Author Archives: biopharmadeals

An Example of Financing Risk in a Microcap Biotech Stock

I previously blogged about financing risks associated with microcap biotech companies. In this post, I wanted examine a real-life example of a microcap biotech that recently had to raise capital.

On February 12th, ImmunoCellular Therapeutics (IMUC) raised approximately $14.6 million. Prior to the raise, IMUC shares were trading around $0.70/share; the stock price fell to about $0.57/share immediately after the financing – a drop of almost 20%. Should investors have known that there was a risk of getting diluted?

If you look at IMUC’s 10-Q, you see that the company had about $23.5 million in cash on September 30, 2014. The company’s historical burn rate was about $10 million a year, so by the end of 2014, IMUC would have had about 2 years of runway. Earlier in September 2014, management had announced the goal of initiating a Phase 3 trial in 2015. Management had stated that the Phase 3 trial could enroll 600 patients. The average cost for a Phase 3 cancer clinical trial is about $75,000 per patient, so the company needed approximately $45 million to fund just the Phase 3 trial. This should have raised red flags for investors.

Larry Smith had brought up concerns about financing, but the analyst covering IMUC at Roth Capital barely mentioned it. In his last note on November 14, 2014, the Roth analyst had a buy rating with a price target of $3/share. Which bank helped IMUC raise money in the last round? Roth Capital. Despite having a ‘Chinese Wall’ separating research from banking, sell-side analysts can still be hesitant to highlight a company’s risks fearing the loss of potential banking business.

Were there other warning signs? On December 11th, 2014, management filed an S-1 to try to raise $20 million. That didn’t work out so well, so IMUC tried to raise again on January 21st, 2015. This time, management wanted to raise $26.5 million but sweetened the pot with 30% warrant coverage. Again, institutional investors didn’t bite, so the company tried a third time on February 10th to raise $30.8 million with 70% warrant coverage. Ultimately, IMUC was only able to raise $14.6 million – enough to start the Phase 3 trial but not enough to complete it. Clearly, there was not much appetite from institutional investors.

What happens now that IMUC raised money? Institutional investors, such as Sabby, who received 26.65 million shares at $0.60, can now sell them anytime the price is $0.60 or more to get back what was originally invested and just keep their warrants for any upside in the future. This creates selling pressure around $0.60/share in the near-term until the institutional investors sell all of the stocks they received from the financing. Assuming half a million shares traded a day, it will take over 50 trading days for the new investors to sell all their shares. In the long-term, IMUC still has financing risk, since the company has to raise additional capital to finish its Phase 3 trial.

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This example of financing will hopefully give you an idea of some warning signs to look out for before in investing in microcap biotech stocks.

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Remember Financing Risk When Investing in Microcap Biotech Stocks

Investing in publicly-traded, early-stage, microcap biotech stocks can be very profitable. For example, if you had invested in shares of Advaxis (ADXS) in 2014 which traded at less than $4 for most of the year, you could have made at least a 75% return, as shares are now higher than $7 (at the time of this writing). However, investors can often get enamored with a technology and sometimes overlook the financial risks associated with early-stage biotechnology companies.

Since most early-stage biotechs do not generate revenue, they often have to raise capital to fund development of their pipeline products. Publicly-traded companies usually raise capital from institutional investors (i.e. hedge funds or mutual funds) in follow-on offerings. To entice institutional investors, companies will sometimes offer shares at a discount to the open market price and warrants in return for capital. When companies issue new shares to raise money, the current shareholders get diluted, and share prices typically drop.

Depending on the discount and warrants offered, there can be a near-term overhang that prevents price appreciation even after an offering is completed. While some new investors may be long-term shareholders, others will start selling shares right away, which keeps a downward pressure on the share price. For example, let’s say a stock is trading at $1.50/share and an investor receives one million shares at $1.00 and 50% warrant coverage at an exercise price of $1.00. The investor can then sell all of their shares at $1.00/share or more to get their principal back and keep the warrants (which were free) to enjoy any future increase in share price.

Before investing in early-stage biotechs, remember to take a look at the balance sheet to see how much cash is left. Management will want to have at least enough cash to last a year. A company’s past expenses will give you an idea of the burn rate, but also consider the cost of clinical trials that have yet to be initiated. Management will typically raise capital after positive news and stock price appreciation. Also, keep in mind that sell-side analysts do not always mention financing risks, because they want their investment bankers to raise capital for the company; so be wary of buy recommendations.

In a future post, I will give you an real-life example of what happens when a microcap biotech company raises money.

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Kaplan-Meier Curves with R

While Excel (and similar spreadsheet programs) are powerful, they are not really suited for survival analysis. For example, graphing Kaplan-Meier curves with Excel is less than ideal. Survival analysis will often require a statistical software package, like  SAS, SPSS, STATA, XLSTAT, etc. R is a free alternative that is widely used by academics. Be warned, the learning curve for R is steep, but the references below should be helpful.

An R script entitled KM graphs.R is provided that will allow you to graph Kaplan-Meier curves using R. You will have to download and install R (and RStudio if you like). Professor Roger Peng, at Johns Hopkins University, has an entire online course introducing R on YouTube and Coursera. This YouTube video shows you how to install R on Windows; he also has a video to install R on a Mac. You will also need to format the survival data you want to graph in a .CSV file. The file should have three columns: time to event, event occurrence, and treatment. The event occurrence and treatment columns should contain either a 0 or 1 to indicate whether the event has occurred or whether an individual received treatment, respectively. An example file entitled data.CSV is provided.

Once you have installed R, download the data.CSV file to the working directory in R and run the KM graphs.R script. You can then replace the data in the .CSV file with the data you want to graph.

References:

  1. UCLA Institute for Digital Research and Education.
  2. Use Software R to do Survival Analysis and Simulation.
  3. Survival Analysis in R (www.openintro.org).
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Option Pain Calculator in Excel

I’ve become somewhat interested in the Max (Option) Pain Theory recently.  In short, it’s a way to predict the price of a stock on a certain date using open option interest.  The theory, which has been around for a while, is based on the fact that stock prices tend to gravitate towards a point where the majority of options will expire worthless.  More detailed explanations can be found at the following Seeking Alpha article.

There are a number of online max option pain calculators: OptionPain, OptionCalc, MaxPain, MaxPa.in, Strike Pegger, etc.  Unfortunately, these online calculators do not have much historical data, so it’s difficult to determine how well the theory predicts stock prices at option expiration.  I’ve created a Max Pain calculator in Excel that allows you to enter historical option interest data to back-test how well the theory works.  For more on how Max Pain is actually calculated, see Optionetics.

From my limited analysis, the theory is somewhat useful for certain stocks.  The stocks should have a ton of open option interest like AAPL.  Not surprisingly, the theory works better as the option expiration date nears, i.e. the forecast tends to be more correct at two weeks vs. four weeks from expiration.  People (e.g. Travis Lewis at AAPLPain) are using variations on the theory to trade stocks and options successfully.

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Kaplan-Meier Curves in Excel

Clinical studies often use Kaplan-Meier (aka survival) curves to show the proportion of patients that have survived after a certain period of time.  There are a several articles that show you how to do the math:

Unfortunately, Excel does not include a function to graph Kaplan-Meier curves.  You have to reformat the data to be able to create survival curves in Excel.  Check out SCEW, an Excel add-in that allows you to create Kaplan-Meier curves.  You do not have to download the add-in if you’re willing to manually type in the spreadsheet formulas that reformats the data (see Appendix A).  Once you have reformatted the data, you can use the scatter graph function to create the Kaplan-Meier curve.  For your convenience, I have created an Excel spreadsheet on Scribd that you can use.

Update: I realized that downloading from Scribd can be inconvenient, so I’ve included a link to the Excel file on Google Drive. For the more daring, try graphing Kaplan-Meier curves with R.

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VC Financing Down for First Half of 2011

EvaluatePharma recently reported VC investments in companies developing human therapeutics (excluding diagnostics, devices, medical instruments, etc.).  A total of $1.9 million was invested in 98 deals the first half of 2011.  If this trend continues for the remainder of the year, 2011 will be the worst year for VC financing during the past five years.  For comparison, $4.5 million was invested in 270 deals in 2010.

Companies developing oncology drugs continue to attract the most of money (34% vs. 31% for 2010).  CNS companies attracted 15% of VC investments, and anti-infectives got 12%.

Unfortunately, the downward trend is not surprising considering that the VC industry itself continues to contract.  LPs want liquidity in times of uncertainty, and venture capital as an asset class is not very liquid.  Other headwinds that may be contributing to the declines VC drug investments include a conservative FDA regulatory environment, as well as Medicare reimbursement uncertainty, expanding development timelines, and increasing costs.

That being said, there’s still a ton of unmet need in the drug therapy space and a ton of very exciting technology being developed.  Hopefully, enough money will be available to commercialize these new technologies.

Portfolio Diversification: When Not to Diversify

Diversification is not always good.  It’s common sense that having more shots on goal increases the probability of making a goal.  Financial advisors will always recommend diversifying your investment portfolio to improve returns.  Keep in mind, however, that blindly diversifying your portfolio does not always reduce risk.  I’m going to use some statistics to show you.

Let’s say that you invested in Gilead (GILD) stock, and the probability that it goes up $1 is 25%.  In other words, the probability that you will make $1 is 25%:

P(G)=25%

Now, let’s say you also invested in Allergan (AGN) shares, and the probability that the stock increases by $1 is also 25%:

P(A)=25%

So if you invested in both GILD and AGN stocks, the probability that you make $1 is now:

P(G or A)=P(G)+P(A)-P(G and A);

where P(G and A)=P(G)xP(A) assuming that P(G) and P(A) are independent events

P(G or A)=25%+25%-6.25%=43.75%

In the previous example, diversifying your investments improves your odds of making $1 from 25% to 43.75%.  More often than not, however, the probability of success for different investments is not the same.  Let’s say that the probability that GILD stock increases $1 is only 5%:

P(G)=5%

Therefore, your probability of making $1 is not as good as before:

P(G or A)=25%+5%-1.25%=28.75%

In this last example, diversification does not reduce portfolio risk very much.  Keep in mind that the odds of the individual events will impact the odds of the entire portfolio before diversifying.  This is a common mistake made even by professionals.  It was “diversification” that led to the subprime crisis.  By combining a bunch of subprime home loans, bankers thought that they could reduce the risk of defaults.  Unfortunately, combining pieces of turd and putting frosting on it doesn’t make it a cake.

How To Read a Biotech Patent

Reading patents can be painful if you’re not a patent attorney.  It can be hard enough to comprehend all the science without trying to understand the legal jargon.

If you’re totally unfamiliar with patents, the USPTO patent site is a good place to start; take a look at the Concept to Protection video presentation.  Also check out Introduction to Patent Law from Fenwick & West LLP.  Brown & Michaels has a comprehensive site on intellectual property; I found the How Do I Read a Patent section very informative.  For more specific information regarding biotechnology patents, I suggest taking a look at How To Read a Biotech Patent by Carol Nottenburg.  All of these articles are helpful in understanding some of the legal terms commonly used in patents.

FDA Approval Rates

CDER NMEs CDER BLAs CBER BLAs Total
1999 35 2 3 40
2000 27 3 3 33
2001 24 6 2 32
2002 17 6 3 26
2003 21 6 8 35
2004 31 5 2 38
2005 18 2 8 28
2006 18 4 7 29
2007 16 2 8 26
2008 21 3 7 31
2009 19 6 9 34
2010 15 6 5 26
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Cancer Immunotherapies Attracting Interest

I’ve always been a bit skeptical of cancer immunotherapies, particularly the use of patients’ own immune system to target tumors. Just look at CancerVax, Cell Genesys, Favrille, and Genitope. One of the major obstacles has been eliciting a strong enough immune response to adequately treat the cancer. Another is identifying the right molecular targets to attack only the tumor cells. Nonetheless, cancer immunotherapies appear to be attracting interest according to Trading Markets.

The FDA approved Dendreon’s cancer vaccine, Provenge, last year for the treatment of prostate cancer. Dendreon’s market cap is now over $4.5 billion. More recently, Amgen acquired BioVex for its oncolytic virus, OncoVex, currently in Phase 3 trials to treat metastatic melanoma and head and neck cancer. Amgen agreed to pay up to $1 billion for BioVex depending on sales milestones. Immunocellular Therapeutics just raised $8.1 million in a PIPE to complete a Phase 2 trial for its dendritic cell vaccine, ICT-107, to treat gliobastoma.