New markets, new models for old pharma

One of the most knowledgeable healthcare economists, Scott Gottlieb (M.D.) of AEI has weighed in on big pharma’s dying business models. While no Pollyanna, Dr. Gottlieb finds the glass surprisingly half full — while (as he often does) identifying areas where the FDA is a barrier to innovation.

Writing at the WSJ (and the AEI website) Dr. Gottlieb summarizes the success and limitations of the old business model. The former was represented by Lipitor, which earned $13b/year at its peak. The latter “mostly involved screening millions of random compounds against a molecular target.”

However, he argues that big pharma is learning the proper lessons from the end of their traditional models.

Lesson number one is to use a biological (rather than scattershot chemical) approach:

They took advantage of new science that allowed drug discovery to become a much more targeted endeavor—focused around precise information about the molecular fingerprints of disease.

In this kind of "rational" discovery process, size matters less than precision. Drugs are designed around the individual biological receptor they're targeting rather than being screened out of a library of random compounds. Deploying bigger tools no longer counts as much as having concentrated expertise in the particular pathway that causes a disease.

The next lesson has to do with the organization of innovation:

[B]ig bureaucracies were hostile to the kind of risk-taking and scientific focus needed to do good research. At most companies, the majority of new drugs are discovered by a handful of scientists with repeated successes. There's something unanticipated in drug research that can't be industrialized.

In recent years, pharmaceutical companies started to carve up their sprawling research enterprises into smaller, more focused teams. The right size of a research team is now said to be 20-40 people. To get at new science early, drug makers rely on collaborations with academic research teams and licensing deals with smaller biotech outfits.

(We call the latter process “open innovation”).

The final point is one that been often remarked over the past few years. Drug companies shouldn’t try for incremental improvements for conditions that have been treated in the past 30 years, but instead try to address other conditions (like Alzheimer’s) which lack an effective theraphy.

As a success story for the new, improved big pharma, Dr. Gottlieb cites Pfizer bringing Crizotinib (a lung cancer therapy) to market in 6 years instead of 10-15. Still, he points to the role of the FDA as increasing the costs and delaying the availability of therapies, by increasing the length of trials and the cost per patient.

While various regulatory reforms have been proposed, “none has been meaningfully advanced.” He concludes:

Drug makers are renewing themselves by realizing that their research success wasn't tied to the scale of those endeavors, but their precision. Today, the continuation of these scientific advances depends on their regulators reaching a similar understanding.

HIPAA vs. preventive medicine

This is finals week for the fall semester at KGI. Teams from our first year Medical Devices course (ALS 320 in KGI-speak) are presenting their technical and business analysis of why the world needs a specific new medical diagnostic test.

As an aside, one of the teams made a persuasive case the compliance and liability issues associated with HIPAA will deter (and possibly prevent) the adoption of new technologies for preventative medicine.

The specific context was monitoring of diabetics, of the most expensive chronic conditions in the United States. (I didn’t write down the statistics, but this article estimates diabetes directly accounts for 10% of healthcare spending, or more than $90 billion/year).

The students suggested that the health impacts of diabetes could be reduced through computerized monitoring of various symptoms — not just glucose, but hypertension and other effects as well. (Disclaimer: I am not an MD not do I play one on TV). One product they pointed to was the Withings blood pressure monitor, which uploads data to your iPhone, iPad or iPod Touch and can be manually emailed to your doctor.

The idea is that if data were gathered and stored in the EHR, then it would be possible to catch problems well before a regularly scheduled test. Getting these widely deployed would probably take a HMO (like Kaiser) or hospital group that is caring for diabetics on a long term basis.

However, the security implications of such as system are daunting. Yes, a firm or nonprofit needs to be diligent in avoiding security breaches that compromise patient privacy. However, a data breach (of the source that seem routine nowadays) could lead to government fines or even a lawsuit.

A regulatory barrier like this could be a dealbreaker for efforts such as San Diego’s wireless health initiatives. This chilling effect seems a perfect example of the law of unintended consequences.

How to solve the problem? One way is that the Federal government can’t be fined or sued under HIPAA. Does this mean that these approaches for data monitoring to support preventative health have to wait until the Feds are innovative enough to try this approach? (Or private insurance is out of business and we all are covered by the Feds anyway?)

Charging towards a bleak future

Many reporters, analysts and other observers over the past decade have remarked on how the traditional big pharma business model has been running out of steam. Proposed solutions have included buying biotech companies (as Roche did) and forming generic divisions (as has Sanofi). Still, from outside, the (in)actions of big pharma resemble the controlled flight into terrain of other IP companies.

Last week, two consultants from Booz & Company published their own analysis of the problems in the Booz house journal, strategy+business.

Alex Kandybin and Vessela Genova deduced the strategic choices of 10 major pharma companies (Abbott, AstraZeneca, Bayer, GlaxoSmithKline, Johnson & Johnson, Merck, Novartis, Pfizer, Roche, Sanofi) through their acquisitions and divestitures from 2004-2010. Nine of the 10 have bet on biologics, five on OTC, four on generics and one (Sanofi) on animal health.

They draw an analogy to the choices of the computer industry:

Most industries go through periods of both deterministic and stochastic development. For instance, the computer industry in the 1960s and ’70s had all the characteristics of a deterministic process. IBM, Burroughs, Cray, and others pursued similar strategies, selling giant data processing machines known as main- frames. The personal computer changed the dynamics of the industry, triggering a turbulent stochastic period. It became impossible to predict where the computer industry was going, and in the early 1980s the incumbent players’ strategies diverged significantly.

This is, alas, an inaccurate revisionist view of the industry: in the 1980s, it was quite clear that the PC was democratizing computers and that standardized microprocessors enabled market entry and reduced margins.

More importantly, the computer industry of the 1970s has significant a priori heterogeneity: it was not for nothing that people referred to IBM and the Seven Dwarfs (or IBM and the BUNCH). Cray was in a very narrow and dangerous niche diametrically opposed to commoditization trends and desperately dependent on Cold War spending.

One place where the authors clearly have it right is that big pharma is fleeing from the highest margins in the life sciences (and among the highest margins anywhere) towards average or sub-average margins. The operating margins of pharmaceuticals is 29%, vs. 12% for generics, 8% for services and 2% for drug wholesaling.

This is utterly consistent with the 15-year-old observations of Clay Christensen: lower cost solutions eventually supplant higher cost solutions, destroying margins. Or, as my former colleagues Jason Dedrick and Ken Kraemer showed in their 1998 book, IBM’s shift from hardware to services dramatically grew revenues but cut margins.

What to do? The authors offer fairly generic (i.e. undifferentiated) advice: firms should embrace change, consider multiple scenarios, and assess the firm’s unique capabilities.

In the end, the old model of one-size-fits-all drug is breaking down. What will replace it? One prediction is personalized, genomic-based medicine. But even if that’s true, many uncertainties remain, including how quickly that future will get here and which part of the value chain will be the most unique and thus valuable.

Saving lives through data mining

At the Open Science Summit (@OpenScienceSum) this weekend, a major theme was applying the lessons of open source software (and other means of social production) to human health and drug discovery. WIthin this, my interest was (as in OSS a decade ago) new firms were organizing to take advantage of these opportunities.

Several of the sessions focused on creating (or simulating) a data commons in which the collective findings of dozens (or thousands) of researchers could be aggregated to allow researchers to spot patterns that would be otherwise unobservable in a single trial.

One example of that was Marty Tenenbaum, founder of Cancer Commons (cancercommons.org), which as its name suggests is seeking to be the clearinghouse for cancer data. Some of this is published research, but the goal is gather and share its own data, as the mission statement articulates:

Cancer Commons is a new patient-centric paradigm for translational medicine, in which every patient receives personalized therapy based upon the best available science, and researchers continuously test and refine their models of cancer biology and therapeutics based on the resulting clinical responses.

Representatives of two for-profit companies talked about their efforts to aggregate the terrabytes (or petabytes) of medical data to allow researchers to mine existing data for new insights.

NextBio aggregates public genomic data and allows (paid) customers to combine that with proprietary data to identify possible relationships. The freemium model gets academic researchers started for free — presumably so that grad students get hooked as grad students and take that to their new employers.

DNAnexus is preparing for the shift from a world with one sequenced human genome to millions, and the vast amounts of storage (and computing power) that will be necessary in only a few years to handle this avalanche of data. Earlier this month it teamed with Google (one of its investors) to host the Sequence Read Archive on the cloud for all researchers to have access.

Meanwhile, the consumer genomics pioneer 23 and Me has both genotype and phenotype data for 125,000 people: while the scale is much smaller, the uniformity is greater. One audience member called on the company to use the data for medicinal research, given the notorious lack of comparability for most phenotype data.

Data mining for medical research reminds me of data mining for social science research. Spending money to gather data is normally an entry barrier in the social sciences, so if there’s a free source of data (patents, open source repositories) this attracts a flood of new researchers and studies.

So if researchers don’t have to gather their own data to hypothesize — or evaluate — potential treatments, this is going to drastically cut the cost of entry into pharmaceutical research. We’ve seen this story before — again in open source — there will be a few big winners that move quickly and decisively to exploit this new technology, while other incumbents will find their traditional business models fail as barriers to entry crumble.

Of course, there are other entry barriers for pharma besides research — trials, funding, distribution, brand. Pressure will come on these fronts too.

An executive of Celtic Therapeutics talked about approaches to cut the cost of clinical trials,by using crowdsourcing for the design of trials and telemedicine for more efficiently processing patients. He claimed the costs of trials could be cut from $15-20 million to $1-2 million. Normally I’d take such dramatic improvements with a pound of salt, but the company claims as an advisor Karim Lakhani — one of the world’s leading crowdsourcing experts (and a personal friend).

Cultivating a new crop of bioscience leaders

Today is the first day of classes for the 13th year of classes here at the Keck Graduate Institute. (The first students of the 2-year Masters of Biosciences Program graduated in 2002).

While KGI started with just the one program, this fall brings record enrollment of 150 students across four degree programs (MBS, PPM, PPC, PhD) and certificate students from the City of Hope. A total of 102 of those students are new, including 31 in the one-year degree programs.

I’ve already had my first teaching at KGI during the business “ramp up” day in the first week of orientation. I also judged five of about 20 teams of new students on their initial team projects, including the very impressive (and eventual winning) team of Felicia Amaechi (MBS), Richard Chen (MBS), Ramya Kartikeyen (PPM), Brent Vincent (MBS) and Erin White (PPC).

At Friday’s convocation, KGI President Sheldon Schuster emphasized his commitment to core idea of KGI. KGI is about combining science and business — the former to provide the technology and the latter to identify the needs that this technology will solve. He noted that , the KGI was the first to offer a life science Professional Science Masters — which is now being copied — and then was the first to create a post-PhD program.

Our guest speaker was Marina Gorbis, executive director of the Institute for the Future in Palo Alto. She provided numerous examples of how social media and crowdsourcing are changing how new ideas are created, including in life sciences. She concluded with a provocative scenario of how a decentralized social learning model might supplant (or supplement) conventional university-based learning.

Finally, on Saturday night, about 50 returning MBS students came both to learn what happened over the summer and to make the transition from being the junior to senior MBS students. When asked by director of student services Sue Friedman what they wanted to be, they suggested a combination of engagement, institution building and support for their fellow students.

In the fall, I will be almost entirely be spending my time with the PPM and second year MBS students through the TMP program. I am faculty advisor for two projects, and am also team teaching the TMP class (ALS 400) with TMP director Craig Adams and Diana Bartlett, Assistant Vice President and Director of Corporate Partnerships.

However, as with faculty at other top graduate schools, I will also be spending time on my research — in this case as 25% of the full-time business faculty. Right now I’m wrapping up my latest review paper on open innovation, and then will be turning my attention to two presentations next month at the Technology Transfer Conference 2011.

At what cost diversification?

In teaching about diversification strategies, one of the main theoretical arguments supporting diversification comes when firms provide financing for a portfolio of bets that can’t be separately financed through the stock market.

In his latest posting to “In the Pipeline,” Derek Lowe notes that such diversification has also been one of the historic strengths of Big Pharma. Quoting a blog comment by (longtime Lilly executive) Bernard Munos:

(Arthur) De Vany has shown that the movie industry has developed clever tools (e.g., adaptive contracts) to deal with (portfolio uncertainty). That may come to pharma too, and in fact he is working on creating such tools. In the meantime, one can build on the work of Frank Scherer at Harvard, and Dietmar Harhoff. (Andrew Lo at MIT is also working on this). Using simulations, they have shown that traditional portfolio management (as practiced in pharma) does achieve a degree of risk mitigation, but far too little to be effective. In other words, because of the extremely skewed probability distributions in our industry, the residual variance, after you've done portfolio management, is large enough to put you out of business if you hit a dry spell.

Both Munos and Lowe ask if Pfizer — the largest drug company in the world — doesn’t have a big enough portfolio to diversify against patent cliffs, who does?

In its forthcoming August 22 issue, Forbes is also running an article on the ideas of Munos to reduce R&D and outsource innovation. It also quotes criticism from former Pfizer R&D head John LaMattina, who thinks the death of the pipeline is greatly exaggerated.

Despite LaMattina’s criticism, I find persuasive the argument by Munos — published two years ago in Nature Reviews Drug Discovery — that the current model is running out of steam.

I don’t have enough experience with pharma R&D enough to offer my own fixes, but my sense is that outsourcing inefficient search processes to external partners isn’t going to work. Perhaps startups will have better intuition as to where to look versus a systematic search by big pharma, but if the discovery paradigm is busted, outsourcing it won’t solve the problem. Instead, that would suggest we need a new search or discovery paradigm.

Still this suggests a new debate to bring to my KGI grad students next spring in the innovation management class. In particular, I’d like assign the 2000 article in Research Policy by Scherer and Harhoff (or the Scherer et al article in the Journal of Evolutionary Economics) if their earlier coursework prepares them for the math. (The RP seems more relevant, but the 2002 De Vany article on movie studios cites the JEE).

Wednesday I sent an e-mail to Harhoff, who I visited many years ago and was once dissertation advisor to a friend of mine. He wasn’t aware of the recent visibility of his earlier work, so I guess I’ll have to use the forward cites from Google Scholar to help students make the connection.

Is the death of blockbusters greatly exaggerated?

John LaMattina, former head of R&D for Pfizer, has a provocative post that argues that “The Death of the Blockbuster Has Been Greatly Exaggerated.”

He lists some contrary evidence including a recent WSJ article on potential blockbusters in the pipeline. And of course the title is a deliberate allusion to the famous Mark Twain line.

It’s hard to argue with his credentials and experience, and he makes some important points about the problems about why it’s hard to make predictions about the future. Some drugs will do worse than expected, and some will do better: Lipitor was predicted to peak at $0.8b/year but peaked at $13b/year.

He also argues that there are some major diseases left to be cured, and these cures will be lucrative by any measure.

I can't say I’m complete convinced. Even if such blockbusters remain, on the recent trajectory the cost of getting those blockbusters is getting higher — at some point firms may no longer try.

Perhaps the more serious problem is that the returns from the losers may also be lower, since incremental therapies are having trouble commanding a higher price than established off-patent drugs. (As an allergy sufferer, I can say that the generic versions of Claritin and Flonase are pretty good compared to what was available 20 years ago.)

So the glass is not entirely empty even if it’s not quite half full. The boom times of the old paradigm are clearly in the past. Perhaps some new paradigm (computational biology? personalized medicine?) will enjoy its own boom, but we haven’t seen it.

What are doctors worth?

US doctors have historically been among the best paid members of a community. One list puts surgeons ahead of CEOs, while another study (based on BLS data) shows medical and dental professionals best represented among the top 25 professions.

However, in countries where government runs and controls healthcare, the premium for doctors is not so high: doctors are paid like government professionals rather than self-employed small business owners. A NYT report puts doctors’ pay in some of the Scandinavian countries at half that of the US. Not surprisingly, many economists expect that (for good or for bad) if the US system continues to evolve towards the European model, doctors’ salaries will do likewise.

Now a Business Week report suggests the premium for doctors in China is ridiculously low:

A newly qualified doctor makes about 2,000 to 3,000 yuan ($309 to $464) a month, while a one-bedroom apartment in Dalian, a city of 6 million people, goes for 2,000 to 2,500 yuan. Typically three or four newly qualified doctors will rent a flat together to defray their costs, Mao says.

Shi Yingkang, dean of the West China Medical School at Sichuan University in Chengdu and vice-president of the Chinese Medical Doctor Assn., says half his students spurn local hospitals for better-paying jobs overseas or in drug sales. “To them, the pay does not match the effort put in,” explains Shi, who says pharmaceutical reps can earn two to three times more.

In fact, the article is about how the doctors are quitting their practice to become sales reps for Western pharma companies, including Pfizer, Sanofi and Bayer. An estimated 30-40% of sales jobs in China are staffed by doctors, with pharmacists and nurses also being targeted.

I would be curious to see how the salaries of Chinese doctors compare to party officials, entrepreneurs or software engineers. But with the state in full control of this segment of the economy, it’s not like they have a choice — other than to join the pharma companies or emigrate.

BTW, it had occurred to me that top US sales reps might be paid so generously that they are paid better than doctors. Certainly I’ve met B2B sales representatives who are paid $100k, $200k or more. But according to Monster.com, the median compensation (salary+commission) for pharma sales reps with 20+ years experience is only $125k.

Still — as with any government policy to set salaries — there are important questions about what is a fair price for doctors. The medical profession is highly skilled, with long training required and a need to attract the most talented people. Even for systems that set pay by central planning (rather than the market), one would expect doctors to command a salary well above average.

If pharma R&D is broken, what will replace it?

The last few weeks, I’ve been watching some disconcerting news that adds to existing concerns about funding pharma research.

At Forbes, Matthew Herper presented two graphs. One shows the number of approved new molecular entities (NMEs), which has wild swings (and an impressive peak in 1996) but no overall trend despite the huge upswing in pharma and biotech R&D.

The second graph is the one that (as Derek Lowe noted) is the depressing one:






Two parts are depressing. First, of course, that we’re getting fewer not more drugs per dollar as time goes on. But almost as depressing, the obstacles are not just the limits of science, but also the regulatory regime which at times can distort the curve (good or bad) with fairly arbitrary decisions.

If that’s not depressing enough, then there was this post (at the NY Post) by former Wyeth chemist Josh Bloom, which opens:

The folks at Scientific American have launched "1,000 Scientists in 1,000 Days" -- a program to bring together scientists, teachers and students to improve America's "dismal" showing among wealthy countries (27th out of 29) in graduating college students with degrees in science or engineering. I'm sure they mean well -- but, at least as it applies to the field of chemistry, "1,000 Unemployed Scientists Living With Their Parents at Age 35 While Working at the Gap" would be a better name.

In addition to the soaring costs of bringing a NME to market and the FDA, Bloom points to offshoring:

To trim expenses, companies began to outsource research to India and China. It started as a trickle, but soon became a tsunami, leaving many thousands of highly intelligent and well-trained professionals with nothing to do -- a shameful waste of talent.
My colleagues and I at Wyeth watched helplessly as one company after another shed employees in huge numbers -- 300,000 since 2000. When Pfizer -- facing the looming expiration of its Lipitor patent and a poor research pipeline -- bought Wyeth for its portfolio of products in 2009, it cut about 25,000 jobs, with more to come.

Now Ph.D. chemists can’t even get a job teaching high school chemistry — or at least in New Jersey, where they’re a dime a dozen.

Bloom seems to think that US drug discovery is not cyclical, but in fact in a permanent decline. Let me offer two historical analogies.

For now, IT seems to be cyclical. I remember after the end of the dot-com era, software engineers were also laid off as IT companies died while the survivors offshored most of the routine work to Bangalore. Now, experienced engineers are once again in high demand in Silicon Valley “as they benefit from a tech job market that hasn't been this overheated since the dot-com bubble in the late 1990s” (as the San Jose Mercury put it a week ago.)

When I was growing up in San Diego, the demand for aerospace engineers was cyclical — layoffs and shortages all throughout the 1960s and 1970s. The Reagan buildup brought it back one last time, but eventually the SoCal aerospace industry died after the end of the Cold War. The cycle has ended and the industry is gone.

What’s interesting is that (iPhone Apps notwithstanding) the sale of software products is also in a steady decline. The growth is mostly in software-as-a-service (SaaS) models like Google and Facebook and the rest of “The Cloud.”

People have been talking for years about a similar shift for medicine, from mass-producing little pills to providing personalized medicine. In 2004, IBM’s consulting arm (the former PWC) released a report entitled “Pharma 2010,” which envisioned such a shift. (Such complex service-oriented businesses would play to both IBM and PWC’s strengths). It didn’t happen by 2010, but that doesn’t mean it won’t happen.

So what is the future?

1. Less spending on R&D
2. Spending on R&D but mostly offshore
3. A shift from mass R&D to custom (bioinformatics-based) research

I don’t know what the future holds, but the employees (and shareholders) of the big pharma companies hope that their brands, distribution, manufacturing and (yes) R&D will give them a significant role to play in that future.

Perverse incentives that encourage unethical waste

If you had a federal agency in charge of getting scientific discoveries commercialized, wouldn’t you want them out talking to industry?

So when the agency is NIH, what do they do? Thanks to the 2005 NIH ethics rules, they are discouraged from collaborating with industry.

Derek Lowe writes

The reason I'm talking about all this is that I've heard of instances where people from NIH have refused (or felt as if they have had to refuse) invitations to give talks in industrial settings, because they feared conflict-of-interest problems. This seems perverse, especially for an agency that's talking about getting heavily into translational drug research. That'll have to lead to numerous contacts with industry, I think, in order to be much good at all. So how will the NIH manage that if the drug industry is seen as contaminating their Purity of Essence?

and then in the comments “JAB” replied:

As an NIHer, I pretty much agree with Derek that we're actively discouraged from interacting with industry by the current ethics rules. Formal consultancies were prohibited several years ago, and I don't believe that's changed. Most of my colleagues shy away from anything that might require ethics office approval. It IS possible to give a simple seminar at an industrial site, with prior approval, and I know of folks who do so. Formal collaborations under a CRADA are permitted, but that's two orders of magnitude more work to set up.

I don’t want to minimize the importance of being as blameless as Cæsar’s wife, or the very real problems of any private entity (whether business or activists) illegally influencing government decisions.

That said, the idea of — on the one hand — pressuring (or exhorting) collaboration between government, industry and university scientists to collaborate — while on the other hand adding red tape to make that nigh impossible — is just crazy. Crazy.

And while i understand the central role NIH plays in funding, evaluating and disseminating medical discoveries, they’re not the FDA. It’s one thing to say we don’t want regulators mingling with dirty industry — it’s another to say researchers can’t actually go out and promote real translational research.

It’s not clear how to fix the problem without re-opening the same problems that led to the 2005 rules in the first place. In any endeavor, government regulation and red tape comes along because of a bad apple (or barrel or orchard) that (often) leads to overreaction in the other direction. So eliminating the rules is begging for trouble.

Still, once upon a time the government had rules about de minimis benefits. Is providing someone free lunch in a cafeteria — rather than spending $25 in labor to reimburse a $10 meal cost — really going to lead to unethical outcomes? Some of this is just common sense.

The problem is that some of the outside lobby groups really don't want close industry-government collaboration. (The group pressuring NIH director Francis Collins seems to fit into this category, led by all the usual suspects).

To me, it seems unethical to waste taxpayer money with excessive regulation, delay necessary therapeutics and diagnostics, and even perhaps lead to people dying who didn’t need to.

But then, much as David Friedman points out in his economics primer Hidden Order, people focus on the direct benefit of a given government intervention (e.g. preventing one case of fraud) but not the indirect costs (wasting thousands of person-hours of labor for compliance).

Buying biotech firms to kill them

(Cross posted from the Engineering Entrepreneurship blog)

At #IndustryStudies2011 this week in Pittsburgh, I heard an interesting talk about what happens to biotech startups after they are acquired. Panos Desyllas of the University of Manchester presented his study (with two Manchester co-authors) of UK biotech firms acquired 2006-2010 by non-UK companies.

The team studied in depth six acquisitions, interviewing executives from both sides of each transaction and also analyzing five years of trailing patent data. They also traced what happened to the key scientists after the merger by noting their affiliations in subsequent patents.

From this data, they came up with a simple (but useful) 2x2 typology: are the two firms similar in technology and are they similar in capabilities?

The firms might be exploring different technological frontiers. Or the acquired firm might have something that the acquirer does not — or vice versa — whether it be UK marketing by the acquired firm or global marketing by the acquirer. The (plausible) intuition is that complementary acquisition is more likely to create ongoing value than a more directly competing one.

The typology worked as predicted. In the case of acquisitions where both the technology and capabilities overlapped, the buyer closed the acquired company, keeping only an IP expert or two as a temporary consultant to transfer the tacit knowledge.

In discussion during and after the session, we discussed the case where the buyer bought a rival with the sole purpose of killing it. This happens all the time, and in some ways it seems like a special case with an utterly predictable outcome.

The other case I brought up was when the acquisition starts out as being complementary — but the acquired firm gets killed anyway.

In April, Cisco killed the Flip camera line that it bought for $590 million in 2009. Pure Digital founder Jonathan Kaplan was sorry to see Cisco knife his baby rather than put it up for adoption, particularly when it remained profitable.

The other example (from the life sciences industry) was Biogen Idec, billed in 2003 as a merger of equals between two biotech startups, Boston-based Biogen and San Diego-based Idec Pharmaceuticals. However, the failed merger brought the closure of the former Idec operations in San Diego last November, and the layoff of some 300 employees (including a close personal friend).

During Desyllas’ session, we discussed whether the closure was a good thing or a bad thing for the local economy. In true Schumpeterian fashion, the creative destruction makes available skilled talent to the local economy for other ventures. On the other hand, some off the displaced workers may never have a similar opportunity again.

But in the end, we agreed that the pattern proved a familiar point: companies get sold when the owners want to sell — usually when they want liquidity for an illiquid investment. Whether the founder (such as Kaplan) or the venture investors, once the company is sold all bets are off.

Where are the heroes of pharma research?

Since accepting my new position with Keck Graduate Institute and switching my industry orientation from ICT to the life sciences, I’ve been struck by the difference in how the two sectors are treated in popular culture — particularly drug discovery, whether “big pharma” or the scrappy biotech startups.

One metric is news articles. When I pick up my copy of Business Week every Friday morning, there will be three or four articles about the major computing, communications or other electronics companies, but many weeks nothing about pharma, big or small. Reading the Wall Street Journal or the New York Times (back before they started charging) suggests a similar pattern.

It’s even more pronounced with books. The weekend brought news of the death of Tom West, a longtime engineering manager for Data General. Most people have forgotten his name, but every computer engineer of my generation read about his success creating the Eclipse minicomputer in The Soul of a New Machine — the book that both created Tracey Kidder’s reputation and also the first to apply “new journalism” to study a complex engineering design problem.

I own at least three bookshelves of memoirs and histories about PC, software, Internet and other ICT companies. (I say at least three because some are in boxes and some are mixed in with other books). These books were written in the past 30 years — since the IPOs of Apple and Microsoft made these firms a household name — and include at least 10 Apple books and 5 each on IBM and HP. (Some of these books are on companies that were never consumer brands, including DEC is Dead, Long Live DEC about the once-great Digital Equipment Corp.)

However, when I went to find similar books about drug discovery companies in the San José public library, almost nothing was to be found. In fact, the only book held by more than one branch was Poison Pills: The Untold Story of the Vioxx Drug Scandal, which as the title suggests is a one-sided “exposé” about Merck & Vioxx.

Along the same lines, watching CNN in an airport waiting lounge — the only time I ever watch CNN — today I saw a similar breathless exposé about allegedly FDA lax approval processes. In this case, the guests were a couple of geriatric contributing editors of Vanity Fair, who wrote an article (“Deadly Medicine”) about Avandia, arguing that prescription drug deaths mean that the FDA standards are too lax.

From the TV interview was no evidence that either man knew anything about small molecule drug discovery, PPAR ligands, risk assessment or the steps necessary to gain a Ph.D. in any of the life sciences. In contrast, before my friend Randy Stross wrote Planet Google, he’d lived in Silicon Valley for decades and written six other books, including a biography of Steve Jobs.

One would reasonably assume this sort of media coverage impacts legislative and judicial decision, class-action lawsuits and even the career intentions of high school and college students. The folks that create privacy-invading breakthroughs like Google and Facebook are lionized while people who try to save lives are (often) demonized.

One notable exception was the 2010 movie “Extraordinary Measures,” based on the memoir of serial entrepreneur John Crowley about his efforts to find a cure for Pompe disease. As one promo put it:

An uplifting, inspirational drama, chronicles John Crowley, the man, who defied conventional wisdom and great odds, and risked his family's future to pursue a cure for his children's life-threatening disease.

Of course, any success of the movie is due more to Brendan Fraser in the lead role with two cute ailing kids, and of course Harrison Ford playing a cross between Harrison Ford and Scottie (“I’m givin’ it all aye got, captain!”).

So are the companies that produce therapeutics and diagnostics as evil as one would think watching CNN or browsing books in the personal health section of Barnes & Noble? If not, what can be done about it?

Lost in translation

Any big pharma CEO or shareholder would love to see a stronger link from basic research to the bottom line. But it’s not something that can be achieved via administrative fiat.

Writing at the WSJ Health Blog, Shirley Wang reports

When former NIH head Elias Zerhouni ran the $30 billion federal research institute, he pushed for so-called translational research in which findings from basic lab research would be used to develop medicines and other applications that would help patients directly.

Now the head of R&D at French drug maker Sanofi, Zerhouni says that such “bench to bedside” research is more difficult than he thought.

When Dr. Zerhouni tried to make Sanofi more like a nimble small biotech, he found it didn’t work because (as the WSJ put it) “small biotechs are no more successful than large drug makers at coming up with new drugs.”

Blogger Derek Lowe remarks that Zerhouni “was, in all likelihood, living in sort of a bubble at NIH.” And, Lowe suggests, knowledge of how to fix this is more likely to be found in an industry veteran than a government refugee.

On the one hand, Lowe notes that current NIH head Francis Collins wants to create a new NIH translational research institute. On the other hand, Wang cites its earlier posting, in which the ex-head of Merck said NIH is not well suited for translational research and instead should stick to basic science.

BTW, Lowe and Wang don’t seem to understand “open innovation” is or why Zerhouni is recommending it.

Defining open innovation is much easier than fixing the difficulties of pharma commercialization. A definition can easily be found with Google and there now are a large body of research, an online community and blog on the topic.

Spending on millions on lottery tickets

The recent difficulties of big pharma creating new blockbuster drugs are well known in the industry. Every time they bring a compound to trials, they’re placing a multimillion dollar bet that it will both be effective and also will make it through (increasingly difficult) FDA approvals.

However, these same sort of gambles also apply far upstream, when a new molecule, new technique or even basic science is being pursued by university scientists.

In his blog (In the Pipeline), Derek Lowe today highlights an example of this from the 1980s — one that brought a Nobel Prize in physiology.

He quotes from the new book Adapt by Tim Harford, as summarized in a recent Slate article.

In 1980, Mario Capecchi applied for a grant from the U.S. National Institutes of Health. . .Capecchi described three separate projects. Two of them were solid stuff with a clear track record and a step-by-step account of the project deliverables. Success was almost assured.

The third project was wildly speculative. Capecchi was trying to show that it was possible to make a specific, targeted change to a gene in a mouse's DNA. It is hard to overstate how ambitious this was, especially back in 1980. . .The NIH decided that Capecchi's plans sounded like science fiction. They downgraded his application and strongly advised him to drop the speculative third project. However, they did agree to fund his application on the basis of the other two solid, results-oriented projects. . .

What did Capecchi do? He took the NIH's money, and, ignoring their admonitions, he poured almost all of it into his risky gene-targeting project. It was, he recalls, a big gamble. If he hadn't been able to show strong enough initial results in the three-to-five-year time scale demanded by the NIH, they would have cut off his funding. Without their seal of approval, he might have found it hard to get funding from elsewhere. His career would have been severely set back, his research assistants looking for other work. His laboratory might not have survived.

The problem is, he did exactly what NIH didn’t want him to do, and its process was designed to screen out. Again quoting Harford:

The NIH's expert-led, results-based, rational evaluation of projects is a sensible way to produce a steady stream of high-quality, can't-go-wrong scientific research. But it is exactly the wrong way to fund lottery-ticket projects that offer a small probability of a revolutionary breakthrough. It is a funding system designed to avoid risks—one that puts more emphasis on forestalling failure than achieving success.

Both Lowe and Harford praise the Howard Hughes Medical Institute — in other words a foundation that can take big risks with its own money.

Once upon a time, big rich R&D intensive companies existed to take these sort of risks. In one 20 year period, AT&T invented the mobile phone, the transistor, error correction codes, solar cells, transatlantic telephone cables, the laser and the communications satellite. While the reconstituted AT&T is now a duopoly, the old Bell Labs is long gone.

A long time ago, big pharma made the great breakthroughs. More recently, they let university professors create biotech startups and then bought them. But now such startups look like a bad bet for VCs, and a new financing model is badly needed.

We don’t know who will fund the next round of great breakthroughs. By their nature, we don’t know what they are or where they will come from. Perhaps if we’re lucky, the new tools for computational biology and chemistry will reduce the time and costs of making such discoveries — reducing the amount of money that scientists have to beg for and improve the odds of getting it.

A new way to fund drug discovery?

In the past decade, two failings of the modern drug discovery have become apparent. First, the major pharma companies are unable to develop new drugs as successful as the ones going off patent.

This has been a major theme of Derek Lowe in various posts in his blog “In the Pipeline”. For example, in a November 2010 posting, he lists the commonly know problems: “lower rates of success in discovery, higher costs, patent expirations, etc.”

The other is that the biotech startup model is beginning to fizzle out. Whether or not the current science will make commercially successful biologics, the idea of creating a new company to develop a few compounds — ending with a successful IPO — hasn’t worked for many years. (It doesn’t help that the IPO market has closed overall for bio and non-bio startups alike.)

Into the breach steps Duane Roth, onetime industry executive and entrepreneur who now heads San Diego-based Connect. Roth gave a webinar April 27 where he discussed the problem and some ideas of how to solve it.

Roth’s suggestions were based on a paper he did with former Warner Lambert executive Pedro Cuatrecasas that was sponsored by the Kauffman Foundation and summarized in Roth’s op-ed last year in Xconomy San Diego.

Roth was pessimistic about the prospects for both traditional pharma and the newer biotech model. He said that the IPO market “is never coming back for pre-revenue companies,” stretching out the return for startups and their investors. Today, only one major biotech startup remains independent — Amgen — while both Genentech and Genzyme have become subsidiaries of big pharma.

Instead of the traditional vertically integrated model, Roth argues that the industry needs to separate out a new role in the value chain: a product definition company. In this model, the federally funded research institute (i.e. a university) would license discoveries to the PDC, which would prescreen these for the product development companies (which might also have the distribution channels to bring these products to market).
In this division of labor, the product definition company spends $3-5 million per discovery to characterize it and attempt to develop a prototype. The drug development companies are the ones that do the clinical trial and hope to bring it to market.

The difference in this new model is that the PDC quickly studies the possible compounds and then sells them. There are no 10 year waits for IPOs — quick exits for the winners and returning the compounds to the universities for the losers.

From his vantage point at Connect, he’s watched the mobile industry (led by Qualcomm) make a similar dis-integration between chip designers, contract fabricators and handset makers.

As a longtime strategy professor, I can think of few examples where industries naturally changed themselves and many where industry inertia prevent long-needed reforms. (Think of the record industry.) Thus my question to Roth was: how do we get there from here?

Roth thinks big pharma will invest in and support such companies. He also hopes that angels could fund some companies, given the relatively small capital needs and quick returns.

I feel more pessimistic. This sort of model requires creating a market — buyers, sellers, price and quality measures — and it seems like today’s market is spotty at best. I can imagine that CROs could try to do this product definition, but be unable to get a fair price from potential buyers. Or they might get to greedy, hoping for a later sale at a higher price rather than handing off the compound to a firm that can bear the cost and risk of clinical trials.

Still, there’s no denying the cracks in the current model. During its heyday, US firms were the winners in both big pharma and most notably for biotech startups. The industry — and universities and the country — need to find a 21st century model that will take advantage of our home court advantages: university science, risk capital, and a large affluent domestic market.

Too many PhDs?

IT and other engineering companies talk about a shortage of skilled technical talent. However, Derek Lowe and his “In The Pipeline” blog this week talks about the converse case — too many PhDs in the life sciences, tied to a recent article in Nature News called “The PhD Factory.”

Of course the incentives are all wrong: many science professors want postdocs to help them with their research and teaching, without regard to their abilities to find career jobs after graduation. The problem is particularly bad in Japan and China, where the government has intervened to increase the supply in excess of market demand.

But the US and Europe are not much better. Compared to 30 years ago, half (if I understand their statistics) as many US PhDs are getting real academic jobs. In contrast, Germany is working to find PhDs jobs in industry.

Other solutions are being tried. The accompanying article, “Rehinking PhDs”, talks about an alternative developed at the Keck Graduate Institute. One of the Claremont Colleges, KGI is offering a business-oriented masters (the Postdoctoral Professional Masters) for life science PhDs who’ve given up on bench science and want to go into senior management or creating a startup. The careers blog of Science published interviews on Feb. 4 and Feb. 11 with PPM alumni who were very satisfied.

If any of these efforts cause American PhD programs to become more practical in their orientation, it’s money well spent. With government funding of pure research declining in relative importance, even the most research-oriented scientist must increasingly consider practical applications or at least science that might have such applications.

Webinar: fixing biopharma business models

Connect — the UCSD-affiliated entrepreneurship nonprofit — is hosting a free webinar on April 27 about fixing the business models of both biotech startups and integrated pharma companies.

The advertised topics are

• What killed the fully integrated model?
• Has the start-up model run its course?
• What will the next model look like?
• Where will future investments come from?
• What role should federal and state government play?

The speaker is Duane Roth, founder of Alliance Pharmaceutical, former manager at J&J and Wyeth and now head of Connect.

These are crucial questions for the pharmaceutical industry and associated firms across the value chain. I’ve already signed up.