After a session at the recent Wisconsin Early Stage
Symposium, I was talking with an investor from Indiana and explained to him that I analyze biotechnology. He then asked me the $64,000 question every
investor would like to know--how do I determine if an early stage biotechnology
will be successful?
It is a great question but, I submit, the wrong one to ask
because there are no unambiguous or concrete criteria one can use to determine if
a promising technology will succeed scientifically. On the other hand, one can look for warning flags
that provide a measure of the risk of failure of that technology. Therefore, a better question to ask is this:
are there reasons that a particular technology might not succeed. By asking the
question this way, you avoid the impossible task of trying to predict success, and
instead you look to reduce risk, thereby, increasing your chance of success by
investing in technologies with lower chance of failure.
Invariably, when considering a promising technology at this
early stage of development, the investor is presented with very exciting laboratory
and maybe animal studies. Also, the
inventor invariably claims that his product has tremendous market potential and
there may be a lot of press hype around this (remember interferon?).
The savvy investor does his due diligence and makes his own
assessment of the market potential, the business plan, company structure,
etc. All of these are certainly important
considerations, but even with the best structure, financing and business plan
in place, the whole enterprise ultimately rests on the success of the technology,
which, at this stage, is not fully tested.
Let me turn to a case study to illustrate the technological pitfalls
that can derail even the most promising science.
A case study of an
anti-cancer therapy
Several years ago, a colleague published very exciting results
showing that a simple plant oil—the oil that makes oranges taste “orangey”--could
both, prevent and cure, advanced breast cancer in rats. Better yet, the compound, perillyl alcohol,
or POH, showed no toxicity in the animals. POH already was approved for human consumption as a food flavoring, was cheap
to produce and readily available, so there was high hope that POH would become
the first cancer chemotherapy and chemoprevention agent devoid of side effects.
Laboratory studies showed that POH stops cancer cells from
growing and causes them to self-destruct. Studies in the rat breast cancer model confirmed this and further revealed
that normal tissues were not affected. Other
research suggested that POH interfered with a biochemical pathway that often is
abnormal in human breast cancer. All of these
pieces of evidence fit into a convincingly coherent picture of an exciting and
novel anti-cancer agent. Based on these
findings, clinical trials began.
The early phase I trial revealed that in humans, POH is
metabolized precisely as it was in rats and also confirmed that POH was
non-toxic in humans. These results added
to the enthusiasm for the product.
Phase II trials were then undertaken in attempt to treat human
breast cancer. In these trials, POH
showed no anti-cancer effect at all and it was removed from the experimental
therapeutic pipeline. What went
wrong?
What are the lessons to be learned?
The first lesson from the POH failure is this: It always is risky to extrapolate experimental
results from rodents to humans. Simply because
a rodent malignancy occurs in the same tissue as human cancer does not mean
that it is the same type of cancer in both species. Rodent cancer models, like the one employed in
the POH experiments, use genetically homogeneous inbred animals and the experimental
cancer arises from a single, artificial genetic cause. In contrast, human cancers occur in a
genetically diverse population and are initiated by many different genetic
events. Thus, there is significant risk
of failure when human trials are based on the results of a single animal disease
model.
Second, the mechanism of action of POH was insufficiently
established before the clinical trials were initiated. The data were not adequately repeated and
were weak to begin with. In fact, while
the clinical trials were underway, another lab found that POH actually affects
a completely different biochemical mechanism than originally believed—the
original results were wrong. Importantly, the correct mechanism of POH anti-cancer
activity may only be relevant for a small subset of human breast cancers and
more important in other malignancies.
Since the proper mechanism of action of POH was not accurately
established and the rat cancer model was inadequate to generalize to human
breast cancer, the human trials were not targeted for the appropriate malignancy
and, thus, doomed to fail.
Yet, the risks of failure were discernable before the POH clinical
trials began—critical laboratory data were weak, the rat cancer model was too
narrowly focused and untested, and the clinical trials were initiated too
early. These warning flags could have
been picked up by an objective reviewer who understood the science.
I sometimes am called upon to evaluate the science behind products
and technologies at a similar stage of development as POH was when it entered
clinical trials—that is, the technology shows great promise based on lab and animal
studies, but no one knows if it will work in humans. This is a high-risk, make-or-break juncture
in the long process of taking a science idea to market.
The difficulty in identifying the warning flags at this
critical stage of development is that each technology will have its own unique warning
flags that portend possible failure. Furthermore, there likely are as
many or more different types of warning flags as there are technologies to be
developed.
Therefore, the first, and obvious, requirement in any technology
analysis is to seek the input from a professional who has good knowledge of the
science. But, doesn’t this beg the
question, who has better understanding of the technology than the scientists
who developed it and aren’t they already telling you it is sound?
This brings me to the second, and equally important
requirement for any technology analysis—it must be objective.
An objective, informed opinion is critical for thorough due
diligence and I submit this is almost impossible to do by a non-scientist, or even
by a scientist who is invested in the success of the technology. It is as hard to realistically see flaws in
one’s pet project as in one’s own children.
Therefore, for thorough due diligence, make sure to obtain
technical analysis from a knowledgeable scientist who has no ties to the
technology or the company. And be sure
to ask that objective expert to evaluate the risk of failure, rather than the
chance for success.
This article was originally published in the Wisconsin Technology Network Newsletter
+++++++++++++++++++++++++++++++
Steven S. Clark,
Ph.D., a former professor and medical researcher at the University of Wisconsin School of Medicine provides consulting services
for investors and biotechnology companies. He encourages contributions to this page. Email him with story pitches.
________________________________________________________________________________________
© 2008 Steven S. Clark, PhD. All Rights
Reserved.
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