Friday, June 12, 2015

Accelerating life science startups

On Thursday, I attended the Indie Bio SF Demo Day, a coming out party for 12 companies in its San Francisco accelerator.

SOSVentures, the sponsor of Indie Bio (which has a second site in Cork, Ireland) believes this is one of the first life science accelerators.

As with a life science incubator, the accelerator requires provide startups with shared wet lab space. However, following the accelerator model pioneered by Y Combinator, the accelerator provides mentorship with a fixed term of residency.

The 12 companies applied in January, joined in February and marked their coming out Thursday with a pitch and exhibition to the press and potential investors. The 12 companies are:
  • ABioBot (Raghu Machiraju, CEO): lower cost, higher reliability lab automation
  • Affinity Wulfrun (Anil Bagha, CEO): improved column for manufacturing monoclonal antibodies
  • Arcturus BioCloud (Jamie Sotomayo, CEO): cloud hosted recombinant DNA experiments
  • ArkReactor aka Sensa.io: inexpensive bioreactors
  • BioLoom (Jennifer Kaehms, CEO): biomaterials for skin repair
  • Blue Turtle Bio (Adham Aljahmi, CEO): oral administration of enzyme replacement therapy
  • Clara Foods (Arturo Elizondo, CEO): synthetic egg whites
  • Extem Bioscience (Mardonn Chua, CEO): high throughput stem cell production
  • Orphidia (Aron Rachamim, CEO): point-of-care lab-quality assays from a single drop of blood
  • Pembient (Matthew Markus, CEO): synthetic rhino horn to supplant poaching
  • Ranomics (Cathy Tie, CEO): genomic database for oncology diagnostics
  • ZymoChem (Harshal Chokhawala, CEO): higher yield synthetic petrochemicals
TechCrunch profiled 11 of the 12 companies in their report of the demo event, while three of the companies were profiled when Co.Exist toured the IndieBio lab in April.

Talking to the entrepreneurs, all were indoctrinated in the "lean startup" philosophy. At least one of the companies has already done a “pivot.”

Consistent with that, each of the firms was trying to get to market with the minimum possible cash. Several of the companies have revenues already, and at least two hope to be cash flow positive within the next year. Several of these are tools companies — a business model that is quick to cash flow positive — while the one therapeutics company is targeting orphan diseases which offer a quicker and less expensive regulatory pathway.

Tuesday, February 3, 2015

No incentives, no innovation

I have been teaching innovation management for more than 15 years at three different schools. In most cases, I kick off the course with a discussion of the incentives for innovation, a topic of particular interest to Berkeley economists such as David Teece and the late Suzanne Scotchmer.

Innovation and IncentivesThe fundamental idea is that innovation is risky in many ways: the innovator doesn't know if the technology will work (technological uncertainty), whether the market will value it (market uncertainty) or whether the innovator will be able to hold off imitators and other competitors long enough to make a profit (appropriability and ompetitive uncertainty).

As with any other gamble — whether investing early-stage companies or lottery tickets — the innovation winners have to pay above-normal returns to cover the partial or total losses from the losers. Business is an experiment, and if you don’t compensate for the risk, then entrepreneurs, managers and investors will avoid risk. (We can debate the magnitude or the approach to providing incentives — as Scotchmer and others have done—without denying the inexorable need for such incentives).

Of course, outsiders only see the winners of the lottery or the IPO jackpots. They don’t see the dry wells, the failed companies or the other investments that fail to pan out. So the big success of blockbuster drugs attracts attention (and populist attacks) from those who don’t factor in the cost of failures. In many cases, this is due to economic ignorance — innovation costs or economics more generally — and in some cases this ignorance is willful.

Forbes columnist (and former Pfizer R&D head) John LaMattina attacks such ignorance in his February 3 column “New York Times Op-Eds Misleading Regarding The Biopharmaceutical Industry.” The column is balanced and thoughtful, allowing for the basis of most of the criticisms while decrying the economic ignorance (willful or otherwise) beyond the criticism.

In the category of willful ignorance has to be that of economics Nobel Laureate Joseph Stiglitz, a “frequent” critic of the pharma industry (and, IMHO, capitalism more broadly). Let me briefly except LaMattina’s comments on the Stiglitz op-ed:
1) “In generics friendly India, for example, Gilead Sciences, which makes an effective hepatitis C drug, recently announced that it would sell the drug for a little more than 1% of the $84,000 it charges here.” – Actually, “generics friendly India” really means that India has its own rules when it comes to intellectual property (IP) and often refuses to recognize legitimate IP positions.

2) “Overly restrictive intellectual property rights actually slow new discoveries by making it more difficult for scientists to build on the research of others and by choking off the exchange of ideas that is critical to innovation.” – This is a stunning misrepresentation of the R&D process in the biopharmaceutical industry. For any investment to be made in R&D, be it the 3 person start-up company or a Big Pharma, the promise of a financial return must exist. An absolute requirement for these investments is having sufficient IP to justify that a project, if successful, will provide such a financial return.

3) “As it is, most of the important innovations come out of our universities and research centers, like the NIH, funded by governments and foundations”. – As I have said in the past, these contributions are very important in the search for new medicines. But Stiglitz, like many other critics, is either ignorant of the amount of R&D carried out by the biopharmaceutical industry or chooses to minimize that the industry’s applied research is what converts nascent ideas and discoveries to the breakthrough medicines that are continually generated by the industry.
I would be naturally sympathetic to LaMattina’s criticisms due to my free market bias, which stems both from my first experience as an entrepreneur, what I’ve learned studying technological innovation for the past 20 years, and of course what I’ve also learned teaching students how to run innovation-related businesses.

However, his three criticisms have particular salience now that I’ve co-founded a new (pharmaceutical) startup that is a spinoff of my current employer. It is (as he says) a 3-person startup, bootstrap funded for now, trying to bring a breakthrough therapy to market.

My two co-founders and I are working nights and weekends — alongside our regular jobs — to raise funds, validate the science, and try to get something approved by the FDA. We wouldn’t be working so hard (#2) unless there was some possibility of a big return at the end: hypothetically, if we’re each putting $10,000 worth of effort into it each year, then if we have a 10% chance of success then we’d each want a $100k+/p.a. return (actually more given due known entrepreneurial optimism biases).

Of course, we wouldn’t have started down this path without IP. We have to talk to the government, CROs, CMOs, potential investors, industry execs and others to make our idea feasible. We are a tiny company with no full-time employees and minuscule resources: almost anyone we talk to is better equipped to bring this to market than we do. All we have is an idea, a vision and the (patent pending) IP that we hope will allow us an exclusive to bring this to market (if we can overcome all the uncertainties).

Finally, we have thought long and hard about commercialization. Even if every NIH or other government grant goes our way, we’ll have certain regulatory, manufacturing, distribution and (yes) IP costs that won’t be covered by government grants. These costs are far beyond what we can bear personally, so unless the potential returns are attractive enough, we won’t get the equity investment necessary to bring this therapy to market.

The Stiglitz ignorance (or misrepresentation) is depressing but utterly commonplace, particularly among economic populists. But sometimes these populists can see the light.

In the 1970s, there was no more outspoken populist among national political figures than George McGovern (1922-2012), the South Dakota senator and 1972 Democratic presidential nominee. After retiring from the senate, he opened a hotel in Connecticut and found out firsthand how little politicians know about business risks.

As McGovern wrote in a June 1, 1992 Wall Street Journal op-ed (quoted in a 2011 Forbes article):
In retrospect, I wish I had known more about the hazards and difficulties of such a business, especially during a recession of the kind that hit New England just as I was acquiring the inn’s 43-year leasehold. I also wish that during the years I was in public office, I had had this firsthand experience about the difficulties business people face every day. That knowledge would have made me a better U.S. senator and a more understanding presidential contender.

We intuitively know that to create job opportunities we need entrepreneurs who will risk their capital against an expected payoff. Too often, however, public policy does not consider whether we are choking off those opportunities.
So there is hope for intelligent people who get out of the Ivory Tower (or the Beltway) to try to make a living in the real world. McGovern was a man of modest means — a modern-day Harry Truman — trying to put away money for retirement. Millionaire politicians and academics are unlikely to leave their comfort zones, but there’s still a chance for skeptics to experience this epiphany.

Friday, May 23, 2014

Nascent biotech entrepreneurs

In between days of the Stanford Big Data in Biomedicine conference, on Thursday night I attended the finals of the Oxbridge Biotech Roundtable Onestart Americas business plan competition. I posted my thoughts over on my Engineering Entrepreneurship blog.

Thursday, May 22, 2014

Stone age EHR

Today was my first #bigdatamed conference data at Stanford Medical School, which is hosting a three day conference on Big Data in Biomedicine. (I wasn't able to come Wednesday but watched two sessions on the live webcast).

I first learned of the conference last year from Atul Butte (@ajbutte), who I met when he presented at the 2012 Open Science Summit. My impression from Atul (and watching the webcast last year) is this is a bunch of computational biologists who’ve replaced their wet labs with databases (or nowadays, cloud computing accounts), in search of the next great lead to be found on their computer screen.

Certainly the first two panels yesterday fit that pattern (the first moderated by Butte). So did the after-lunch keynote by former UCSD professor Phil Bourne, creator of the PDB (protein database): a few months ago, Bourne joined NIH as its first-ever associate director for data science, reporting directly to NIH Director Francis Collins.

Translating from Science to Practice

But today the conversation broadened (as one slide put it) from the "science of medicine (biomedical research)" to the "practice of medicine (healthcare)". In other words, from faculty to the clinicians, and from universities (few industry scientists were present) to hospitals and clinics.

Some of the differences were as expected. Drug discovery researchers are at the bleeding edge of the science, and then after 5 or 10 or 15 years of drug development (animal models, clinical trials, regulatory filings, manufacturing, marketing etc.) the product finally shows up in the hands of doctors. Similarly, researchers are hoping to add to their journal publications while providers are trying to improve clinical outcomes — and increasingly under pressure to do so at higher efficiency (of both time their time and the amount spent on tests and treatments).

For clinicians, HIPAA privacy rules limit dramatically what and how data can be used and shared. Researchers have institutional review boards, but also face HIPAA restrictions. The NIH helpfully makes available a brief (16-page) note on researchers should interpret the interaction of IRB and HIPAA privacy constraints. (As it turns out, both clinicians and non-clinical researchers at the conference complained that HIPAA places unrealistic limits on combining data from differing sources to render an assessment of a given patient's health).

Proprietary vs. Open Platforms
At some point, it was inevitable that participants would discuss where the patient’s clinical data resides. Ten years ago, it was in paper charts, but now the ACA has strong incentives and penalties to store it in an electronic health record or EHR. (The administration’s healthcare IT czar says don’t call it an “electronic medical record”).

It was also inevitable that someone would ask: if we are compiling personal genomic data for patients, how will that data be made available for the clinical benefit of that patient? By one estimate, a patient’s EHR runs less than 100 megabytes while whole genome data (I’m told) runs into the gigabytes. As David Watson (ex Kaiser CTO, now at Oracle) said on today’s opening panel, medical images (such as MRI scans) are stored external to the EHR; will that happen with genomic data?

More seriously, how will such data be phased into operational systems? On the same panel, Jim Davies (CTO for England’s 100K genome project) suggested that existing EHRs would need an abstraction layer that would allow new data types to be added on, i.e. the way that apps, plug-in modules and extensions are added to other modern software systems.

However, today the EHR vendors (except for VistA) as proprietary as mainframe platform companies of the 1960s. Even Kaiser — which in 2010 had the largest private EHR implementation to date — is highly dependent on a proprietary vendor (Epic).

Proprietary control of the platform means high switching costs and other proprietary control of the customer, and so (I predict) this is something that none will relinquish unless forced to. We have a technical solution, but not a market solution. And the ACA penalties for EHR non-compliance mean that no provider can credibly defer or set aside EHR adoption until one provides the necessary openness.

So we know where we need to go, but it’s not clear how we get there. Two Harvard researchers — Zak Kohane and Ken Mandl — have proposed a way forward, and the following year won $15 million from HHS to implement their Smart Platforms project.

However, the plan seems to think that either vendors will see openness as being in their own interests or that customers will organize to demand openness. As someone who’s studied IT openness for 15 years, I can say that openness is almost always instituted by the weakest player (e.g. a late entrant), and right now I don’t see an obvious candidate in the EHR market.

WIthout such openness, health care providers are stuck with healthcare IT systems without third party add-ons. This is not just pre-app store, but pre-IBM PC, pre-Apple II, vertically integrated platforms with little if any choice to extend or change their systems. In other words, EHR systems are stuck in the stone age (1960s) of the digital computer era, with little prospect for improvement.

Sunday, May 4, 2014

The next wave of life science startups (and entrepreneurs)

On Wednesday, KGI held a major public event for the finals of our business plan competition. This year (as with last year), the competition was tied to our business plan class, which was first offered in Fall 2003, for our third graduating class of MBS students. Also like last year, the class was team taught by me (as the business guy and course coordinator) and Mark Brown, a KGI grad and senior scientist at a local KGI spinoff company.

This year we had 17 MBS students and 8 (PhD-educated) PPM students across seven teams. The students worked with four external sponsors (plus KGI) to develop detailed business plans — product, sales, marketing, operations and financing — for the patented invention provided by (in most cases) the university technology transfer office.

The teams included therapeutics, research tools/services and a medical device:
  1. Elegans Therapeutics: a novel treatment for asthma (California Institute of Technology)
  2. Insituomics: improved visualization of RNA transcripts (California Institute of Technology)
  3. Click-Brains: software that analysis neurological MRI scans (Children’s Hospital Los Angeles)
  4. Klondike Therapeutics: improved therapy for anthrax (Keck Graduate Institute)
  5. Cardiovascular Cell Source: improved quality supply for endothelial cells (UC Merced)
  6. Mucotherapeutics: therapy to clear mucus for COPD (UC Merced)
  7. Innovfusion: improved epidural infusion pump (BioFactory Pte. Ltd)
We had the most amazing panel of judges, who were all directly involved in launching, funding and/or running life science startups:
  • Robert Baltera, a director of the San Diego Venture Group, former CEO of Amira Pharmaceuticals until its acquisition by Bristol-Meyers Squib, a 17 year Amgen veteran (and a KGI trustee)
  • Craig Brooks, angel investor, head of two current life science startups (BCN Biosciences, Biostruxs) and a 19 year Amgen veteran who formerly worked for Procter & Gamble
  • Robert Curry, partner of Latterell Venture Partners, former general partner of Alliance Technology Ventures, former faculty member at the University of Delaware (and chair of the KGI trustees)
  • Stephen Eck, vice president of Astellas who previously worked for Eli Lilly and Pfizer, a board-certified hematologist/ oncologist (and a member of the Board of Advisors of the KGI School of Pharmacy)
  • James Widergren, a former senior VP, group vice president and treasurer of Beckman Coulter, angel investor (and a former KGI trustee)
From the discussion, the judges were most intrigued by one project, and so it was not surprising when Dr. Curry announced that Insituomics was selected as the winner of the competition. Several of the judges expect that the Caltech technology will enable the next generation of diagnostic instruments. Runner up was Mucotherapeutics, which spent three months translating an in vitro scientific discovery into a viable product.

Head judge Bob Curry with the winners of KGI’s 2014 business plan competition:
Jagan Choudhary, Jixi He, Ashi Jain and Melanie Ufkin 

Entrepreneurship is the lifeblood of any high-tech industry, including biotechnology and the related life science industries that have arisen over the past 30 years. Being entrepreneurial — and applied — are two of KGI’s core values, that we try to embody in our programs, courses, events, faculty and students.

Mark and I want to thank all the judges, the university sponsors and of course our student entrepreneurs for all the hard work that made this event possible.

Wednesday, January 29, 2014

Someday putting doctors out of business

In the KGI business class today, a student idly asked “when will computer replacing doctors in diagnosing patients?” Another student said “never”.

It's pretty clear that technology will reduce the labor-intensity of medical care, and also shift some tasks from expensive high-skill people to inexpensive low-skill people. Look at how cars were made by Gottlieb Daimler, Henry Ford, Toyota in the 1970s and then today.

Computers will over the next 20-40 years replace some or all of the role of doctors in diagnosing conditions. It’s too labor intensive and expensive not to become a target. The question is not if, but when, where first and how fast.

The claim will be that it's intended to improve consistency and accuracy, but the real reason will be cost. Claimed improvements in quality — such as for patients who lack access to a specialist for diagnosis — could be used to overcome the opposition of highly educated, compensated and organized physicians.

The initial push thus will come from an organization that both has scale economies and a record of innovating to save pennies. My prediction is that the first major use in North America will fall in one of three categories:
  • US government, probably the Veterans Health Administration
  • An HMO, almost certainly Kaiser Permanente; or
  • A provider serving rural areas, most likely the First Nations and Inuit Health Branch of Health Canada.

Sunday, November 10, 2013

Biotech not like other high tech

In teaching, research and talking to industry professionals, I am often tempted to refer to “high technology” industries, “technology startups” and the like. This would tend to emphasize the commonality between IT and biotech.

And then there are days like Friday, when I’m reminded that biotech — and human health more generally — is completely different.

The occasion was an event on pharmaceutical quality, organized by KGI’s student chapter of the Parenteral Drug Association, a professional organization concerned with drug quality and safety issues.

The students invited three industry speakers.

First up was Susan Weber of Baxter introduced us to the principles of Quality by Design, i.e. start from a quality goal and work back through the entire design, development an production process. The ideas are more than 20 years old, but apparently have recently have begun to influence pharmaceutical manufacturing in the US.

The second speaker was Marsha Hardiman, a consultant for Concordia Valsource. After showing a stunning video by the American Society for Quality on the consequences of quality failures, she summarized the regulatory and process failures of the New England Compounding Center that have led to 64 deaths so far. Nothing illustrates the difference between a bad drug and a bad iPhone app.

The final speaker was James Sesic of Amgen, talking about the challenges of maintaining regulatory compliance for drugs sold in more than 100 countries.

This was the real eye-opener. We all know about the need for drug companies to spend years and hundreds of millions of dollars to get the first NDA or BLA approval. Sometimes we talk about getting the second approval — e.g. in Europe or Japan after the US. But I’ve never heard anyone talk about the rest of the world.

How does a company like Amgen handle approval in dozens of countries? The richest countries have their own large-scale regulatory systems (US, Japan, Canada, Europe), the smallest grant approval after certified approval from one of the major regulators, while a range of countries attempt to form their own regulatory judgements without a lot of resources.

On top of that, regulatory approval is required for any major change in the production process. Normally this discourages companies from making major changes, but if there’s a major improvement in the process — or the company needs to comply with new regulations — it will go through the process.

One example is getting approval to shift manufacturing to a new factory. The company will have to apply for approval in dozens of countries and cannot sell drugs in country X from the new factory until regulatory agency X has approved such production.

If a drug has several deliver modalities — concentration, IV vs. injection, etc. — then when multiplied by the disparate languages, marking requirements and other national regulations, a single blockbuster drug could be sold in 100s of SKUs. Double that with separate SKUs from the old and the new factory.

When it takes 4-6 years for all the countries to approve the change, then an Amgen needs to keep track of all those 200? 500? SKUs (for one drug) to know which SKU is legal to sell in one country.

Contrast this to the rollout of the latest iPhone, a product that (unlike software or PCs) must satisfy strict government and operator requirements to be sold in a given country. Apple launched the iPhone 5c in 10 countries in September, added 60 countries between October 25-November 1, and expects to have more than 100 countries by the end of the year (i.e. in less than 4 months).

The process of global drug regulation seems pretty inefficient, and we pay for this inefficiency through higher costs (or lack of access by smaller countries to non-blockbuster drugs). It would be nice if we could develop a drug regulatory system where the first review is highly rigorous but the remaining process is streamlined so that drug companies spend their money on development (and safety), not SAP and paperwork.