Will New Business Models Enhance or Endanger Drug Discovery?
Stewart Lyman2/16/12
The most successful biotechs of the past quarter century have been companies that established relatively large, cutting edge research programs, such as Biogen, Immunex, and Genentech. I’ll refer to this as the B.I.G. model. These companies were able to hire young, innovative scientists by promising them a certain degree of intellectual freedom to pursue research projects and build their reputations on the results. While these researchers were well compensated financially for their efforts, I don’t know of a single one who signed on for the money. Their true reward: the ability to make ground-breaking scientific discoveries, publish and present their data in prestigious journals and conferences, and help turn them into breakthrough medicines for treating serious medical problems.
The current VC mantra says that this approach is now outdated, a relic from a time when the sauropods ruled biotech. Investors won’t tolerate a lengthy wait to receive a return on their investment. As a result, biotech business models are unsettled and in flux. The days when startups hoped to become stand alone, vertically integrated drug sellers are clearly on the wane (with a few exceptions). Virtual companies and smaller, focused businesses represent the current flavor-of-the-month for many investors. A senior venture capitalist in Seattle recently stated “For a long time, we in the venture business created the wrong companies for [big companies] to buy. We’d build something with 150 employees and four projects, when what they want are 25 people and one project.”
You can see where this train is heading. VCs (at least the ones that subscribe to this idea) are going to be creating lots of these small, single project startups. While this new model may generate good financial returns for VCs, is there much data to support the idea that this approach will succeed in generating new and useful drugs? Will it siphon money away from other approaches? What effect will adopting this model have on the biotech ecosystem?
An ecosystem is generally defined as a group of interacting organisms and the environment in which they function together. Alterations to one small part of an ecosystem can have detrimental, disproportionate effects that spread across the environment. The field of biology provides numerous examples where a potential solution to an ecological problem resulted in an even bigger predicament. For example, the deliberate introduction of foreign species in Australia, such as rabbits or cane toads, each produced serious environmental repercussions that did not resolve, and in fact worsened, the troubles that they were intended to remedy. The accidental introduction of pythons into the Florida Everglades appears to be wiping out the resident mammal species. The study of ecosystems is not limited to the field of biology, and can provide insights into a number of different disciplines.
The biotech ecosystem includes investors, patent agents, scientists, patients, doctors, and regulators, all of whom interact in a resource-limited, financially constrained healthcare environment. Each of these elements is critically important to its overall success. In an ideal setting this ecosystem is sustainable and produces strong financial returns, a significant number of jobs, and, most importantly, a substantial number of unique, quality medicines that result in enhanced patient health. However, many things can go wrong. Not attracting enough investment dollars will put you out of business. Choose the wrong drug target, come up with a molecule that’s too toxic, or fall short of recruiting enough patients for your clinical trials and you will go bankrupt. Present incomplete or bad data to the regulatory agencies, and your development program will flame out.
Some resources, such as drug targets, are unique to this ecosystem, but others, such as investment capital, are shared with many others. Within the larger financial ecosystem, there is significant competition for dollars. From a financial return perspective, many other ecosystems have an apparent big advantage over biotech. For example, software development projects generally have much lower costs, require fewer people, can be completed in shorter time frames, and are not impeded by government regulatory requirements. The relative advantages of these other ecosystems have been touted as a major reason why investing in biotech has dropped disproportionately in recent years. The virtual model may be a response to these investing inequities.
The primary goal of venture capitalists, of course, is to invest in companies that can be liquidated (via acquisition or IPO) for a significant return in a relatively short period of time. Is there any data to indicate that drugs originated by a small company, working on a single project, are as (or more) likely to be successful than medicines arising from a larger, more diverse firm? Put another way, is there a correlation between the size of a company that produces a drug candidate and the probability that the medicine will make it to market? It’s a complex question, since the ultimate fate of a drug candidate will depend heavily on the skill set of the acquiring company. The outcomes associated with Big Pharma’s interventions are unpredictable. They may screw up the development of potentially good drugs, or successfully resuscitate marginal ones.
Small companies, in theory, can work on drugs with less revenue potential because they require lower revenues to fund operations. That assumes, of course, that these companies intend to take the drug all the way through development and keep it as an asset. Virtual companies can work on drugs suitable for a wide range of markets since they harbor no illusions of staying in business for the long haul. Still, questions remain. Will contract workers perform with the same passion as those who are directly invested in the success of a new drug? Can remote oversight substitute for walking down the hall to get your questions answered?
Virtual companies that outsource many traditional in-house functions, such as research and clinical trials, are currently fashionable. Their fates will be determined by several factors. First, their skills in identifying and obtaining a worthwhile drug candidate from the corridors of academia or the Big Pharma discard pile. Secondly, they need to find high quality contract organizations to do much of the heavy lifting work prior to acquisition. What happens if the drugs produced by these small, 25 person companies don’t pan out for the Big Pharma companies that buy them? The VCs won’t be feeling the pain (at least in the short term) as they will have already pocketed their money and eased on down the road.
Morgan Stanley suggested that Big Pharma’s current ability to discover their own drugs was so lackluster that that they should switch their primary focus to alliances and acquisitions. Although productivity across the industry varies widely (as measured on a “number of new drugs per R&D dollars spent” basis), I don’t know of a single company that bought in to this idea. GSK claims good results from an initial review of their experimental Drug Performance Unit approach, but the data hasn’t been made public and the program has yet to reach the point of actually producing useful drugs. I expect the success rate will be quite variable among Big Pharma companies in choosing which small biotechs they acquire for new drug leads. It’s too early to determine if this selection process will produce better or worse results than their current efforts to create drugs in-house.
Big Pharma will buy any company if they value it sufficiently, although their vetting process for both drug acquisitions and internal candidates often leaves plenty of room for improvement. The pharmaceutical industry’s front yard is littered with the chemical and peptide fragments of potential drugs that died deaths large and small. Look no further than industry bellwether Pfizer, who in 2007 took a $2.8B charge following the market failure of Exubera, an inhaled form of insulin. This calamity followed closely on the heels of their writing off a nearly $1B investment on internal drug candidate torcetrapib. That’s a lot of money to flush down the drain.
Plugging holes in portfolios or fighting to gain entry into a hot market may cause companies to overpay for their acquisitions. Virtual companies Plexxikon and Calistoga Pharmaceuticals were bought last year for what now looks like chump change in light of Bristol-Myers staggering $2.5B acquisition of Inhibitex (who’s hepatitis C drug INX-189 is only in early phase II development). Inhibitex, which at of the end of 2010 had only 33 employees, might represent this new model of virtual biotech company, although they actually have four pipeline programs, not the idealized single lead. The FDA approved Plexxikon’s lead drug last year, but whether either of these other deals is ultimately successful remains to be seen. While the early investors in Inhibitex are no doubt smiling and counting their money, what will Bristol-Myers say if their drug craps out in clinical trials and doesn’t make it to the marketplace? Oops?
Another important question about this latest biotech model: what’s attractive to researchers in this new ecosystem? Is it capable of attracting the best and the brightest scientists? As Nobel Prize winner James D. Watson put it “Science that leads over the horizon depends on gathering the best minds and enabling them to do what the best minds naturally seek to do: pursue the most thrilling questions of the time.” If one accepts that the B.I.G model era is over, then this type of pioneering work seems unlikely to happen in biotech. Current career choices for scientists wishing to discover the drugs of tomorrow are in Big Pharma companies (most of which are shedding research jobs faster than Gore-Tex sheds water), or in small biotechs that are destined to either be acquired or go out of business. Surprisingly, academia (where many university departments are already financially intertwined with Big Pharma) may be another stronghold of jobs, especially at those research institutions where a commercialization focus is in vogue (e.g. the USTAR program at the University of Utah or the QB3 program at UCSF). Future biotech scientists are likely to be changing companies often whether they like it or not. Maybe the largest pool of jobs will be in contract research organizations, although I see their primary focus as helping develop drugs, not discover them.
As consumers, we are used to disposable products such as throwaway razors, paper plates, and single-use cameras. All are designed to be used once (or possibly a few times), then thrown away. In biotech, we seem to have entered the era of disposable companies. It’s going to take some time (likely more than a decade) to acquire sufficient data to indicate if this new biotech archetype will be more or less successful in producing useful drugs than other models. It would be wonderful to believe that this model can revitalize the industry, but it’s way too early to go all-in on this new biotech genre.
Every time a venture capital firm boasts about a biotech acquisition that provided a substantial return on their investment, let’s keep track of whether or not the acquired asset actually makes it to market. I have no doubt that the virtual biotech model is one that is capable of generating significant financial returns, and investing solely to make money is as American as baseball and apple pie. Unfortunately, societal goals of developing drugs for unmet, serious medical conditions are not fully aligned with the objectives of venture capitalists and industry. I’ve yet to see a sick patient cured by an infusion of stock warrants or the cutaneous application of cold, hard cash. The government officials who screwed up the Aussie ecosystems described above were working (we hope) with the greater good of their citizens and environment in mind. Magical thinking may be needed to believe that virtual companies will slip easily into the biotech ecosystem without serious and potentially perilous complications.














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