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Continued from previous page
Research Centers as Hubs for Industry Collaboration
"As a research center we are guided by the concerns of
our 17 member companies," said Marketing Professor
George Day, co-director of the Impact Conference and
of the Mack Center for Technological Innovation, which
produced it. "We created a list of priorities by consulting
with them, asking what are their problems. We are
currently funding 36 faculty members throughout the
School, who do the research, and then communicate the
results through conferences."
The Mack Center is one of 24 research centers and initiatives
at Wharton. Each is a direct connection to industry
through the participation of supporting members, as
well as a nexus of interdisciplinary thought. Their work generates
courses, academic programs, community outreach,
published research, and partnerships among academics, government,
and industry.
Explained Day, "Wharton is fortunate to have outstanding
academic departments with vertical expertise. The research
centers are the horizontal linkages that tie them together."
"We are all active consultants and teach on programs for
executives, so we have a good sense of industry practices and
issues," he continued. "We wouldn't succeed if we didn't deliver
value to our partner companies."
Each year, each Wharton center conducts its own conferences
and members meetings, about a dozen of which
are designated Impact Conferences for their broader application.
The 2006-2007 series kicked off with "Inclusion in
the Business of Sports" in September 2006 and will continue
with "International Financial Integration" in May 2007.
In between, the conferences will cover topics from environmental
management to household investment portfolios to
urban economic development.
New Models for Innovations at Merck
The varied research that comes out of the centers highlighted
in these conferences is funded by member companies and
rooted in the business problems they face. Sometimes it is
even produced in concert with members, as faculty consulting
and research projects.
That's how Christian Terwiesch, Wharton associate professor
of operations and information management (OPIM),
ended up at the Impact Conference co-presenting with Brian
Kelly, a 1997 alumnus of the Penn Engineering Executive
Masters in Technology Management program and vice president,
business integration, at Merck & Co.
The project began three years ago through a conversation
between Kelly and Terwiesch's colleague and frequent
co-author, Karl Ulrich. The professor asked a question about
Merck's development pipeline that Kelly couldn't answer, and
the collaboration began.
The relationship, which included a research grant and access
to data from Merck, has yielded fascinating results, soon
to be published in Management Science. The paper by OPIM
doctoral candidate Karan Girotra, Terwiesch, and Ulrich
shows that when large, publicly traded pharmaceutical firms
experience a failure in Phase III drug development (the last
stage before official drug approval), there is an average decline
in firm value of $551.9 million. Substantial fixed costs
? time, manpower, and resources—mean that a late-stage
failure of a compound can be devastating to a company.
Case in point from a Merck competitor: In December
2006, when Pfizer experienced late-stage failure for its most
promising heart drug, the company's valuation plummeted.
Merck faced a similar situation in the early 2000s. After
experiencing wave after wave of scientific and commercial
success in the 1980s and 1990s, the pipeline began to dry
up. Success had created overconfidence that manifested in
inflated estimates of probability of success (POS).
In the boom decades, "most things we tried, worked," said
Kelly. "The drugs had an impact on patients and were commercially
successful, and this reinforced a bullish attitude.
When we struggled in the 2000s, we realized that we were
way too optimistic."
For drugs in various stages of development, general odds
for reaching the market are well known: 20% for drugs in
Phase I, 30% for Phase II, 60% for Phase III, and 80% for
new drug applications (NDAs).
However, those general odds are aggregates. Increasing
probability of success for each compound at each phase
would have multiplying effect on Merck's valuation.
"If you ask most people what's the difference between a
60% and 70% chance of success, they can't tell you," explained
Terwiesch. "But if you look at the expected payoff, there is actually
a 50% difference between the two. It's a big implication. So
increasing the accuracy of projections is critical."
Too often in business, he said, when someone says a
project has an 80% probability of success, it's less of a prediction
than an indication of how much they want to
do the project. And unless the accuracy of predictions is
tracked, it can't be improved.
Terwiesch and Kelly reported that their methodology
produced a substantial increase to the accuracy of
Merck's predictions.
Of course, predictions alone don't create drugs that work
? they merely improve the efficiency of the pipeline.
"A key premise is that the safety and efficacy and biopharmaceutic
properties of any compound are intrinsic," said
Kelly. "There is nothing we can do to change those properties.
The role of development is to reveal them. Success is
based on revealing those properties as soon as possible to assess
whether to take the compound to the next stage of testing.
Appropriate POS estimates are critical to inform how
much it is worth to reveal the properties."
Doing so efficiently means that sometimes potentially effective
compounds are rejected.
"If I have an imperfect but sufficiently predictive test after
Phase One, we're going to use it," said Kelly. "If you want to
improve POS, you must be willing to throw out some compounds
that are good with an imperfect test if that means
that the drugs that make it through have a higher chance of
succeeding. It will drop your cost structure."
While choosing between leads can be a thorny problem in
product development, that's less of a concern for Merck. In
pharmaceuticals, a queue is beneficial.
At earliest stage, 5,000 to 10,000 compounds are evaluated
against a "target"—the clinical indication. In the last
stage, Product Development, one to three compounds are
evaluated and zero to two compounds emerge as NDAs.
"Some years the successful products are zero, and all the
money developed to research and development goes to nothing.
We can make good decisions, and have bad outcomes."
Effective R&D strategy can make a big difference. When
pharmaceutical companies have developed a backup—a redundant
compound that could potentially serve the same
indication—they can decrease the impact of a late-stage
failure. But whether that's the right call or not depends on
the POS for each of the drugs.
"If I can only launch three things and five things are competing
and several are redundant, how do I choose?" said Kelly.
"Do I launch three of the same or diversify? If you can't estimate
dependent POS, you have no ability to make decisions."
"One of the lessons here," said Terwiesch, "is that you
can't value a drug in a vacuum." The value depends in large
part upon the company's strategy and portfolio. "Net present
value won't do it," he continued. Instead, you need to look
at how the drug fits into the overall pipeline. He and his colleagues
are working on models that will value the whole
pipeline, taking into consideration the balance of risks involved
as well as the utilization of knowledge resources.
The outcomes of the Merck/Wharton collaboration are
already finding a wider audience. The research will be included
in Ulrich and Terwiesch's upcoming book, Managing
Innovation Systems. And earlier in 2006 Wharton launched a
week-long Strategic R&D Management program for executives
under academic director Terwiesch, who developed the
curriculum in collaboration with Ulrich and INSEAD colleagues.
The course has already been offered through Executive
Education at Wharton, INSEAD, and Merck itself.
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