the potential win is very large rationality is often suspended). If the trial is clearly positive, though, there is still a wide range of financial returns: whether a trade-sale generates a moderate return or a stellar one will depend mostly on the degree of competition for that asset (be it real or perceived).

 

That competition doesn’t necessarily depend so much on the qualities of the asset itself but on the timing. The feeding-frenzy around therapeutic antibody platforms in the mid-1990s saw stellar deals for average assets as …

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May 20, 2015 comments

The perils of ignoring negative data

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June 2, 2014 no comments

Cometh the saviour? Casting Valeant’s J. Michael Pearson in a new role

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January 23, 2014 no comments

Even odds-on favourites can lose: lessons from the Prosensa story

With the details from the DEMAND-III study, the …

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August 19, 2013 comments

Dendreon proves the risk of investing in “Silver Medal” companies

Once upon a time, getting a drug approved …

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July 29, 2013 comments

An Open and Shut Case: The Madness of the IPO window

As biotech companies queue up like lemmings on …

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July 16, 2013 comments

Incremental innovation lives on

In 2010, DrugBaron declared the death of incremental …

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June 17, 2013 no comments

Ichorcumab: the blood of the gods?

Index Ventures have announced the completion of an …

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June 11, 2013 no comments

Soriot and AstraZeneca face increasing headwinds: can the acquisitions of Omthera and Pearl boost the engine?

The acquisition of Pearl Therapeutics for up to …

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April 8, 2013 no comments

The power of crowds – and their limits

The first internet revolution in the 1990s saw …

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