NIH to repurpose failed leads?

According to the WSJ, NIH Director Francis Collins is pursuing a role for the NIH in dusting off and repurposing failed pharma leads.

(Let's call them "shelved" leads instead of the pejorative "failed." Some of the leads just lacked the organization will, expertise, or budget necessary to justify the risk of further investment.)

I find Collins' idea VERY interesting for a few reasons:

- this seems like a good role for government DD investment - the NIH can provide some very worthwhile assets & expertise, especially as leads may be repurposed from one disease class to another. (say, cancer to allergy application.) No pharma company has the breadth of expertise that the NIH does across their Institutes.

- this looks like a high leverage role for the NIH - theoretically, a small incremental investment in a shelved lead that is already proven safe in humans could have a HUGE return. However, the nature of the quest says that there will be ALOT of failure along the way, so much failure that pursuit of this mission by the private sector isn't economical.

-Politics: Any clinical success can make the NIH's mission more tangible to those who fund the NIH. The NIH does some great research, but since it is heavily biased towards early, basic research, not a lot of it can be used as a 'trophy' to gain more funding. Also, from the NIH perspective, a "win" from repurposing can come a lot sooner than a "win" from de novo drug discovery by NCATS, and by the nature of the repurposing work, the NIH can't step on any toes. If a pharma has shelved a program, how can they object to the NIH building off their earlier work? (I think we all know how pharma execs run from failed programs like cockroaches when the lights are turned on.)

-Also, while I'm not in love with the idea of the NIH taking a formal role in translational research, this seems like a smart way to dip a toe into drug discovery. Perhaps the NIH's DD experience to come from repurposing will help improve the DD regulatory process.

The devil is in the details, and in this case, it's the IP. What happens if a chemical patented by Company A for Disease X is found to be effective in Disease Y? Who owns the resulting IPR? There's no shortage of failed/shelved leads for the NIH to consider, so might they only pursue leads off patent or nearly off-patent?

The only question that I'd ask the NIH is "why does the NIH believe they have a higher probability of success with the "shelved" leads than the originating pharma team?" I can think of a few reasons, but I'd like to hear their rationale from them.

biotech VC economics illustrated

HIG announced that they've raised another $268M fund to support drug development investments. (Congrats to them - the squeeze is on in VC, and most believe that VC limited partners are likely to concentrate their investments in 'survivor' VC funds. In other words, it's survival of the fittest, and having a number of LPs in follow-on funds means HIG is fit.)

Separate, Amgen announced the acquisition of KAI Pharma for $315M. (Congrats to them, as well.)

Seeing these two unrelated transactions, I wondered how many KAIs does HIG have to create to provide a worthwhile return to their LPs. (This is intended as general analysis, unrelated to HIG or KAI's specific performance or history, except that I'm using their numbers & press releases as representative of their industries.)

First, a bit about HIG's fund: according to the press release, the fund will support HIG's investment in 12-15 companies, with each investment to receive up to $20M, and liquidity targeted 4-6 years post-investment.

KAI, meanwhile, was launched in 2002, and has received $63M in venture funding over 10 years. So, using really simple terms, KAI generated a 5X return, or (on average) a 17% annual return. (This very simple analysis ignores the fact that the $63M invested in KAI was made a different times and valuations, and that some of the KAI equity is held by employees, not investors. You could assume that employee ownership was ~10% of the shares, but these are certainly common shares, vs. preferred for investors, meaning only that all of my figures could vary if you knew specifics of the KAI story.)

Any biotech that creates liquidity in excess of invested capital is automatically in the top half of all bioventure investments, but unfortunately, the 17% annual return is likely no better than half of the investors' expectations. There's some debate about what the discount rate should be for an early stage biotech - I've always used 40% at a minimum, so would argue this could be lower, particularly for later stage private investments. LP expectations for a biotech fund is for fund returns somewhere in the 20-30% (annual) range overall, which is the net of some positive returns and unfortunately some number of absolute failures.

Using 40% as the target IRR, and six years as HIG's average time to liquidity, the average new HIG investment would need to generate a 7.5X return in 6 years (40% annual IRR.) Overall, HIG needs to turn $268M into ~$2B in 6 years, though more and sooner would always be appreciated by the LPs.

So let's say that HIG funds 13 investments from this fund, and results are distributed as such:

4 x complete duds x $13M avg investment, zero return
4 x small return on original capital x $18M investment, 2X return
4 x modest return x $18M investment, 5X return (roughly equal to KAI's outcome.)
3 x big wins x $23M investment, 20X ROI

Here's what the total fund value becomes with these assumptions:

You can argue with my distribution of investments and ROIs (every VC would), but I've played with the numbers, and can't make it work - I can't come up with a plausible macro scenario for a drug development investor to turn $268M into ~$2B.

(One other observation: this analysis confirms the notion that VC fund success or failure is determined by the amount and magnitude of the big winners. One more or less 'big wins' makes the VC fund either a screaming success or honking failure.)

I tried one other approach to validate the VC drug development model: it is widely stated by Windhover that an anti-cancer compound in Phase 1 trials is worth ~ $100M. Assuming a cost of $5M per program from discovery to Phase 1, HIG would need to generate 20 of these programs, and they'd have enough capital to support ~40 targeted tries (after accounting for the friction of fund salaries, overhead at portfolio companies, etc.) Is there any reason to believe that HIG (or any other VC firm) could bat .500 in their attempts to generate phase 1 programs?

I'd disagree with any program IND success rate expectation of >25%, so my answer is no, though you could convince me that through the use of outsourcing maybe you could get the cost/program down from $5M, thus, reducing the required success rate.


In short, I can't see how the traditional biotech VC model could work, without abnormal success in portfolio companies or sooner or greater liquidity for portfolio companies. I'd say that KAI and other bioventures that have reached liquidity like Plexxikon - while representing above average success relative to the industry, show that the VC model is busted. (In biotech at least.)

I don't think this is a product of macro trends (Sarbox, competition from generics, medicare price cuts, etc.) but rather a by-product of the inefficiency of early stage drug discovery. For example, much of the earliest stage lead discovery is best described as a shotgun approach rather than rifle shots. Part of this is driven by how hard and imprecise drug discovery is, and partially by asset investment (if you spend millions on an HTS lab, you're biased towards quantity over quality).


postscript: just a reminder that this analysis isn't intended as a critique of HIG or KAI. I'm just using their #'s to illustrate.

ex-Pfizer R&D head vs. bank analyst on drug discovery strategy: who ya got?

Forbes magazine unintentionally hosted a good drug discovery strategy debate. It started with a prominent pharma industry bank analyst Jack Scannell critiquing therapeutic R&D productivity. His points: 1) targeted drug development has been less productive than other approaches, and 2) high-throughput R&D technologies really haven't been productive either.

John LaMattina, formerly Pfizer's head of R&D fired back, also in Forbes ("Analysts get it wrong again"), which attributes lower R&D productivity to.........pharma mergers and more demanding regulators and payors. (Never mind that increasing R&D productivity has been the rationale for much of the industry consolidation.)

Both make good points, though. HTS and genomic technologies have definitely under-delivered. But, while the industry in the early days of HTS and genomics truly WAS guilty of treating drug discovery as a numbers game, researchers have become much smarter more efficient in their use of these technologies. (Whereas some R&D centers initially built labs to maximize compounds screened per day ("100,000 per day capacity!"), most are using HTS (and other technologies) to more inexpensively examine smaller focused libraries.)

Note: neither side cites budgets (neither pharma nor NIH) as an inhibitor of R&D productivity.

Scannell says that the numbers don't lie - 33 of the 50 first in class drugs studied started from a phenotypic-centric philosophy, but LaMattina counters that this is explained by the lag inherent with tech adoption, and that a wave of targeted compounds is on the horizon.

This is tough analysis to choose a side on - I think the phenotypic approach has been the benefit of low-hanging fruit (i.e. development to date has benefitted from easy molecules, but there aren't nearly as many easy ones left), while the targeted approach just has an inherent intellectual appeal. ("If we know what causes disease "X," why not just target it?")

(That being said, one of the more significant tech flops of the last decade or so has been "Rational Drug Design.")

I'd also nominate one other reason for low R&D productivity not mentioned by Scannell or LaMattina: organization structure. Innovation becomes the exception and not the rule as organizations grow bigger, while risk tolerance seems to decline. That bigger organizations stifle drug development is reinforced by the notion that many of the successful therapeutic programs were once considered UNsuccessful programs, as LaMattina's story of the invention of Viagra indicates. Another reinforcing story is that of Gleevec's development from Daniel Vasella's book: only the singular efforts, passion,  and strength of Dr. Brian Druker kept a Novartis committee from killing off the lead that became known as Gleevec.

Let's hope that pharma R&D rises soon, whether because pharma mergers have slowed, or because productivity is catching up with the technology.

More on Warp Drive Bio

I analyzed the Warp Drive Bio (WDB) launch here (Warp Drive launched with a stunning $125M in financing.)

Even better,  BioIT World has more detail on Warp Drive Bio, including an interview with the CEO.

Interesting to see that the 'put' of WDB to Sanofi is actually formally agreed to - hit certain milestones, and Sanofi has to pay a pre-determined price, so there's more risk on Sanofi's part that I assumed was being carried by the VCs.

Either directly or indirectly, this results in reduced risk for Sanofi, the VCs, and WDB company management - a win all-around - pretty smart. Consider:

-WDB & company management doesn't have as much financing risk as most biotech's - they can concentrate on discovery productivity, instead of chasing next round financing.

-VCs get a liquidity put. There's even less downside, as VC's are providing less than 100% of the start-up capital. (Assuming more than the VC's $75M was required to launch.)

-Sanofi gets exclusive (I assume) access to a novel technology platform, gets R&D expenses off of their income statement, and locks in discovery productivity and the cost of acquiring WDB technology at 2012 prices. As long as SNY's R&D agenda is matched by WDB's, and the value of leads does not go down, this is great.


I think most VCs and company executives would LOVE to do this sort of deal, especially at company founding, but pharma's aversion to risk prohibits most deals of this sort. Big Pharma's usual game plan is to wait to see more data, as they would rather trade potential financial upside for reduced product or program risk. Let's hope that this deal represents Big Pharma's willingness to take a little more risk, especially when a company at start-up has such a great pedigree.


Besides the novel Sanofi partnership, WDB has a very traditional lead discovery value proposition  - their expectation is that their technology platform will generate novel lead compounds quicker/better/or more efficiently.

I'm in no positon to evaluate the technology, but from a business strategy perspective, it is another example of over-valuing lead discovery. (That is, if you believe as I do that preclinical leads are over-valued.)

Consider the typical drug discovery & development timeline, as put forth in Nature:

WDB's value proposition affects only the first two years of the timeline (up to lead selection.) Presumably WDB is more efficient (either in time or cost) during the early stage. Let's say they're 25% more efficient in terms of time, which equates to 6 less months of development over 8 years, assuming that the drugs have the same downstream risks of other R&D programs. (i.e. a WDB-sourced lead is just as likely to succeed in Phase II as any other pharma lead.)

The net effect is WDB's entire discovery advantage is in 1/16th of the total effort required to produce a drug, and does not seem to impact the probability of success. Sure, there's financial value in getting a product to market 6 months earlier, but bringing $250M in revenue forward by six months 7.5 years from now is only worth $31M in present value (25% WACC, 30% OPM).

The same $31M in NPV could be generated just by increasing the probability of a programs success by a small amount. (In other words, quality over quantity.)

For this reason, I'm a fan of investing not in more early leads, but rather any IND leads or technologies, especially if I'm a risk-averse pharma.

Thoughts? Reactions?