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2
The Current Landscape
Important Points Highlighted by Individual Speakers
· Genomic information has great potential to identify new path-
ways involved in complex diseases, suggest new therapeutic
targets, evaluate adverse drug effects, and identify populations
for which a drug is most effective or has the least deleterious
effects.
· Pharmaceutical and biotechnology companies have integrated
genomics-based strategies for drug discovery, but this has
largely not been translated into late-stage development.
· The cost of therapeutic development has increased significantly
over the past few decades while the success rate has remained
unchanged, and many drug failures often occur after large
investments have been made.
· While targeted therapeutics may decrease market size, overall
market share may increase, leading to a significant potential
advantage for developing stratified medicines.
· Commercial and marketing organizations may need to be
aligned with research and development in order to develop a
successful commercial model for targeted therapeutics.
5
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6 GENOME-BASED THERAPEUTICS
GREAT EXPECTATIONS
The advent of the genomic era generated great expectations for drug
discovery and development, said Geoffrey Ginsburg of Duke University.
Genomic information was expected to provide insights into the underlying
biological mechanisms of disease and to highlight biological targets and
pathways that would be amenable to new drug discovery. It indicated an
approaching ability to stratify populations based on genomic-based bio-
markers, leading to better clinical development programs. Genomic data
would reveal how individuals might respond to, be resistant to, or have
adverse effects from a drug, creating the potential for personalized medi-
cines. As a result of these and other changes, genomic data would increase
the efficiency of drug discovery and development, increase the success rate
of new drugs, enhance safety, and decrease costs.
The genomic era has made major strides toward delivering on these
promises, Ginsburg said. Several genomics-enabled products have been
approved in recent years or are in development for use, including three
that are described in Chapter 3 of this report: crizotinib for the treatment
of non-small-cell lung cancer, pomaglumetad methionil for schizophrenia,
and ivacaftor for cystic fibrosis. In addition, academicindustry partner-
ships have formed to leverage a deep understanding of disease biology
from the academic realm and to meld that to product development and
commercialization in industry. Precompetitive collaborations, such as the
European Innovative Medicines Initiative and programs sponsored by
the National Center for Advancing Translational Sciences (NCATS) at the
National Institutes of Health (NIH), have sought to lay the groundwork
for new therapeutics.
CURRENT USE AND POTENTIAL
Nicholas Davies from PricewaterhouseCoopers (PwC) elaborated on
the potential and current use of genomic-based drug discovery and devel-
opment during his presentation in the workshop's initial session. The effi-
ciency and quality of research inputs have undergone huge improvements.
The cost of DNA sequencing has dropped by many orders of magnitude
and continues to drop. The ability to find targets, screen compounds, and
generate chemical libraries is immense. The development of companion
diagnostics has made it possible to target patient subpopulations that would
be expected to benefit from a specific treatment. As Mark Trusheim from
the Sloan School of Management at the Massachusetts Institute of Technol-
ogy added, in this way patients and providers have more and better treat-
ment options, regulators gain a better sense of risk-benefit comparisons,
drug and diagnostic innovators generate more products and profits, and
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THE CURRENT LANDSCAPE 7
payers spend less on ineffective therapies. "We see opportunities not just for
developers and patients, but for everyone in the cycle. . . . It has to work
for everyone or it is not going to work at all as a system."
Both Ginsburg and Davies said that a genomic-based approach con-
tinues to have tremendous potential. For example, a recent analysis of
genome-wide association studies (GWAS) found that such studies can reveal
new pathways involved in complex diseases and suggest potential therapeu-
tic options that had not previously been considered for those indications
(Collins, 2011). This analysis also suggested that the off-target or adverse
effects of those drugs could be monitored through the analysis of genes
discovered through these unbiased genome-wide approaches.
Garret FitzGerald of the University of Pennsylvania added that it has
already been demonstrated that genetic information can be used to evalu-
ate adverse drug effects. Studies designed specifically to determine whether
particular gene variants can be used to identify individuals at particular risk
have been successful for both lumiracoxib and abacavir and required only
very small numbers of study participants to do so.
According to recent data from the U.S. Food and Drug Administration
(FDA), more than 110 marketed drugs have pharmacogenetic bio markers
on the label (see Table 2-1),1 and the need for further drugs developed
through a genomic-based approach remains strong. As Trusheim observed,
many major drugs, including hypertension drugs, heart failure drugs, anti
depressants, cholesterol drugs, and asthma drugs, are ineffective for large
portions of the population (Spear et al., 2001). Furthermore, ineffective ther-
apies cause substantial harm. Medication-related health problems account
for an estimated 3 to 7 percent of hospital admissions ( Pirmohamed et al.,
2004), and 15 percent of patients experience an adverse drug reaction dur-
ing hospital stays. An important consequence of these adverse reactions is
heightened patient noncompliance.
Oncology has made the most progress in developing personalized medi-
cine (defined in Box 2-1), Davies said, but genomic-based research is also
starting to make progress on diseases of the cardiovascular system, central
nervous system, and immune system. Metabolic, respiratory, and viral dis-
eases also are starting to yield to this approach, though progress has been
slower than expected.
Pharmaceutical companies and biotechnology companies are striving to
modernize their drug discovery and development processes. Davies pointed
to data from the Tufts Center for the Study of Drug Development (Tufts,
2010) showing that 100 percent of surveyed companies are using a discov-
ery strategy that involves a genetic or genomic approach. Thirty percent
1 For an up-to-date listing of these drugs, see http://www.fda.gov/Drugs/ScienceResearch/
ResearchAreas/Pharmacogenetics/ucm083378.htm.
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8 GENOME-BASED THERAPEUTICS
TABLE 2-1 Pharmacogenomic Biomarkers in Drug Labels
Drug Therapeutic Area Biomarker
Abacavir Antivirals HLA-B*5701
Aripiprazole Psychiatry CYP2D6
Arsenic Trioxide Oncology PML/RAR
Atomoxetine Psychiatry CYP2D6
Atorvastatin Metabolic and Endocrinology LDL receptor
Azathioprine Rheumatology TPMT
Boceprevir Antivirals IL28B
Brentuximab Vedotin Oncology CD30
Busulfan Oncology Ph Chromosome
Capecitabine Oncology DPD
Carbamazepine Neurology HLA-B*1502
Carisoprodol Musculoskeletal CYP2C19
Carvedilol Cardiovascular CYP2D6
Celecoxib Analgesics CYP2C9
Cetuximab (1) Oncology EGFR
Cetuximab (2) Oncology KRAS
Cevimeline Dermatology and Dental CYP2D6
Chlordiazepoxide and Psychiatry CYP2D6
Amitriptyline
Chloroquine Anti-Infectives G6PD
Cisplatin Oncology TPMT
Citalopram (1) Psychiatry CYP2C19
Citalopram (2) Psychiatry CYP2D6
Clobazam Neurology CYP2C19
Clomiphene Reproductive and Urologic Rh genotype
Clomipramine Psychiatry CYP2D6
Clopidogrel Cardiovascular CYP2C19
Clozapine Psychiatry CYP2D6
Codeine Analgesics CYP2D6
Crizotinib Oncology ALK
Dapsone Dermatology and Dental G6PD
Dasatinib Oncology Ph Chromosome
Denileukin Diftitox Oncology CD25
Desipramine Psychiatry CYP2D6
Dexlansoprazole (1) Gastroenterology CYP2C19
Dexlansoprazole (2) Gastroenterology CYP1A2
Dextromethorphan and Neurology CYP2D6
Quinidine
Diazepam Psychiatry CYP2C19
Doxepin Psychiatry CYP2D6
Drospirenone and Ethinyl Reproductive CYP2C19
Estradiol
Erlotinib Oncology EGFR
Esomeprazole Gastroenterology CYP2C19
Everolimus Oncology Her2/neu
Exemestane Oncology ER &/PgR receptor
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THE CURRENT LANDSCAPE 9
TABLE 2-1Continued
Drug Therapeutic Area Biomarker
Fluorouracil Dermatology and Dental DPD
Fluoxetine Psychiatry CYP2D6
Fluoxetine and Olanzapine Psychiatry CYP2D6
Flurbiprofen Rheumatology CYP2C9
Fluvoxamine Psychiatry CYP2D6
Fulvestrant Oncology ER receptor
Galantamine Neurology CYP2D6
Gefitinib Oncology EGFR
Iloperidone Psychiatry CYP2D6
Imatinib (1) Oncology C-Kit
Imatinib (2) Oncology Ph Chromosome
Imatinib (3) Oncology PDGFR
Imatinib (4) Oncology FIP1L1-PDGFR
Imipramine Psychiatry CYP2D6
Indacaterol Pulmonary UGT1A1
Irinotecan Oncology UGT1A1
Isosorbide and Hydralazine Cardiovascular NAT1; NAT2
Ivacaftor Pulmonary CFTR (G551D)
Lapatinib Oncology Her2/neu
Lenalidomide Hematology Chromosome 5q
Letrozole Oncology ER &/PgR receptor
Maraviroc Antivirals CCR5
Mercaptopurine Oncology TPMT
Metoprolol Cardiovascular CYP2D6
Modafinil Psychiatry CYP2D6
Nefazodone Psychiatry CYP2D6
Nilotinib (1) Oncology Ph Chromosome
Nilotinib (2) Oncology UGT1A1
Nortriptyline Psychiatry CYP2D6
Omeprazole Gastroenterology CYP2C19
Panitumumab (1) Oncology EGFR
Panitumumab (2) Oncology KRAS
Pantoprazole Gastroenterology CYP2C19
Paroxetine Psychiatry CYP2D6
Peginterferon alfa-2b Antivirals IL28B
Perphenazine Psychiatry CYP2D6
Pertuzumab Oncology Her2/neu
Phenytoin Neurology HLA-B*1502
Pimozide Psychiatry CYP2D6
Prasugrel Cardiovascular CYP2C19
Pravastatin Metabolic and Endocrinology ApoE2
Propafenone Cardiovascular CYP2D6
Propranolol Cardiovascular CYP2D6
Protriptyline Psychiatry CYP2D6
Quinidine Antiarrhythmics CYP2D6
Rabeprazole Gastroenterology CYP2C19
continued
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10 GENOME-BASED THERAPEUTICS
TABLE 2-1Continued
Drug Therapeutic Area Biomarker
Rasburicase Oncology G6PD
Rifampin, Isoniazid, and Anti-Infectives NAT1; NAT2
Pyrazinamide
Risperidone Psychiatry CYP2D6
Sodium Phenylacetate and Gastroenterology UCD (NAGS; CPS; ASS;
Sodium Benzoate OTC; ASL; ARG)
Sodium Phenylbutyrate Gastroenterology UCD (NAGS; CPS; ASS;
OTC; ASL; ARG)
Tamoxifen Oncology ER receptor
Telaprevir Antivirals IL28B
Terbinafine Antifungals CYP2D6
Tetrabenazine Neurology CYP2D6
Thioguanine Oncology TPMT
Thioridazine Psychiatry CYP2D6
Ticagrelor Cardiovascular CYP2C19
Tolterodine Reproductive and Urologic CYP2D6
Tositumomab Oncology CD20 antigen
Tramadol and Acetaminophen Analgesics CYP2D6
Trastuzumab Oncology Her2/neu
Tretinoin Dermatology and Dental PML/RAR
Trimipramine Psychiatry CYP2D6
Valproic Acid Psychiatry UCD (NAGS; CPS; ASS;
OTC; ASL; ARG)
Vemurafenib Oncology BRAF
Venlafaxine Psychiatry CYP2D6
Voriconazole Antifungals CYP2C19
Warfarin (1) Hematology CYP2C9
Warfarin (2) Hematology VKORC1
SOURCE: U.S. Food and Drug Administration.
BOX 2-1
Definition
"Personalized medicine" or "stratified medicine," as used by speakers in the
workshop, refers to the use of an individual's characteristics, including genetic
information, to guide medical decisions regarding prevention, diagnosis, and
treatment of disease. This tailoring of medical treatments is based on the ability
to classify individuals into subpopulations so that they can benefit from the most
efficacious treatments or interventions or be spared from expense or deleterious
side effects.
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THE CURRENT LANDSCAPE 11
require that all their compounds have an associated biomarker before
going into clinical development. More than 80 percent of companies have
established strategic partnerships related to personalized medicine, and
half have collected DNA samples from clinical trial participants. In addi-
tion, companies that have developed genomic and diagnostic technologies
have recently been acquired by other companies, suggesting that these
approaches continue to be viewed favorably. However, Davies said, in large
part these methods are not being employed in late-stage development due to
a reluctance on the part of pharmaceutical companies to enable genomic- or
genetic-based trials.
One concern about targeted drugs, Trusheim said, has been that they
will have smaller markets and therefore attract less investment. But higher
efficacy for targeted groups can in fact yield more market share and help
minimize the overall reduction in market size (Figure 2-1; Trusheim et al.,
2007). Underserved patients may enter the market and look for treatment
Empirical Stratified
medicine medicine
a
Market size (units)
e
Diagnostic Patient
targets compliance
patients d improves
Underserved
patients enter
b c
Preferred
therapy for
targeted patients
Market share (%)
FIGURE 2-1 A number of factors influence the market potential for targeted thera-
Figure
peutics with the prospect of reduced 2-1.eps
market size leading to increased market share.
NOTE: As defined by Trusheim et al. (2007), an empirical medicine, as opposed to a
stratified medicine, is not developed based upon the characteristics of an individual
or a subpopulation of individuals. These medicines are based on overall population
response and may work for a large or a small amount of individuals without using
(either because it is not necessary or one is not available) a methodology to identify
which groups may respond.
SOURCE: Trusheim et al., 2007.
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12 GENOME-BASED THERAPEUTICS
if they are more confident that a treatment will work for them. In addition,
providers may be more confident to prescribe a drug, especially since pos-
sible side effects are outweighed by the benefits. If biomarkers can separate
those who will respond from those who will not, a drug will perform much
better in the response group, potentially leading to quicker adoption, better
patient compliance, more market share, and a higher price premium. This
can produce a "niche buster" where the clinical performance of the drug
and diagnostic drives commercial performance. For example, a study of
the use of trastuzumab and panitumumab in cancer and bapineuzumab in
Alzheimer's disease showed a substantial potential economic advantage to
using stratified-medicine strategies (Trusheim et al., 2011).
A final consideration in the adoption of personalized medicine, Davies
said, is that cost-effective and outcomes-driven therapy will be critical in
the future as health care changes. Care will become more preventive, and
medicine in general will be more patient-centric. Cost control and value in
outcomes will be increasingly important focuses. New therapies may need
to be cost neutral, in that they make up for the additional expense of the
therapy through reduced costs elsewhere, whether hospital readmissions,
surgery, or some other form of care.
THE ECONOMIC CHALLENGE
Genomic-based approaches are an area of promise in an otherwise
troubled industry. The success rate for new drugs in the pharmaceutical
industry--with success defined as the ability to identify a compound that
will be approved and be commercially successful--has remained more or
less constant over the last few decades, with occasional upticks, Ginsburg
noted (Mullard, 2012). On average, fewer than 1 in 10 compounds enter-
ing preclinical testing will be successful. Furthermore, as Davies observed,
failures often occur after large investments have been made. In 2010,
45 separate drugs failed in Phase III clinical trials, with the average cost for
a Phase III trial being about $100 million. Meanwhile, patents are expir-
ing on profitable drugs, which is further reducing resources. The costs of
failures add to development expense and decrease the willingness to invest
in the process.
Because of declining productivity, more resources have been needed to
produce a constant level of new drugs. According to an analysis in Nature
Reviews Drug Discovery, productivity in the pharmaceutical industry, mea-
sured in terms of output per billion dollars spent, has been decreasing
logarithmically (Figure 2-2). This declining productivity has become known
as "Eroom's law." "Eroom" is "Moore" spelled backward, and the name
is meant to imply a backward version of "Moore's law," the observation
made by Intel co-founder Gordon Moore in 1965 that the number of
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THE CURRENT LANDSCAPE 13
Number of Drugs per Billion US$
FDA tightens
100 regulation
post-thalidomide
R&D Spending
FDA clears backlog
following PDUFA
10 regulations plus small
bolus of HIV drugs
1.0
First wave of
biotechnology-
derived therapies
0.1
1950 1960 1970 1980 1990 2000 2010
FIGURE 2-2The number of new drugs approved per billion dollars spent has
declined steadily on a logarithmic scale for more than a half-century.
Figure 2-2.eps
NOTE: FDA, U.S. Food and Drug Administration; HIV, human immunodeficiency
virus; PDUFA, Prescription Drug User Fee Act; R&D, research and development.
SOURCE: Scannell et al., 2012.
components in integrated circuits was doubling approximately every year.
In the pharmaceutical industry, the output per billion dollars spent has
consistently decreased by half every 9 years since 1952.
To remain in the pharmaceutical business, companies and investors
need to make money. But the return on capital investment is diminish-
ing to the point that the existing financial model is no longer sustainable,
Davies said. The average return on capital after 5 years' sales is currently
about $75 million per billion dollars invested, which is clearly not sustain-
able. A recent report in Forbes magazine estimated that some companies
are spending upward of $12 billion per launched product (Herper, 2012).
As FitzGerald noted, "catastrophe rather than opportunity usually drives
radical change . . . and this model is about to change."
According to Davies, the pharmaceutical industry invested an esti-
mated $125 billion in research and development across the industry
(Hewitt et al., 2011). An estimated 5 percent of this amount was spent
specifically on genetic and genomic research, or about $6 billion includ-
ing partnerships, acquisitions, and internal research. Companies have
slightly different levels and strategies of investment, with some invest-
ing more heavily in internal research and some more heavily in external
research. As discussed later in this summary and in a prior Roundtable
on Translating Genomic-Based Research for Health workshop (IOM,
2011), academic partnerships have become popular, though ways of esti-
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14 GENOME-BASED THERAPEUTICS
mating the value generated by these partnerships remain rudimentary.
"Pharma[ceutical companies] and academia need to understand how to
work together more effectively and demonstrate that they generate value
from [partnering]," Davies said.
CHALLENGES FOR GENOMIC-BASED APPROACHES
Despite its promise, a genomic-based approach to drug discovery and
development is surrounded by great uncertainties, as noted by each of the
speakers in the workshop's opening session. As FitzGerald pointed out,
genomic testing must be shown to influence clinical outcomes to guaran-
tee reimbursement. Adoption will also require substantial physician and
patient education, a financial incentive for test development, and patent
protection. Davies observed that oncology has been the poster child for a
molecular approach to target discovery, diagnosis in the clinic, develop-
ment of companion diagnostics, and treatment. However, these therapies
tend to be expensive, making their value in general medicine uncertain.
Furthermore, outside oncology, the value of targeted therapies for the
most part remains to be determined. In addition, regulatory constraints are
getting tighter, which is an issue for thinking about innovative approaches
to bringing medicines to market with companion diagnostics or a targeted
approach.
In general, Davies continued, the commercial model for the develop-
ment of personalized medicines remains immature, with the commercial
and marketing organizations within industry retaining a preference to go to
market with a more general molecule than with a targeted therapeutic. An
analysis by PwC estimates that the companion diagnostic market will reach
$42 billion by 2015.2 "There is a huge market for companion diagnostics,"
Davies said, "but they are culturally and from a time perspective [off]-kilter
with the development cycle and culture of the research and development
industry."
Trusheim added that there are countervailing forces at play. Developing
both a drug and a diagnostic can take longer, especially given the need to
recruit targeted patient pools and synchronize development of the diag-
nostic; the resulting market may be smaller than for a more general drug;
and developers face an increased risk of failure since the drug approval is
dependent upon simultaneous approval of the diagnostic. Further compli-
cating the matter, regulatory requirements differ because therapeutics and
diagnostics generally fall under different legislative authorities. In addition,
product exclusivity concerns raise profitability questions among companies.
2 For more information, see http://www.pwc.com/gx/en/pharma-life-sciences/pharmaceutical-
industry-thought-leadership/pharma-life-sciences-mergers-acquisitions-diagnostics-2011.jhtml.
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THE CURRENT LANDSCAPE 15
Patients are prone to confusion regarding the value of genetic and genomic
technologies, and providers tend to be untrained in these areas, which slows
adoption. Drug reimbursement has been slow, reimbursements for diag
nostics remain focused on costs rather than value, and payers do not invest
in research and development, even though they benefit from stratification.
Many payers and health care providers remain unconvinced that many such
therapies improve people's health or are cost-effective.
In addition to its successes, Trusheim said, genomic-based drug devel-
opment offers cases where these challenges have so far prevailed. For
example, no candidate marker for response to bevacizumab has reached a
level of performance acceptable to regulators, and genetic tests for warfarin
response have not been widely adopted. FitzGerald added that while it is
well established that genetic variants impact warfarin metabolism, there
is little change in prescribing practices for testing largely because physi-
cians are reluctant to move away from established measures of anticlotting
effects. It also still remains to be seen whether there is an impact on clinical
outcomes from utilizing this genetic information. Similarly, FitzGerald said,
meta-analyses of multiple studies have not suggested a benefit from segre-
gating patients based on genotype in using clopidogrel, which is a medica-
tion used to prevent thrombotic events that has a total of $6-$7 billion in
annual sales.
Davies stressed the need to consider what the impact on quality and
cost of health care will be from genetic or genomic strategies rather than
the activity itself. Translating the multitude of genetic and genomic data
into a better understanding of disease, improved targets, rapid translation
to the clinic, better patient selection, and increased safety will be cru-
cial, he said. FitzGerald noted that "genomic variation is only one hand
clapping" and urged that other variables, such as environmental effects,
be integrated with genomic information to fully explore the consequences
of drug exposure.3 He also suggested that collaboration with sponsors
in small studies that utilize next-generation sequencing and drug-evoked
phenotyping of adverse events presents an opportunity for genomic and
genetic based strategies.
More generally, Ginsburg concluded, the great expectations generated
by the promise of genetic-based drug discovery and development have not
always been met (Pollack, 2010). According to a recent article in Clinical
Pharmacology and Therapeutics, "the level of trust between the different
actors in drug development needs to be urgently restored following the
disillusionment felt by many that the sequencing of the human genome did
3 A concept for an integrated data network of genomic and other information is described
in Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and
a New Taxonomy of Disease (NRC, 2011).
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16 GENOME-BASED THERAPEUTICS
not deliver the expected therapeutic breakthroughs" (Goldman, 2012). But
there is optimism moving forward as well, Ginsburg said, noting that the
same article pointed out that "there is now a unique window of opportunity
to tackle these challenges" and a key model for doing so is establishing new
models of collaboration among industry, academia, patient groups, regula-
tors, and biotech companies.
