The Invisible Hand Has Arthritis: Why Free Market Capitalism is not a Panacea for U.S. Health Care

Running a health care service business is hard. Very hard. It is real-world and messy. It is a man with no insurance and a heart attack on your doorstep. It is an elderly woman who arrives senile with a broken hip and no caretaker. All of the clean simplifying assumptions written on the chalkboard at the start of my economics classes (perfect information, infinite buyers and sellers, rational players, elastic curves, a lack of externalities, homogeneity of goods or services) simply don’t apply to medicine.

Below are some useful considerations:

·         Externalities & the Common Good: Libertarians argue that if a person can’t afford health care, they shouldn’t receive it. However, U.S. society does not seem prepared to turn away the desperately ill. The Emergency Medical Treatment and Active Labor Act (EMTALA) requires most US hospitals to provide care to anyone needing emergency treatment regardless of citizenship, legal status or ability to pay.^1,2 Similarly, community hospitals can be considered a “public good”, which should fall outside of traditional market forces.

·         Perfect inelasticity of demand: Health Care is often life and death and demand curves become perfectly inelastic (straight up and down). How can you put a dollar amount on someone’s life? When you or a loved one is in the hospital, rationality is thrown out the window as fear takes hold. This reality, combined with a limited amount of suppliers, puts dramatic upwards pressure on prices.

·         Risk-pooling and third-party payers: The third-party payment system arose to pool catastrophic health care risk amongst many consumers. Now, the consumer (i.e., the patient) is not the payer (i.e., the insurance company) and the employer usually sits between the two. The relationship hinders price transparency, i.e. the relationship between subsidized premiums paid by patients and cost of services provided by hospitals & physicians.³

·         Physician/Hospital fiduciary duty: In most industries, the payer for and provider of a service agree to price ahead of time. Not in health care. Physicians and hospitals have a fiduciary duty to *rapidly* decide what and how many services to provide while ultimately receiving a financial reward for those services and potentially incurring legal liabilities if they miss something.⁴

·         Medicine is not a commodity: Medicine is complicated. It is not like drycleaning or babysitting or getting your car fixed. It is constantly advancing and certainly not a commodity. All patients have unique issues and, while there are standard treatment protocols, doctors have to quickly use their discretion and judgment at all times.

·         Lack of perfect competition: On the one hand, the government is a quasi-monopolistic buyer. Private payers often follow its lead. On the other hand, due to high infrastructure and licensing requirements, many US towns only have one or two hospital networks to supply services. There simply aren’t thousands of payers and providers driving marginal cost to equal marginal revenue, nor is there the time or inclination to shop around.

These are a few of the ways in which the simplifying assumptions of free market capitalism do not apply to health care. There are many others and they all interact with each other. The business of medicine is complicated. The better the BioPharma, Med Device, and Health Care IT industries understand this, the more likely they can all work towards driving efficiencies into and waste out of the health care system.  

Notes:

¹ http://en.wikipedia.org/wiki/Emergency_Medical_Treatment_and_Active_Labor_Act

² However, often no one reimburses hospitals for many of the related costs – it is essentially an unfunded government mandate. Many hospitals write off such care as charity or bad debt for tax purposes. Besides causing some hospitals to go bankrupt, this law has led to cost-shifting and higher rates for insured hospital patients. There are, in some cases, funds form the city or county to remunerate hospitals for indigent care. Many times these funds do not come close to completely covering the deficit. Also, not for profit hospitals have to do a certain amount of charity care to qualify for their tax exempt status. 

³ Consumer-directed health plans aim to ameliorate this situation.

⁴ This is why insurance companies often pay hospitals fixed DRG payments for a given diagnosis regardless of the actual cost of treatment to the hospital. This results in a large administrative effort to prove after the fact that the services they provided were appropriate and necessary.

Related links:

http://krugman.blogs.nytimes.com/2009/07/25/why-markets-cant-cure-healthcare/

http://e.viaminvest.com/B12Methodology/PosEcon/Table_3ExamAssumptions.asp

http://www.cdc.gov/ncidod/eid/vol7no2/scott.htm

http://www.sph.umich.edu/vbidcenter/publications/pdfs/jama1207.pdf

http://econlog.econlib.org/archives/2009/07/what_makes_heal.html

http://insureblog.blogspot.com/2009/06/economics-of-health-care.html

http://healthblog.ncpa.org/is-health-care-different/

http://www.davidhilfiker.com/docs/Economics/Constitutive%20Rules.htm

A Fish Out Of Water?: A Biotech Investor At A Mobile App Hackathon

At first (and second) glance, the worlds of biotech and mobile app development seem to mix like oil and vinegar. What do kinases, IFNs, GPCRs, RT-PCR, SNPs, DRGs, NDA, and 510K have to do with HTML5, JAVA, API, UI, WYSIWYG, Freemiums, 3G, and the Cloud? The two worlds seem polar opposites and seemingly attract people with distinctly different personalities, backgrounds, and ambitions.

·         Biotech is a steady, capital-intensive, IP-reliant industry with a fixed business model (increasingly high price/low volume), high regulation, and risk primarily dependent on technical not commercial success. Participants are used to ten or more years from product conception to commercialization.

·         Mobile App development, by contrast, is a relatively brand-new, rapid-fire, low cost industry with endless novel business models (trending towards low price/high volume), currently low regulation, and risk primarily dependent on consumer adoption. Time from product concept to commercialization could be days.

As someone who has spent the last seven years immersed in the business of biotech, I view the world of Mobile App Development with some trepidation. It seems too good to be true. In contrast to biotech, which appears to be on the flattening phase of its growth curve, Mobile Apps are the Wild West with ample room for exponential growth. Can it be real?

I decided to attend a local Mobile App Hack-a-thon sponsored by AT&T to learn more (http://mobileappsd.eventbrite.com/). The event was described as follows:

Mobile App Hackathon is an event for mobile developers to come together, network, learn about new technologies and build mobile apps. A full day of coding, drinks, food and snacks and fun contents with prizes across categories. Meet new people and teammates, start projects and work on existing ones, and learn from short talks on technologies and trends that can help you build better apps. 

Sounds great, except I know nothing about coding or developing. I built my website with a WYSIWYG (What You See Is What You Get) software program and only recently started to use Twitter and Blogger (for which I was very proud of myself). When I showed up at the event on a Saturday morning, I felt like a fish out of water.

My worries were quickly overcome, however, by the casual, open, and positive energy of the event. It turns out, by a show of hands, that many people there didn’t know how to code. Red Foundry, which has a web-based WYSIWYG App Developer Program, even gave a presentation for the non-coding App Developer (http://redfoundry.com/). In addition, plenty of expert App Developers at the event wanted to work with non-developers with good ideas for Apps. There was room, need, and even hunger for brains – not only those with HTML5 knowledge.

The next Friday, I visited ansir innovation (AI) center, a local tech accelerator with co-working space (http://aicenterca.com/), for their “Hackaway Friday” event – advertised as a casual, all-day coworking event especially for entrepreneurs and startups. Again, I felt like a biotech infiltrator who would illicit an immediate immune response from the nest of techies. Again, I was wrong. The group was casual, welcoming, and smart with a lot of positive energy and intellectual curiosity.

The moral of the story, and the point of this blog, is to encourage the biotech and other communities to get involved with the mobile one. One year ago, when a senior biotech executive encouraged me to consider software applications, I answered, “but I know nothing about that”. In reality, there are plenty of smart, casual, intellectually curious people who do know coding/developing and are eager to partner with people with good business ideas. It is yet to be seen whether mobile will live up to the hype, but I see no reason why it will not. With the biotech and other industries in a temporary (and potentially permanent) slump, it seems like a good time for biotech brains to pivot into the mobile world.  

The Digitalized U: The U.S. Health Care Consumer of 2026

What will the digitalized U.S. health care consumer of 2026 look like? Fifteen years from now, several currently emerging trends will have had time to mature, converge and disrupt the U.S. health care ecosystem, including mobile connectivity & mHealth, social media & electronic health records (EHRs), genomics/proteomics & diagnostics, consumer-controlled healthcare & insurance reform, and, not unimportantly, the rise of the BRIC countries. The system of levees and dams that currently controls and constricts innovation in the U.S. health care industry, (i.e. HIPAA, FDA Regulation, Medical Malpractice, Third-Party Payment System, Cultural Mores, Medical Paternalism, etc.), will find itself overcome by a surge of digital technology, consumer (a.k.a. voter) demand, a loosening of disease stigmas, Medicare & Medicaid cut-backs, an aging population, and a drastic need for improvement in system efficiency.  A generation of individuals raised on the internet with easy access to information, a culture of openness & sharing, and a consumer-focused economy will become middle-aged and demand more control over their own health and that of their parents. 

·         Mobile Connectivity & mHealth: The mobile health revolution is underway. Consumers are already psychologically connected to their iPhones, so a physical connection seems inevitable. mHealth will allow for continuous capture of clinical data in the home and mobile setting, an innovation which will dramatically change the treatment of chronic conditions and general health.  Sensors of all abilities will flood the market by 2026, and we will use wireless patches and implants along with environmental sensors to monitor our every biodigital datapoint, e.g., heartbeat, net calorie consumption, temperatures, insulin levels, blood pressure, brainwaves (yes, some basic thoughts), mood, stress, cholesterol levels, infections, protein-expression levels, etc. Cyborgs, here we (be)come.

·         Social Media & EHRs: The Web 2.0 revolution will be a distant memory and Web 3.0 will be underway. Compiling and utilizing international databases of consumer health care data will be considered second-nature. Population statistics applied to this data will reveal novel understandings about disease etiology & response to treatments. Clinical study implications will change the face of drug development, clinical use, and reimbursement. Social stigmas for many diseases will be reduced as a clearer picture of epidemiology and open discussion of symptoms emerges.  

·         Genomics/Proteomics & Diagnostics: A large percentage of the U.S. will have their genome sequenced, housed within global population databases, annotated for phenotype, and analyzed for revelation of new promoters, genes, SNPs, etc. Similarly, advances in microfluidics and proteomics will allow for the monitoring of a variety of protein expression signatures over time and an understanding of their association with disease. Diagnostics in general will be more accurate and ubiquitous, with OTC access. The medical profession will be incentivized to put much more emphasis on prevention vs treatment, with major implications for the drug industry.  

·         Consumer-controlled Healthcare & Insurance Reform: “Patients” of today will become the “Consumers” of tomorrow who utilize consumer driven health plans and are culturally open to out-of-pocket payments for health monitoring and preventative therapies. Instead of brick-and-mortar doctor’s offices and hospitals, health care will take place at home, in retail stores (Walmart, Walgreens, Brookstone), and online (Amazon, iTunes App Store, SaaS sites), etc. Health care consumers will take more control over their treatment plans and medical paternalism will give way to doctor-patient partnerships.

·         Rise of the BRIC Markets: India and China will be more dominant forces with innovation economies of their own. Their lower barriers to market will drive initial launches of new health care innovations outside of the U.S., with obvious successes influencing the U.S. market. The interconnectivity of the internet and digital information will allow for international human health & biomedical databases and an arbitrage on conducting research in those geographical markets with lower regulatory hurdles and more fundamental health care needs (with resulting ethical concerns).  

How the process will play out over the next 15 years remains a question, but the end result described above seems clear. Big, successful, profitable, transformative health care companies will exist in 15 years that are only glimmers in someone’s mind today. Stay tuned.

"p" or "β": How Clinical Success is Affected by the Macroeconomy

In the footnotes to my last blog post “Cost of Biotech Capital: Incorporating Development Risk into VC’s Target Return,” I contemplated which biotech start-up risks are uncorrelated with the general market and hence “diversifiable”. Many assume that a given clinical trial’s binary probability of technical or regulatory success (“p”) is one such risk.¹ As described in the last post, short-term oriented financial analysts (many at hedge & PE funds trying to gauge the outcome of binary events) assign a probability of success ("p") to a given clinical trial and do not expect that value to fluctuate with the general market (i.e. S&P 500). In the short run (event to occur in < 2 years), they are likely correct. In the long run (event to occur in >2 years), however, “p” is often influenced by general political and economic conditions. This is the timeframe considered by VCs and BioPharma companies. Below are three of the ways in which “p” can find its way into “β” in the long run and, ultimately, drive up the long term cost of capital for biotech.

(1)    FDA

FDA requirements affect clinical trial design and the choice of primary and secondary endpoints. All things equal, a stricter FDA will lead to a lower “p” or probability of what the FDA considers technical success. The FDA is in turn affected by the general political environment and hence the macroeconomy.

(2)    Availability of Capital

The free availability of capital can have dynamically opposed effects on “p”. On the one hand, more cash means better and bigger clinical trials which boosts “p”. On the other hand, too much capital leads to poor investment discipline and many companies getting funded that shouldn’t. This phenomenon is similar to what occurred in mortgages, where the free availability of low interest rate IO mortgages with no credit checks manifested in historical default rates 3-5 years later.   

(3)    Clinical Trial Recruitment

The status of the economy likely influences who and how many people agree to participate in clinical trials. One theory argues that in good times, more people can pay for experimental treatment or top-notch medical care themselves and decide not to participate in clinical trials. In bad times, the reverse may be true. Better recruitment may lead to better clinical trial results and a higher “p”. Likely (2) Availability of Capital and the existence of many competing trials is another factor in recruitment success.   

There are likely many other ways in which general economic conditions impact biopharma’s probability of technical success over time. In the long run, “p” shows up in “β”. Counter to my last blog post, this is an argument for adjusting biotech’s long-run cost of capital for binary technical risk. While 58.7% IRR still seems too high, perhaps the industry standard ~30% IRR is a reasonable happy medium.  

1.       “p” is not to be confused with the statistical term “p-value” which determines how likely a clinical trial result is due to chance.

Cost of Biotech Capital: Incorporating Development Risk into VC’s Target Return

Although the average biotech investor probably understands the term “cost of capital” and general CAPM theory, there still seems to be much confusion around how to incorporate the binary risk of drug development into discount rates and required IRRs. CAPM and portfolio theory tells us that investors are only compensated for correlation to general macroeconomic risks – i.e. risks we can’t diversify away. Thus, taking on so-called “idiosyncratic risks”, such as the binary risks of clinical trials, should not theoretically garner an investor any extra return (assuming the clinical trial risks are not correlated across a wide portfolio of investments, which may or may not be an appropriate assumption¹). Why then, do we see VCs demand gross² IRRs of 35%-60% per each investment (dramatically higher than CAPM would dictate) to compensate for drug development? The answer lies in the difference between a portfolio’s ultimate expected return (i.e. a VC investor’s cost of capital) and an individual investment’s target return.

                Andrew Metrick, my former professor at the Wharton School, clearly explains the difference in his book “Venture Capital and the Finance of Innovation” (http://www.amazon.com/Venture-Capital-Finance-Innovation-Metrick/dp/0470074280). The general financial theory he describes is also used widely in the BioPharma industry to calculate eNPV (expected or risk-adjusted NPVs). We used this theory at Genzyme, and I know it is used at many other major BioPharma companies to value their pipelines. The basic idea is to probability-adjust cash flows (or the numerator) for the binary risk of drug development (probability of technical success) and not incorporate that risk into discount rates (or the denominator). For example, to determine the value of an early-stage acquisition target, you would multiply the stream of potential cash flows by the probability of each of them actually occurring and then discount back using a discount rate determined by either (i) the general CAPM equation R_Discount = R_F + β(R_M - R_F) or (ii) a more elaborate model, such as the Pastor-Stambaugh model (PSM) that incorporates additional factors for value, size, and liquidity (for simplicity, assume no debt). The discount rate used by most BioPharma’s is ~10-15%. However, many VCs will use the following equation to move the idiosyncratic (or binary) risk (i.e. “p”) into the target discount rate (i.e. Target Return):

p/(1+ R_Discount)^Time = 1/(1+Target Return)^Time

For a project that has a p = 20% chance of exiting for some fixed amount of money and an 80% chance of exiting for $0 in Time = 5 years, with a standard R_Discount of 15%, the Target Return or Target Discount Rate = 58.7%.

.20/(1+.15)^5=1/(1+.587)^5

When VCs say their discount rate or required IRR is 58.7% to adjust for development risk, this really translates into the 15% discount rate we normally think of adjusted for probability of technical success. No investor actually expects to receive a 58.7% return for the entire portfolio. As is often said in the VC world, the winners have to make up for the losers so the returns can average out to a reasonable compensation for taking macroeconomic or non-diversifiable risk (and possibly adjustments for size, value, and liquidity).

Notes

 (1) These days, the big question is which biotech start-up risk is diversifiable and which is correlated to the general economy (i.e. macroeconomic risk) and affects β. Certainly capital availability, which plays a significant factor in the success of biotech start-ups, is greatly tied to the macroeconomy. However, this is perhaps already captured in the “size” factor of the PSM model. Other factors, such as FDA regulatory requirements or access to patients for clinical trials, are also tied to the general political environment and perhaps cannot be diversified away.

(2) Note that a VC’s gross IRR and net IRR differ due to fund management fees and carry.

Punctuated Equilibrium: Is a Meteor Heading Towards the BioPharma Ecosystem?

It is impossible to ignore the impact of social media in recent years and its powerful ability to connect people, ideas, and information across time and space. For relatively minimal time and effort, commercial websites can be created with tremendous social value (e.g. use of social media in Egypt's youth revolution). Contrast this to the aging drug development industry, which many pundits claim is facing a crisis due to a “broken business model”. Cash burn is too high, development timelines too long, approvals too infrequent, and reimbursement too low. Perhaps this is true, but pharmaceuticals are far too important to humanity for the industry to simply dissolve. Inevitably some set of phenomena will cause a rapid and dramatic change in the BioPharma ecosystem - a punctuated equilibrium of sorts. Could social media be this meteor? Could the IT world ironically give BioPharma the dose of medicine it so desperately needs?

                The striking aspect of the social media site Twitter is its openness and ability to index and communicate massive amounts of information. Similar to the invisible hand of capitalism, Twitter’s collective platform has a greater power than the sum of its individual contributors. In contrast, the BioPharma industry operates mainly in shadows and silos. At the research level, the patent system, while necessary to compensate investors for taking large and lengthy risks, clearly can stymy communication and the public’s ability to freely innovate in already staked areas. At the patient level, confidentiality and the historical difficulty of obtaining and sharing consistent digitalized clinical data are barriers to identifying large-scale trends through applying population statistics. When these barriers are overcome, the subsequent increase in the efficiency and effectiveness of drug discovery could return the industry to its boom years.

            Signs of the social media meteor can already be seen. Sage Bionetworks, a nonprofit research organization, is trying to “create an open access, integrative bionetwork evolved by contributor scientists working to eliminate human disease (http://sagebase.org/sage/index.php)”. According to their website, “The Sage Commons . . . an accessible information platform . . . will be used to integrate diverse molecular mega-datasets, to build predictive bionetworks and to offer advanced tools proven to provide unique new insights into human disease biology. Users will also be contributors that advance the knowledge base and tools through their cumulative participation. The public access goal of the Sage Commons requires the development of a new strategic and legal framework to protect the rights of contributors while providing widespread access to fundamentally non-commercial assets (http://sagebase.org/commons/index.php).”

                “Open-Source” sharing of discoveries seems anti-capitalistic. Patents should certainly continue to exist for downstream commercial developments that require millions of dollars of investment. However, many academic, corporate, and clinical datasets and scientific results will never be relevant for commercialization. A lot of information is sitting stale in a lot of labs and doctor’s offices across the globe. Like individual pieces of a large jigsaw puzzle, a clear picture of human biology only emerges when they are combined. BioPharma stakeholders will have to adjust to freely sharing basic research, datasets, and perhaps bioinformatics tools. In return, the resulting improvement in the fundamental understanding of biology will dramatically improve the success rates of patented drugs and lower costs of development. Although there will be a lot of cultural resistance at first, the social media meteor may be just what it takes to keep the struggling BioPharma ecosystem alive.

Relevant Links:

http://www.economist.com/node/2724420?story_id=2724420

http://p2pfoundation.net/Open_Source_Biotechnology

http://www.nature.com/nbt/journal/v28/n7/full/nbt0710-631.html

http://www.patentlens.net/daisy/cambia/home.html

http://mjlst.umn.edu/uploads/CS/bW/CSbWvh00RsLS5YM4raBkYg/feldman_a2.pdf

Subtle Barriers to Seemingly Win-Win BioPharma Spin-outs

Many of the R&D programs housed within big BioPharma may be developed faster, cheaper and better in the hands of a more nimble and focused start-up. These programs are often delayed or cancelled due to short term budget issues or changes in commercial strategy. Meanwhile, the IP clock runs out, researchers become demoralized, and past effort and capital is wasted. Why then, do we not see more spin-outs as part of a ritualistic spring cleaning on the part of big BioPharmas? There are six subtle reasons why seemingly win-win BioPharma spin-outs never happen.

1.       Precedent

For many BioPharma companies, there is little institutional precedent for such spin-outs (although there are admittedly notable examples, see links below). Business Development, Legal, R&D, and Commercial professionals often have scant experience preparing their own early-stage programs for someone else’s due diligence. Scientists may not have Know-how, Trade Secrets and physical materials organized and ready for transfer. Accountants may be uncomfortable with reporting requirements in light of Fin 46. Bus Dev folks may have never completed an out-license or structured a start-up. Commercial groups may lack analysis or projections for early-stage programs. This all adds up to a BioPharma deal machine whose wheels are not greased for spin-outs.

2.       Glamour

The Business Development groups of most BioPharmas are focused on M&A or in-licensing products to fill near-term holes in their parent’s income statements. Spinning-out early-stage R&D programs that the parent can no longer develop is considered neither glamorous nor the best means of career advancement. Spin-outs are also a psychological acknowledgement that someone else may be able to do a better job, a fact that can be uncomfortable to swallow.

3.       Fear

This point is perhaps the most obvious. BioPharma companies fear licensing out a potential blockbuster. After all, if they keep the R&D programs in-house, they maintain their (often valuable) option to resume developmet efforts if conditions change. Thus, BioPharma may want to include “strategic rights” or “clawback provisions” in an out-license or asset sale in addition to equity, milestone payments and royalties. These can include Right of First Refusal, Right of First Negotiation, Hard and Soft Call Options, etc. However, VCs/Angels and the management of start-ups are loath to agree to such provisions and their inclusion often halts spin-out discussions in their tracks.

4.       Entanglement

Whereas start-ups are often “project” companies focused on discrete technology bundles to be sold in five or so years, “perpetual” BioPharma companies are much more complex. Their R&D programs are often entangled with one another and may each step on some broad core set of IP or Know-how (e.g. a class of compounds or targets or manufacturing know-how). The BioPharma may not be able to effectively license out or assign IP to one program without endangering or affecting another program or restricting future activities. In addition, the BioPharma may have itself sub-licensed relevant IP without the ability to sub-sub license it. Furthermore, whereas start-ups have limited assets to worry about outside of their lead program, BioPharmas have much more cause for fear from lawsuits and other liabilities.

5.       Valuation

BioPharmas often have poured more money into a program than the VCs are willing to value in a financing round. As stated in a previous post, BioPharmas usually want to stay under 20% share ownership. With say a $10M cash Series A raise from investors, the BioPharma’s stake is equivalent to $3M (assume post of 65% investors, 20% biopharma, 15% option pool). If the BioPharma has spent $8M on the program so far, that is a hard pill to swallow even factoring in milestones and royalties. (However, it raises an interesting accounting question as the R&D has most likely already been expensed.)

6.       Management

Many of the better known BioPharma spin-outs are the result of M&A where the acquired start-up’s management team decides to spin-out remaining peripheral assets (e.g. Relypsa/Ilypsa/Amgen). In this case, the assets are unentangled and a management team is both ready, willing and able to spin them out and backed by the momentum of a recent success. It is a lot less clear who would manage the spin-outs of BioPharma’s organically grown programs.

Despite the challenges, BioPharma spin-outs can still be worthwhile endeavors. Besides preserving value and R&D momentum, they can also provide jobs during periods of corporate downsizing and give some drug programs a greater probability of success. There have been many other articles/blogs written on this topic, a few of which are linked below.

Useful Links:

http://www.nature.com/bioent/2003/030401/full/bioent727.html

http://www.signalsmag.com/signalsmag.nsf/657b06742b5748e888256570005cba01/cf05408f18adda9d8825679b0052d533?OpenDocument

http://www.fiercebiotechresearch.com/story/gsk-bets-hungry-spinouts-can-upstage-fat-pharma/2010-10-05

http://venturebeat.com/2007/10/29/amgen-relypsa-and-the-art-of-the-biotech-spinout-startup-restart/

http://www.fiercebiotech.com/story/alkermes-spinout-nabs-20m-fuel-parkinsons-program/2011-01-10

Apples v Oranges: Don’t Use BioBucks for Deal Comps

Press releases often grossly overstate the dollar value of life science license agreements. The stated “BioBucks” are adjusted for neither probability of occurring (often slim) nor the time value of money. However, many industry participants refer to these press releases for deal comps when structuring agreements. Upfronts, regulatory milestones, and single or double digit royalties are all teased apart for signs of what is “fair market value”. Below is an explanation of why this is a common yet faulty approach.

Non-disclosure

The detailed financial terms and structure of drug development and commercialization agreements are rarely made public. Private companies don’t disclose them and public companies only do so if they are “material”. License agreements disclosed as Exhibits to regulatory filings often redact key items. It is small wonder that people rely on what is available – carefully tailored press releases.

Complex and Customized Deal Structures

Drug development and commercialization agreements are highly complex and customized. Trying to condense their key terms into one or two sentences is unrealistic.  Some subtle variables that are manipulated to structure a license agreement include:

·         R&D – Some deals require the licensee to pay for near term clinical trials which can easily match or surpass the size of any Upfront.

·         Indications – Some agreements “split indications” and only license a few of a drug’s many potential therapeutic uses or pay indication-specific milestones. The same may apply to a particular route of administration.

·         Geography – While some licenses are worldwide, there has been a recent trend towards ex-US or country-specific deals.

A worldwide deal where the licensee pays for all future clinical trials and the licensor accesses all uses of the drug will have much higher “headline” deal terms than an ex-US deal where the licensor pays all future expenses and only accesses the lead indication.

Drugs Are Not Fungible

Even if two agreements have identical structures, are at the same stage of development and are for the same specific indication (e.g. front-line for stage III lung cancer), their financial terms can and should diverge. The value of a drug depends on many factors including existing and projected safety & efficacy data, route of administration, reimbursement setting, IP life, manufacturing requirements and COGS estimates, etc.  

Because each deal is custom and terms are kept mostly private, the life science partnership market is extremely opaque.  Relying on surface-level press releases is bad practice. Every deal should be properly financially modeled to include all key variables and identify the optimal structure and financial terms that can withstand a variety of future scenarios.  Otherwise, you are just comparing apples to oranges.

When to Partner a Biotech R&D Program

When early-stage life science companies are deciding when to partner a program, they must weigh their ability to convince a third-party of its value against their ability to successfully continue to the next stage of development. Both require a bit of guesswork. The time sensitivity of the VCs on their board may tip the scale.

Convince a partner of your worth

Many big Pharma’s operate their development pipeline using portfolio theory. Every stage of development has an average attrition rate, which Pharma’s apply across a bucket of projects. If your drug truly has an above average probability of success in future stages, you must convince a partner of this fact or face an unfair valuation haircut. You know your drug better than anyone and are in the best position to judge its chances. The Pharma knows there is an information asymmetry and will rely on the empirical preclinical and clinical data you provide. It is up to you whether you can and should stick to your guns and raise another round of funding. Remember that the process of finding and courting potential partners, preparing for diligence, and engaging in term negotiations is itself a distraction and significant use of limited management time and focus.

Going it alone

While big Pharma’s have the resources, experience and horsepower to execute later stage clinical trials, many biotech companies are essentially focused on completing research projects vs building traditional stand-alone companies. They often hire only those needed for the immediate task at hand and make liberal use of consultants. This approach, while efficient, can limit a company’s options if it cannot find a partner and/or chooses to go forward alone. Besides finding and adding appropriate full-time personnel for the next stage of development, a company’s most difficult challenge these days is raising enough capital to reach an inflection point years away. Earlier stage projects in the pipeline may have to be postponed or cancelled. The impact on corporate morale (both good and bad) of such a decision is not insignificant. On the bright side, going it alone allows a biotech to maintain full control and avoid the possibility of watching their lead program get short-shrift within a big Pharma.

VCs and Time Sensitivity

VC funds face pressure to monetize their investments in roughly five years. They may balk at doubling down again on an investment and claim to prefer “non-dilutive financing” via a partnership. This is a misnomer, however, as the top-line (revenues, cash flow, control) does get diluted in a partnership, if not the shares outstanding. The partner is not jumping in for free and will demand a significant portion of the project NPV. These days direct secondary PE funds may play a small role in preserving corporate value while allowing investor liquidity.

As the universe of potential big Pharma partners will likely continue to contract in the near future, more and more biotechs are going to have to derisk their programs themselves. For this to be sustainable and realistic, proof of concept trials will have to be shorter, smaller, and cheaper. Perhaps the answer lies in the discovery and use of surrogate biomarkers as endpoints. Perhaps next-gen sequencing and computing power will discover new easy-to-drug targets and restore us to a time when biotechs pursued low-hanging fruit. For the dreamers out there, perhaps the IPO market will return and early-stage biotechs will evolve into the very FIBCOs (fully integrated biotech companies) that are now an endangered species.  

The Impact of Time on the Drug Development Industry

The lengthy timeframe for drug development serves as a strong and subtle influence on the biotech industry.  Certainly its relatively slower pace has caused traditional biotech to adopt a unique culture distinct from its Med Device, Diagnostic, & Tools cousins. Below are three ways time causes the biotech model to diverge from most other industries.

1)      IRR (Time-weighted return)

Many VCs and the biotech media will measure multiple return on cash investment as an indication of success (e.g. 5X return). However, this ignores an important variable in finance, time. IRR, a time-weighted return, is the more important measure. A 10X return achieved over 100 years is not so impressive. Because biotech takes so long before a product is cash flow positive (10+ years), returns on an IRR basis take a hit. Even if an early-stage biotech sells to big Pharma after say Phase IIa proof-of-concept, its purchase price will be heavily influenced by the Pharma’s timeframe to cash flow breakeven. Cost of capital becomes a real issue over ten years, as does any loss in patent life. Contrast this to the faster paced Med Device or Diagnostic world, and you can see why a lot of Healthcare VC dollars are migrating in those directions. Furthermore, the pressure for a biotech to partner or sell after five years to satisfy VC’s timeframe puts unnatural pressures on a program that is meant to take much longer. When a biotech rushes development to partner early, when the focus is not on a successful product launch but solely Phase II exit, shortcuts are taken, know-how, focus and momentum are lost, and drugs often fail as a result.

2)      Crystal Ball

In many ways running a biotech is like steering an ocean-liner. It is hard to be nimble and you have to predict what macro and microeconomic conditions will look like ten years from now. Will regulatory rules and reimbursement mechanisms have changed? Will there be an IPO market or interested acquirers? Will a new diagnostic tool identify more patients to treat? Will the emerging markets have a sustainable health care system and honor IP? What about competition? It is very difficult for biotech companies to predict any of these variables. Unlike most industries, the long R&D time-cycle means you can’t necessarily tailor your business model to the fluctuations of the marketplace.

3)      Personalities

The relatively slower pace of drug development and its focus on major innovations vs incremental improvements attracts a different personality than most other industries. Many start-up biotech companies are at least initially run by MDs or PhDs, not traditional business people. These individuals are intellectually curious, passionate about their field, and interested in advancing science and medicine. However, many were raised in academia and have little inclination to focus on the end market. They often base their companies around innovative capital-intensive solutions looking for problems to solve. This “hammer-looking-for-a-nail approach” can create a challenging dynamic for a for-profit, VC-backed start-up with little cash or time to spare and high demands for exits.

Because the healthcare commercial marketplace is constantly evolving, biotech companies should avoid relying on stale business model heuristics that were only relevant to the healthcare landscape of the past. No one has a crystal ball, so the best you can do is research current market conditions, take a reasonable and thoughtful guess as to the future, narrow your focus on a specific set of product opportunities, and generate a tactical game plan. Then do it all over again in six months.

Issues To Consider When Adding A Corporate VC To Your Fundraising Syndicate

Since 2008, cash has been king, and as the traditional VC market constricts, Corporate VCs have become an appealing source of capital and expertise for young biotech companies. Below I discuss issues to keep in mind when considering adding a Corporate VC to your syndicate.

Disclaimer: Please consult an accountant expert for more information as these rules are complex and change frequently. I am not an accountant.

1.       Ownership constraints – Historically, many corporate VC’s could not own ≥ 20% of your post-financing fully diluted shares outstanding or their parent BioPharma would have to absorb a portion of your P&L expense onto their income statement. In recent years, the accounting rule FIN 46 has lowered the 20% ceiling further, especially if board seats or special voting rights are involved. The rule could potentially require the parent BioPharma to consolidate all of your financials onto their books every quarter and is a logistical nightmare for their finance group. The same may hold true if the Corporate VC contributes the majority of the cash in the round.

2.       Leading rounds – Many corporate VCs will not lead rounds despite their strong enthusiasm for your company.  The reason again has much to do with accounting. Parent BioPharma’s have to justify to their external accountants that they are paying fair market value for your stock. This is easier to do if a stand-alone third party VC sets the price. This is also one reason corporate VCs will be more hesitant to pay a premium for your stock (among other reasons) as they may have to immediately expense a portion of it. This same may hold true for all elements of the financing terms including liquidation preferences, anti-dilution provisions, conversion ratios, etc.

3.       Strategic relationship – There are both pros and cons to adding a Corporate VC to a syndicate. On the one hand, many Corporate VCs work closely with their parent Company to provide valuable expertise regarding clinical trial design, regulatory interactions, research tools, commercial assessment, etc. This expertise is often impossible to duplicate using external consultants. On the other hand, there are implicit signals sent to the world when you forge a formal relationship with a BioPharma company. These signals can provide validation and help you fill out your syndicate, but can also make other BioPharma’s feel that the invested Company will have the upper-hand when it comes time to partner.

4.       Motivation – Many Corporate VCs have different agendas then their Financial VC counterparts. Afterall, they are “strategic” investors who are using VC investing to ultimately help fill their parent’s product portfolio down the road. The people running the shops may have slightly different backgrounds and approaches to an investment. This can manifest in slightly different behavior than you are used to from a VC.

No two Corporate VCs are identical and they come in a variety of corporate structures and personnel flavors. Some are separate operating companies with their own balance sheet. Some are run off the parent Company’s books. That being said, in BioPharma there are less than a dozen major players, so getting a feel for each one does not take long. Overall, if done correctly, a Corporate VC can be a valuable addition to your syndicate.  

3 Tips for a Successful BioPharma Partnership Pitch

During my time in Corporate Development at a large BioPharma company, I observed hundreds of private biotechs make their case for partnership or a Corporate VC investment.  I noticed some constant themes for what works and what doesn’t. Below are three tips for a successful BioPharma partnership pitch.

1.       Know your audience – R&D vs BD meetings

Successful pitches are tailored to the concerns of a particular audience. R&D folks will care about data, data, data and how this program will fit into the existing R&D portfolio (and whose budget it will consume). They are by nature intellectually curious and will enjoy discussing the nitty-gritty details. BD folks care more about the big picture, synergies with the BioPharma’s existing commercial infrastructure, and tactical next steps. They are looking at hundreds of other companies and asking themselves whether they should spend their time on yours. Tailor your presentations wisely and know who will be in the room ahead of time.

2.       Don’t alienate your potential champion

Going around or over a BD person’s head often backfires. Very often, private life science companies will simultaneously try several different avenues to gain the attention of a particular BioPharma. I have seen this approach backfire VERY often because it ignores intra-Company dynamics. Remember, a BioPharma company is not its own living organism. It is made up of individuals with their own agendas. If a BD person who is supposed to “own” a particular space feels their autonomy or authority is being usurped, they will be less likely to champion your company when it eventually hits their desk. This is just human nature, and I have been guilty myself. Find the right person from the get-go even if it takes more time.

3.       Do think beyond Phase 2

Plan your program as though you were taking it through market launch. It shocks me how many companies pitch their Phase 2 program with no concept of the clinical, capital, and time requirements for Phase 3 and beyond. In my opinion, every Phase I biotech company should have financially and operationally modeled their program through ten years post launch. Not only will this guide their Phase 2 operating decisions but it will also heavily influence their partnership discussions and optimal deal structures. Claiming ignorance on the matter and deferring to their potential partner impairs the chances of any partnership at all. Don’t make your partner do all the heavy-lifting.

Welcome!

Welcome to the first of many biotech blogs!