An excerpt from the latest issue of AccessPoint, looking at how genomic profiling data is transforming our understanding of patient subpopulations - a key to targeting treatments with greater precision

1. PAGE 4 IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS
INSIGHTS INNOVATIVE APPLICATIONS OF RWE
How patient subpopulations are
changing the commercialization
of oncology products
significant progress in understanding the science of cancer is not
only improving knowledge of underlying molecular pathways but
also increasing the complexity of launching new products.
Comprehensive genomic profiling data, linked to other available
RWD, offers rich potential as a resource for understanding patient
subsets – a key to targeting treatments with greater precision. As
this well of information continues to expand, extended applications
leveraging advanced analytics will enable even greater opportunities
for RWe to support the challenging oncology environment.
Natalia Balko, mBA
Principal, RWE Solutions, IMS Health
Nbalko@imshealth.com

2. Advances in oncology research are yielding the discovery of
new determinants of cancer and a greater understanding of
its progression, specifically via clinically-relevant genetic
mutations. Novel drugs designed to target disease pathways
more precisely often focus on patient subpopulations,
including those defined by genetic alterations. The resulting
introduction of new therapeutic options has, without
question, made the oncology market more complex.
In parallel, to aid in patient diagnosis and treatment
selection, cancer diagnostics have also been evolving
rapidly. The rise in next-generation sequencing (NGS),
including comprehensive genomic profiling, brings a
wealth of information about the genetic make-up of a
patient’s tumor, enabling oncologists to make more
informed treatment decisions.
The data generated by these tests is a rich source of RWD.
When combined with other sources of RWD, such as claims
or electronic medical records (EMRs), this allows deep
insights into target patient populations and the evolving
oncology market.
The rise of patient subpopulations
Developments in research and diagnostics are generating
new patient populations in three ways, with downstream
implications for the successful launch and commercialization
of oncology therapies
1. Growth in understanding of clinically-relevant mutations
In recent years, researchers have identified hundreds of
genes thought to be clinically relevant in the development
and progression of cancer; the understanding of these
genes and their role in the disease is evolving rapidly.
Taking non-small cell lung cancer (NSCLC) as an example,
mutations in at least 15 genes have been identified to date
for which there are also drugs available or in development.
Nine of the genes have been identified since 2009 (Figure 1).
Therapies targeting these mutations will provide new
options for patients but will also lead to shifts in treatment
paradigms and add complexity to physician decision
making. While some of the early genes discovered formed
distinct molecular subsets (eg, KRAS, EGFR and ALK in
NSCLC), in many cases the relationship between recently
identified genes has not been well characterized.
Impact of the genetic revolution
2016 (NSCLC Frequency)
ROS1 (1%)
RET (1%)
PTEN (4-8%)
NRAS (1%)
MEK1 (1%)
MET (2-4%)
FGFR1 (20%)
DDR (~4%)
2009 AKT1 (1%)
PIK3CA PIK3CA (1-3%)
ERBB2 (HER2) ERBB2 (HER2) (2-4%)
BRAF BRAF (1-3%)
2004 ALK ALK (3-7%)
1984-2003 EGFR EGFR
EGFR sensitizing (10-35%)
EGFR other (4%)
KRAS KRAS KRAS KRAS 15-25%
Approved in NSCLC for Labeled Biomarker
Previously Approved in NSCLC, Now Studied in New Biomarker
Drug Approved in Other Cancer
Drug in Clinical Development
Source: My Cancer Genome. EGFR in Non-Small Cell Lung Cancer (NSCLC). https://www.mycancergenome.org/content/disease/lung-cancer/egfr/
Evolution of Biomarker Identification in NSCLC Treatment
continued on next page
Figure 1: Current understanding of biomarker status in NSCLC
ACCESSPOINT • VOLUME 6 • ISSUE 12 PAGE 5

3. PAGE 6 IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS
INSIGHTS INNOVATIVE APPLICATIONS OF RWE
2. Greater numbers of smaller patient subpopulations
Many of the early gene discoveries were present in large
proportions of the patient population. However, new
mutations are often more rare, typically accounting for
less than 5% of the patient population. Additionally,
patients will likely have more than one mutation and
their tumor mutation profile can evolve over time. For
example, while most EGFR mutations are sensitizing for
first- and second-generation TKI inhibitors (eg, erlotinib,
gefitinib), a subset confers resistance to these drugs.
Notably, the point mutation T790M is most commonly
acquired and is related to resistance to first- and
second-generation TKI inhibitors. While less than 5% of
untreated EGFR-mutated tumors are estimated to harbor
the T790M mutation, approximately 50% of EGFR-
mutated tumors have the T790M mutation conferring
resistance1
(Figure 2).
3. Launch of drugs with novel biomarkers, introducing
new patient segments and pathways
Around one-third of the oncology drugs launching in the
next five years are expected to have biomarkers,2
many
of which are likely to be the newly discovered genes or
specific mutations. For example, third-generation TKI
inhibitors (eg, TagrissoTM
(osimertinib), AstraZeneca)
have been developed to address the issue of acquired
resistance to earlier TKIs (eg, via the EGFR T790M
mutation). These new treatment options, targeted for
specific patient populations, can shift treatment
paradigms and relevant patient segments for
existing products.
Together, these trends point to more complex treatment
paradigms with significantly more targeted patient
populations; the evolving understanding of the molecular
pathways underpinning cancer progression is yielding a
wider range of available treatments that address specific
patient subsets.
subpopulations and oncology commercialization
A granular understanding of patient subpopulations, their
characteristics and outcomes is essential for pharmaceutical
manufacturers in the changing oncology environment.
Results from comprehensive genomic profiling tests serve
as an important source of RWD to provide this knowledge
because they hold insight into emerging genes and
mutations and therefore future biomarkers and patient
subpopulations.
This understanding will become increasingly valuable in the
future as genomic tests are more frequently incorporated
into clinical practice earlier in the treatment paradigm.
Experts believe that their adoption will increase
dramatically in the next five years, with potential to be
used in up to 50% of newly diagnosed cases depending on
the tumor type.3
Use is also expected to be more widespread
in malignancies with multiple biomarkers and potential
treatment options, and vary by patient subgroup (eg, lung,
colorectal, and breast cancer). An increase in testing will
enable additional applications that are limited today by
small sample sizes due to the rarity of genomic alterations.
Comprehensive genomic profiling data can inform five
components of product commercialization
1. Prioritizing portfolios and assessing relative market
opportunities
Understanding the size of a target patient population can
inform market sizing and forecasting, thereby supporting
indication prioritization and sequencing, as well as
investment decisions. A combination of comprehensive
genomic profiling data with pharmacy and medical
claims information can also enable the definition of
molecular patient segments and treatments, shedding
light on opportunities for innovative therapies.
2. Defining unmet needs and informing stakeholders
New molecular subpopulations are often not well
understood because most patients were not tested for
markers other than those related to a particular drug.
Combining comprehensive genomic profiling data with
adjudicated claims or EMRs can provide insight into
outcomes, disease burden and healthcare resource
utilization for molecular subpopulations. This can then
be used to educate key stakeholders and support product
value propositions, particularly around unmet needs.
“
*With the exception of A763_Y764insFQEA
Source: My Cancer Genome. EGFR in Non-Small Cell Lung Cancer (NSCLC)
https://www.mycancergenome.org/content/disease/lung-cancer/egfr/
EGFR TKI Resistance Mutations
EGFR TKI Sensitizing Mutations
Exon
19
Exon 19
Deletion/
Insertion
Exon
18
G719X
Exon
20
Exon 20
Insertion*
Exon
21
L858R L861Q
T790M
Figure 2: Schematic of EGFR mutations
”
New testing approaches have yielded valuable data that complements single-marker
testing to provide both a more holistic and granular view of patient populations“

4. ACCESSPOINT • VOLUME 6 • ISSUE 12 PAGE 7
3. Strengthening product positioning and launch planning
The launch of new therapies, particularly those with
novel biomarkers, creates shifts in treatment paradigms.
Mapping treatment pathways for particular patient
subpopulations provides visibility into how target
populations are treated, the opportunities or challenges
for product positioning, and the support needed to
enable this (eg, education).
4. Articulating product value
By linking genomic alteration data with clinical (eg, EMR)
or claims data, outcomes research studies can be
performed to understand product value for target patient
populations in real-world settings.
5. Engaging with clinicians
Launching a product for niche patient subpopulations,
particularly if a diagnostic is used to identify a specific
biomarker, often requires additional education for
potential prescribers. Using testing data to identify
diagnostic patterns can help companies understand
which physicians may be early adopters for a new
therapy targeting a novel patient population and who
should therefore be the focus of educational efforts.
Applying a novel approach
The following is one illustration of an RWE analysis linking
treatment information to genomic profiling data to provide
insights into treatment dynamics within different
molecular subpopulations in NSCLC.
Duration of therapy was used as a proxy for patient
response to therapy and was the key metric of interest for
comparative cohorts (Figure 3). IMS Health medical and
pharmacy claims data was linked to Foundation Medicine’s
comprehensive genomic profiling data using a HIPAA-
compliant encryption algorithm. Comparative cohorts were
profiled and analysis was conducted on the proportion of
patients within each cohort initiating and discontinuing
therapy over the study period.
The study indicated that patients with mutations sensitizing
them to TKI therapy (EGFR mutations that are not Exon 20
mutations) had a longer duration of therapy compared to those
with mutations that tend to confer decreased TKI sensitivity
(EGFR mutations that are in Exon 20). This finding validated
published literature on these molecular subpopulations.
A path to a more precise understanding of
patient subpopulations
Historically, biomarker status was primarily derived from
companion diagnostics or single-marker tests. Test results
would typically be incorporated into EMR notes or a stand-
alone lab report, providing two sources of RWD for studies
of patient subpopulations.
Within the last several years, new tests have yielded
valuable data that complements single-marker testing to
provide both a more holistic and granular view of patient
populations. These tests establish the tumor molecular
signature through NGS-based techniques which identify
genomic alterations across a broader set of genes. In doing
so, they provide oncologists with additional data on a
tumor’s genetic make-up to inform treatment selection.
Information from these tests is critical for RWE analyses in
oncology. However, due to differences in the depth of data
and breadth of patient populations covered, they are being
used differently today. From an RWE perspective, they can
be grouped into two categories
1. Single-marker tests
These routine diagnostic tests are commonly used to
determine whether a patient has a particular biomarker
(eg, estrogen receptor status in breast cancer, HER2) and
include companion diagnostics developed for a particular
therapeutic treatment. The way in which results are
presented will vary by test but are often shown as
“positive” or “negative” for the particular marker.
2. Multi-gene diagnostics
These tests encompass the emerging set of techniques
including hot spot panel testing, comprehensive genomic
profiling (such as the Foundation Medicine FoundationOne
test in the case above), and whole genome sequencing,
and can identify alterations in multiple genes and
mutations within the tumor. Their focus can range from a
subset of pre-specified genes in certain portions of the
genome to broader sets of clinically-relevant mutations
and all classes of genomic alterations. For comprehensive
genomic profiling, the physician report will contain all
clinically-relevant alterations for a patient for the genes
tested, even if the particular alteration is relatively rare or
has not been previously characterized.
Results of single-marker tests have been used in both
commercial and scientific RWE studies examining different
patient subpopulations and provide valuable insight into
patient populations and outcomes. In the clinical setting,
tests such as HER2, EGFR, KRAS and ALK have shaped
treatment guidelines and been used to determine optimal
therapeutic paths for relevant tumors. Because these tests
are fundamental to clinical decision making, biomarker
status is known across broad segments of the patient
population, creating a viable source of data for RWE analysis.
EGFR- EGFR+
135
358
EGFR+
Exon
20 mut
EGFR+
non-Exon
20 mut
107
365
KRAS+ KRAS-
115
312
150
100
50
0
250
200
400
350
300
Source: IMS Health and Foundation Medicine analysis, September 2014
MedianDaysonErlotinibTherapy
Figure 3: RWE analysis of duration of therapy among
different molecular subpopulations
continued on next page

5. PAGE 8 IMS HEALTH REAL-WORLD EVIDENCE SOLUTIONS
INSIGHTS INNOVATIVE APPLICATIONS OF RWE
While the advantages are clear, there have been hurdles to
using this data for commercial and scientific RWE. In
particular, because these are new methods, the proportion
of tested patients has been relatively small. This also means
the tested patient populations tend to skew towards those
with more advanced diseases. However, this is changing; an
estimated 50% of newly diagnosed patients could benefit
from genomic profiling of their tumors and testing for
multiple genes at diagnosis could become commonplace.3
Powering scientific and commercial RWe analytics
Comprehensive genomic alteration data, linked to other
sources of RWD, should be considered as a potential,
innovative approach to gain granular insight and enhance
RWE in oncology. It can provide a greater understanding of
both target patient populations that historically have not
been well characterized, as well as evolving treatment
pathways as new therapies with novel biomarkers launch.
As this testing approach continues to gain adoption in the
market, the size of databases will grow, enabling new
applications not previously possible. These applications will
be supported by the development of advanced analytic
techniques, including predictive analytics, to determine
relationships between an increasingly complex set of
variables. The combination of new data and analytic
approaches will enhance the insights that can be derived
from this data and used to address commercial and
scientific questions.
However, there are several areas where single-marker tests
fall short for RWE
Lack of insight into new patient segments. Single-
marker tests provide insight into biomarkers with
marketed therapies but typically not into new
biomarkers or patient subpopulations that will be
relevant in the future. Therefore, for companies
launching novel products for new targets and patient
subpopulations it is challenging to gain insight into
target patient populations ahead of launch for
commercial planning. Likewise, for companies with
marketed products it can be difficult to ascertain how
new targeted therapies may shift treatment pathways.
Inability to detect specific alterations driving a
mutation. As observed in EGFR, specific alterations
can create sensitivity or resistance to therapy and can
also mutate over time. Single-marker tests often do
not provide this level of granularity, making it
difficult to understand relevant subgroups of patients.
A one-dimensional, static view of biomarker status.
More genes and biomarkers are becoming clinically
relevant. However, results from single-marker tests
only provide a view into a single dimension,
overlooking several which may be relevant,
particularly as treatment and diagnostic pathways
evolve. The absence of biomarker status for a
patient may not mean that he or she lacks the
alteration, merely that they were not tested or a
test did not exist.
Multi-gene tests, and in particular comprehensive genomic
profiling, can address these challenges, thus providing
unique value for commercial and scientific questions in RWE
Complete genomic evaluation of new patients.
Testing for a broad set of genes, even those without a
marketed therapy, means that emerging patient
segments can be evaluated using genomic profiling
data. When linked to other sources of RWD, this
insight is particularly useful for understanding
burden of illness, unmet needs and market potential
for new targets, which can support the product value
proposition at launch.
Multi-level profiling that accounts for genetic
alterations. Since all classes of alterations are
identified, patient cohorts can be profiled at different
levels by looking at specific alterations in isolation or
by grouping them in clinically meaningful ways. This
flexibility is particularly valuable for understanding
treatment pathways and evaluating outcomes within
different patient populations when the data is linked
to clinical or claims data.
A comprehensive molecular picture of patient
cohorts. With a view of a large number of clinically-
relevant genes (eg, 400+ in the case of Foundation
Medicine), a comprehensive picture of the molecular
profile for a patient cohort can be developed. This
insight enhances understanding of burden of disease,
treatment pathways and product outcomes.
References
1
EGFR c.2369C>T (T790M) Mutation in non-small cell lung cancer.
My Cancer Genome.
https://www.mycancergenome.org/content/disease/lung-cancer/egfr/4/
2
IMS Institute for Healthcare Informatics. Global Medicines Use in 2020:
Outlook and Implications. November 2015
3
McKinsey & Company. Personalized Medicine: The path forward. 2013
Comprehensive genomic alteration
data, linked to other sources of
RWD, should be considered as a
potential, innovative approach to
gain granular insight and enhance
RWe in oncology
“
”