Transcript This paper - Knowledge, Internationalization and Technology Studies

The revolution that never arrived: Clinical and
genetic paradigms in bio-medical discovery and
the R&D productivity paradox
Michelle Gittelman
Rutgers Business School
“New Frontiers in the Economics and Management of Innovation”
KiTeS- Knowledge, Internationalization and Technology Studies
Bocconi University, Milan
March 22-23, 2012
A puzzle
The pharmaceutical industry is having trouble
filling its pipeline with new drugs – despite
doing many things “right”
 Consistent increase in R&D expenditures
 Much more basic science and genetics in drug
discovery
 Increased use of analytical informatics
 Deeper division of innovative labor and active
markets for technology, fueled by
entrepreneurial firms spun off from universities
A puzzle
The pharmaceutical industry is having trouble
filling its pipeline with new drugs – despite
doing many things “right”
ent increase in R&D expenditures
Much industry
more basic science
and genetics
drug
“The
is doomed
if weindon’t
discovery
change”
Chairman
of
Eli
Lilly,
Increased use of analytical informatics
2007
eper division of innovative labor anmarkets for
technology, fueled by entrepreneurial firms spun
off from universities
This paper
Describe research paradigms and historical
shifts in the institutional landscape of biomedical research
We study biotech as a “revolutionary” paradigm. What
did it replace?
Genomics (1980s-present) – locus of discovery is
the lab
Patient-Oriented Clinical Research (POR) (1940s1970s) – locus of discovery is the hospital
Genomics discovery paradigm: Bench to bedside
DNA mutation associated
with pathology
Targets in cells
Design a drug to bind
to target
Clinical discovery paradigm: Bedside to bench
Observe perturbations in humans
(e.g. unexpected reaction to a drug)
Test treatment
experimentally
Theorize disease
mechanisms
Competing discovery paradigm
Experiential vs. theory-driven search
 Rooted in ancient debates between Plato and
Aristotle on the role of pure reason and
experiential learning in advancing knowledge
 Key issue in current debates in medical policy on
translational research and systems biology
 A central question in organizational learning
literature (Arora & Gambardella, 1994; Gavetti and Levinthal, 2000;
Nelson, 2003, Fleming and Sorenson, 2004)
This paper: framing the issue
 Compare two research paradigms as different
epistemologies of discovery – different beliefs
about the best way to find new medicines
 Describe the institutional history of clinical
research in biomedicine in the USA
 Review the secondary evidence on discovery
outcomes
 Suggest that productivity is linked to search
paradigms – much more research needed here!
Search logics
Experiential
Abstract
Type of search/Search routines
Search logics
• Theory-driven,
predictive logic
• Fundamental
cause-effect
understandings
• “Offline
experimentation”
Abstract analytical
models
Experiential
Abstract
Type of search/Search routines
Search logics
• Feedback-based,
backward looking
• Knowledge of how
objects work
• “Online
experimentation”
• Theory-driven,
predictive logic
• Fundamental
cause-effect
understandings
• “Offline
experimentation”
Real-world objects in
real-world contexts
Abstract analytical
models
Experiential
Abstract
Type of search/Search routines
Search logics when problems are complex
“A striking characteristic
of fields where
technological advance
has been rapid is that
they all seem to be
closely connected to a
powerful applied science
or engineering
discipline”
Nelson, 2003
Experiential
Abstract
Type of search/Search routines
Search logics when problems are complex
“A striking characteristic
of fields where
technological advance
has been rapid is that
they all seem to be
closely connected to a
powerful applied science
or engineering
discipline”
Nelson, 2003
Experiential
When complexity is
high, theory-driven,
predictive search
yields better
discovery outcomes
than experiential
learning
Arora & Gambardella
(1994), Fleming & Sorenson
(2004), Gavetti and
Levinthal (2000)
Abstract
Type of search/Search routines
Search logics: framing genomics
Trial-and-error
Blind search
Random screening of
compounds
Genomics
Rational drug design
Experiential
Abstract
Type of search/Search routines
1980s/1990s: genomics was presented as a
“silver bullet” in drug discovery
 In 1990, Congress approved ~$3 billion funding of the
Human Genome Project to sequence the entire human
genome with the promise that the knowledge would
translate to a wave of new “rationally designed” drugs
 Genomics firms were founded to turn genetic information
into drugs (Human Genome Sciences, Celera, Millenium,
Incyte)
 Scientific entrepreneurship by “star scientists” core to the
model (Zucker and Darby, 1998).
 The model attracted billions in funding from private
investors and Wall Street hoping to capitalize on the
promise of rational drug discovery
Incyte is based in Palo Alto, Calif., deep in
Silicon Valley, and it is no coincidence that the
heart of its headquarters is a vast, glassenclosed room full of powerful computers. ''At
the end of the day, it's the information that
matters,'' said Randy Scott, the president and
chief scientific officer. ''We are all about the
application of Moore's Law to biology,'' he said
-- a reference to the observation that computer
processing power doubles every 18 months.
Applying that exponential growth to genomics
should produce similar gains for drug
discovery, Dr. Scott said.
Incyte is based in Palo Alto, Calif., deep in
Silicon Valley, and it is no coincidence that the
heart of its headquarters is a vast, glassenclosed room full of powerful computers. ''At
the end of the day, it's the information that
matters,'' said Randy Scott, the president and
chief scientific officer. ''We are all about the
application of Moore's Law to biology,'' he said
William Haseltine, Founder, Human Genome Sciences
-- a reference to the observation that computer
processing power doubles every 18 months.
Applying that exponential growth to genomics
should produce similar gains for drug
discovery, Dr. Scott said.
“Death is a series of preventable
diseases”
Search logics: framing genomics
Trial-and-error
Blind search
Random screening of
compounds
Genomics
Rational drug design
Experiential
Abstract
Type of search/Search routines
Search logics: framing genomics
Patient-oriented Clinical
Genomics
Research (POR)
Rational drug design
Experiential
Abstract
Type of search/Search routines
Patient-oriented clinical research
 “Research performed by a scientist and a human
subject working together, both being warm and
alive” (Schechter, 1998)
 Rejects the idea of disease causality as a useful
starting point for drug discovery
 Causal understanding is not useful in finding
treatments.
 A dominant paradigm in bio-medicine in post-
War USA, spurred by the federalization of
research (NIH)
Different predictive logics in science
[T]here remains a real problem about the relevance of
many model systems, and the inability of many to
understand that in biology, unlike physics, we don’t
have great general laws or large forces operating
that allow us to work from the bottom up in terms
of clinical prediction
Rees, Jonathan. 2002. “Two Cultures?” J Am Acad
Dermatol, 46:313-6.
Different predictive logics in science
The great physicist-turned biologist Leo Szilard said that
once he changed fields (no pun intended) he couldn’t enjoy
a long bath as he could when he could dream abstract
physics in the bath.
As a biologist he was always having to get out to check on
some annoying little fact. It is the problem of predicting
across several levels of biologic explanation, and the
absence of the all encompassing general laws in
biology, that accounts for the fact that most clinically
relevant discoveries come from the clinic rather than
the laboratory and not, contrary to what many believe,
vice versa.
Rees, Jonathan. 2002. “Two Cultures?”
Bedside-to-bench discoveries in medicine
 The link between cholesterol and heart disease, which
culminated in the development of statins in the 1980s,
originated in experiments conducted in 1913, when the Russian
scientist Nikolai Anichkov unexpectedly observed that rabbits
fed high-fat diets developed atherosclerosis.
 The treatment for pernicious anemia was discovered from the
mechanistic insight that feeding patients liver cured them – the
underlying vitamin deficiency (b12), identified decades later,
was one of many complex causes
Bedside-to-bench discoveries in medicine
 Observations of surgical patients receiving a new sedative
resulted in the unexpected finding of marked decreases in
hallucinations and delusions among psychotic patients. The
discovery of an effective treatment for psychosis subsequently
facilitated new theories of brain activity associated with
schizophrenia.
 Fundamental discoveries for the treatment of sickle-cell anemia
were triggered by the bedside observations of clinical
researchers, who noticed that some populations (infants and
certain ethnic groups) showed irregularities in disease
rates. Later discoveries of the underlying genetic
manifestations of the disease were motivated by models
developed through earlier clinical research.
Early history: application of scientific
principles to medicine
 In the 19th century, medical education carried
out in for-profit schools taught by practicing
doctors with no scientific training
 1910: Two landmarks
 Flexner report - teaching-oriented medical schools,
housed in universities, full-time university faculty.
Medical education based on the European model.
 Rockefeller Institute Hospital founded to foster
clinically-driven medical discovery
Organizing POR: Rockefeller Institute
(1901) and Rockefeller Hospital (1910)
 First institution to combine
laboratory and clinical work to
find treatments for major
infectious diseases of the day.
 Cosmopolitan, open culture,
attracted top scientists from
Europe
 Unique scientific climate:
Diverse specialization;
transdisciplinary - no
departmental divisions; minimal
control by administrators
Bedside to bench learning at
Rockefeller
“Simon Flexner, the first director of the
Rockefeller Institute, conceived of the Rockefeller
Hospital as a test site for the bright ideas
generated in the Institute’s laboratories. In
fact, this has happened only rarely. During my 40
years at Rockefeller Hospital, I recall only one
instance in which a laboratory observation by
biochemists was turned into a testable
hypothesis in patients. Indeed, the traffic of
ideas often runs the other way”
Ahrens, Crisis in Clinical Research
Organizing POR: The NIH Clinical Center
(1955) and GCRC network
 Modeled on the
Rockefeller Institute –
10x larger: 500 beds
 Victory over science
policy czar Vannevar
Bush, who promoted
government funding of
basic research, not
medical resaerch
 A model for a network
of clinical sites in AMCs
The bedside as the locus of discovery
Scientifically, the most important asset of a POR facility is the
golden opportunity it provides for medical investigators and
their staffs to watch carefully and to think deeply about the
medical challenges posed by their patients; this forces them
to formulate new hypotheses and to devise new stratagems
for attacking unsolved problems. There is time to ponder
an unexpected event – an unexplained turn in the course
of the disease or a puzzling response to a medication –
and thus to obtain fresh insights into a disease or a
manipulation under study.
Ahrens, “The Crisis in Clinical Research”
1970s-80s: Decline in clinical
research
1200
1000
800
600
400
200
No. of centers
No. of Funded Beds
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1966
1964
1962
1960
0
Two (three) factors accounting for
the decline in POR
Eroding
Declining
institutional
career
and financial
opportunities
support for
for young PIs
Emergence of POR
genomics as a
dominant
discovery
paradigm
Changes in healthcare delivery
Decline of POR: Career pressures
Publications in the Journal of Clinical investigation,
1969-1999
100%
Animal
study
90%
80%
70%
60%
NonGCRC
study
50%
40%
30%
GCRC
study
20%
10%
0%
1969
1999
Source: Robertson and Tung, 2001
The Promise of Biotechnology, ca. 1980
The Promise, ca. 2012
Genomics and basic science in
medicine
 Now acknowledged that genomics has been a
bonanza for science but not for medicine. Few new
drugs have emerged from the paradigm.
 Recent study at Brigham: 101 genetic markers that
have been statistically linked to heart disease were
shown to have no value in forecasting disease
among 19,000 subjects followed for 12 years; a
more valid predictor was the old-fashioned
method of a family history
Basic science and firm-level
innovation
 Genomics as a business model has failed –
major firms sell diagnostics tests and home kits
 $100+ billion invested in the biotech industry –
never made money
 Growing empirical evidence that “star” scientists
have a negative impact on firm-level
innovation: nonstars and scientists in applied
fields have a positive impact on performance in
biopharmaceuticals (Baba et al, 2009; Breschi and Catalini, 2010,
Gittelman and Kogut, 2003, Rothermel and Hess, 2007, Toole and Czarnitzky,
2009, Zucker and Darby, 2001)
Concluding remarks
 Science is not homogenous – enormous
variation in search logics
 Experimentation vs. theory-driven logics
 Real world vs. reductionist methods
 We need to pay more attention to field-specific
differences in explaining science-technology
links
 Experiential learning important for complex problems
 Almost NO empirical research on the clinical
paradigm in medical discovery – a rich terrain
for future research
Thank you!
1. Identify and define medical needs
2.
Research on disease mechanisms
3. Identify and validate targets involved in
disease processes
4.
Search for lead compounds that interact with
target
5.
6.
Optimize the properties of the lead
compounds to generate drug molecules
Drug development and pre-clinical studies (in
vitro and in vivo)
Genomics as a rational approach to
drug discovery
Rational design of molecules is gradually replacing random,
trial-and-error experiments. . . Growth of scientific
understanding in molecular biology and genetic
engineering has clarified important aspects of human
metabolism and the chemical and biological action of drugs.
. . By studying the structure of receptors, scientists can
design (typically on computer) a theoretical compound that
matches a given receptor site, and is expected to counter a
certain pathology.
Arora and Gambardella, The changing technology of technological change, Research
Policy, 23 (1994)