Drug Baron

February 28, 2013
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Venture Capital 2.0

Innovation is the life-blood of venture capital.  Whether the innovation is in marketing, business model or the product itself, the principle of venture funding is to identify that novel spark that disrupts markets and delivers supra-normal returns – albeit accompanied by abnormally high risk.

But for an industry focused on innovation, the business model of a typical venture fund has remained remarkably consistent for more than a generation.  The majority of funds today, and for the last several decades, raised a fixed term fund, charge a management fee off the top, and then find exciting portfolio companies to invest in and earn a percentage of the upside that they generate.

Asset-centric investing is only the first step on a road to improved returns for life science investors

Not only is the model pervasive, but the “2 and 20” formula, referring to the 2% management fee and 20% carried interest, has also stood the test of time.  For a limited partner seeking to invest in another venture fund, there is plenty of competition in terms of track record of the fund management but remarkably little in terms of the basic business model behind the funds.

Given the performance of the sector as a whole – across life sciences and tech the median funds scarcely return the money invested after accounting for the management fee – one is forced to ask if there is a better solution.

DrugBaron asks whether the shift to asset-centric investing pioneered at Index Ventures might actually be the foundation for yet more innovation in the venture capital business model, yielding a step-change in returns for all concerned.  Looking into the crystal ball reveals VC funds that look very different to many alive today.

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February 11, 2013
by admin
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The Primacy of Statistics: In defense of the pivotal Phase 3 Clinical Trial

Statistics have always had a bad press.  Ever since Disraeli’s supposed utterance “lies, damn lies and statistics” the public have treated any claim based on statistical analysis with appropriate caution.  But if it is indeed true that statistics can be used (or more likely abused) to ‘prove’ almost anything, it is equally true that without proper use of statistics almost nothing can be considered proven.

When it comes to drugs, that means comparing the response in the treated group with a placebo group to determine whether a given treatment has had any effect at all in that particular patient population.

With the rise in personalized medicine (the sound concept that what works for one patient may not work for the next), this well-accepted paradigm has started to face challenges – not least from patients brought up with a healthy dose of skepticism for statistics.  Looking at the trial data, there always seems to be a proportion of the people who seemed to respond very well to the drug – even if, on average, the improvement was not statistically significant.

Inebriated by the principle of personalization, patients and advocacy groups are quick to demand access to such a drug that can provide benefit for a subset of the patients in the trial.  But that conveniently forgets the purpose of statistics – the aggregation of data from lots of individuals so as to eliminate the operation of chance.

In an untreated population, some people get better and some people get worse over a given time interval.  Statistics determines how like it is that people getting treated did, on average, better than those who were untreated.

Assuming that anyone receiving a drug who is better at then end of the trial than they were before (without reference to a control population) has benefited from the treatment is very dangerous (if entirely understandable for the patient themselves and those who care about them).  Unless the difference is statistically significant, the supposed benefit is as likely to be due to chance than the costly drug.

Statistics are our only barrier of defense against old-fashioned quackery – where anecdotal evidence, powerful marketing and advocacy, rather than solid scientific data, are the basis for adopting new medicines

Of course, clinical trials can be (and often are) badly designed – looking at the wrong patient population or the wrong end-point.  That is the fault of the drug developer, not infrequently aided and abetted in their folly by the regulators.  Making such mistakes lets down the very people we are trying to help (as well as the investors in those companies). But we must not try to make up for those errors by undermining the primacy of the statistically significant clinical trial as the only acceptable metric for efficacy.

Dredging through the data of a failed trial to find subsets of ‘responders’ is becoming a favorite pastime.  Drug companies are doing it in Phase 2 data, and progressing drugs into vast and expensive Phase 3 trials that are doomed to fail. Patient advocacy groups are doing it to Phase 3 data to plead for the approval (and sale) of drugs that more than likely do not work at all (often with the full support of the owner of the drug who would love to be able to sell their product).

Statisticians of the world must unite, rise up and find a voice to halt this madness.

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January 29, 2013
by admin
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The REAL scandal of drug pricing

Healthcare provision, at least in the Western world, is in a permanent state of turmoil, as costs rise inexorably and politicians search for ways to cut spending without angering voters.

But why do costs keep on rising so steeply?

High priced drugs often get the blame.  After all, every time new medicines come on line that treat something that was previously untreatable that can only ratchet costs up (albeit taking the health of the population to new levels).  The spotlight has been firmly on this upward cost pressure with the launch of orphan drugs Gattex™ and Kalydeco™, with price tags around $300,000 per year for each patient.

But drug prices do not always rise.  As atorvastatin became generic at the end of 2011, a $10billion per annum market for Pfizer’s Lipitor™ (the only available source of atorvastatin during the period of market exclusivity) almost disappeared overnight – translating virtually directly into savings for healthcare providers.

So why do these competing trends always seem to result in rising drug bills? Are the high-priced drugs really to blame?

Only by tackling the REAL scandal in drug pricing – the unearned premium – do we stand any chance of stemming the haemorraging healthcare budget

DrugBaron examines the real reason why drug prices remain stubbornly high, despite a decade of relatively poor productivity in pharmaceutical R&D.  The focus should be on prices paid for high-volume proprietary drugs that offer little incremental value over generics, or – most scandalous of all – in replacing branded drugs with generic equivalents wherever the opportunity exists.

Paying a premium for something that’s scarcely superior (or even identical) – what DrugBaron calls the “unearned premium” – is the REAL scandal in the drugs bill, and not the high, but justifiable, prices for drugs like Kalydeco™.  Politicians, driven on by a baying public, need to be careful not to jump on the bandwagon and cut the highest prices, threatening to once again ‘orphan’ those with rare diseases, while leaving untackled the real flaws in the system.

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