GENOMIC AND BIOMARKER RESEARCH IN INDUSTRY SPONSORED CLINICAL TRIALS
Rebecca Blanchard, PhD
Executive Director and Head, Clinical Pharmacogenomics and Operations
Genetics and Pharmacogenomics
30 Aug 2017
Bispebjerg Hospital
Copenhagen, Denmark
Agenda
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• MSD overview
• Overview of genomic and biomarker research in MSD sponsored clinical trials, with focus on NGS
• Challenges in returning results of NGS
FOR MORE THAN A CENTURY, MSD HAS BEEN INVENTING TO SOLVE SOME OF THE GREATEST CHALLENGES TO PEOPLE’S HEALTH AND WELL-BEING AROUND THE WORLD.
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2016 REVENUES $39.8 billion, 54% of sales come from outside the United States
2016 R&D EXPENSE $10.1 billion; 24 product pipeline programs in late-stage development
BUSINESSES Prescription medicines, Vaccines, Biologic therapies, Animal Health products
HEADQUARTERS
Kenilworth, NJ, U.S.A. operating in more than 140
countries
Merck & Co., Inc. is our legal name and is
listed on the New York Stock
Exchange under the symbol "MRK."
EMPLOYEES approximately
68,000 worldwide (as of 12/31/16)
Global Clinical Trial Organization (GCTO) Regional Structure
Translational studies / precision medicine
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Treatment
Patients
Clinical
efficacy
No clinical
efficacy
Adverse
Event
Ben
ch to
Bed
side
Bed
side
to
Ben
ch
Patients
Diagnostic Biomarkers
Clinical
efficacy
Clinical
efficacy
Clinical
efficacy
Phase I Phase II Phase III
GENETICS Genetic variation
explains PK variability
Genetic variation Explains
variable efficacy
Validation: Phase II GWAS “hit”
predicts for response in Phase 3
Inform
Discovery
Candidate Genes
Drug metabolism,
drug targets
Primary Discovery
GWAS + WES
Genetic Marker/
Positive Result
YES
NO
Stratified Trial
Enriched for
responders
Continued Discovery
GWAS, targeted
genotyping, +/- WES
IMMUNO-
ONCOLOGY Biomarker Validation, Mechanism of Action, Novel Biomarkers, New Targets
Routine genomic and biomarker research in clinical trials
Genotyped 30,000 pts in 2016
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Immune Checkpoint Blockade: A Paradigm Shift in Cancer immunotherapy
To “turn on” the immune
response to fight cancer
Vaccines
TNFα, IL-2
To “release the brakes” on the immune
system to unleash a pre-existing immune
response against cancer.
(CTLA-4, PD-1/PD-L1)
Checkpoint blockade approach
Brakes Gas
Pre-checkpoint blockade
era strategies
Future state: combination strategies,
including precision medicine approaches
Personalized
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0
100
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0
100Melanoma1
-100
0
100NSCLC2
-100
0
100Gastric6
-100
0
100
-100
0
100H&N3 TNBC5
-100
0
100cHL7
-100
0
100NHL PMBCL8 Urothelial4
Ch
ang
e F
rom
Bas
elin
e in
Tu
mo
r S
ize,
%
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0
100
Mesothelioma9
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0
100
Anal14
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100
SCLC11
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100NPC13
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0
100Biliary Tract15
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100Colorectal16 Esophageal12
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0
100
Ovarian10
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0
100
ER+/HER2– BC17
1. Daud A et al. ASCO 2015; 2. Garon EB et al. ESMO 2014; 3. Seiwert T et al. ASCO 2015; 4. Plimack E et al. ASCO 2015; 5. Nanda R et al. SABCS 2014; 6. Bang YJ et al. ASCO 2015 ; 7.
Moskowitz C et al. ASH 2014; 8. Zinzani PL et al. ASH 2015; 9. Alley EA et al. AACR 2015; 10. Varga A et al. ASCO 2015; 11. Ott PA et al. 2015 ASCO; 12. Doi T et al. ASCO 2015; 13. Hsu C et
al. ECC 2015; 14. Ott PA et al. ECC 2015; 15. Bang Y-J et al. ECC 2015; 16. O’Neil B et al. ECC 2015; 17. Rugo HS et al. SABCS 2015; 18. Frenel JS et al. ASCO 2016; 19. Mehnert JM et al.
ASCO 2016; 20. Cohen R et al. ASCO 2016; 21. Ott PA et al. ASCO 2016; 22. Hansen AR et al. ESMO 2016; 23. Reardeon D et al. SNO 2016.
Gastric: sBLA accepted for Priority Review with PDUFA date of September 22, 2017
Cervical18 Thyroid19 Salivary20 Endometrial21 Prostate22 GBM23
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KEYTRUDA monotherapy has shown activity in more than 20 tumors resulting in approvals across 5 tumor types
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An unprecedented opportunity to develop next-generation biomarkers and therapies
Tens of thousands of patients are treated with Keytruda in our clinical trials
An unprecedented opportunity to understand mechanisms of response and resistance through biomarker research
Biomarker research will: Identify biomarkers associated with response,
resistance and safety Identify new drug targets Identify patients most likely to need combinations
rather than Keytruda monotherapy Suggest rational drug combinations Help to develop treatment regimens that are unique to
a patient’s tumor biology (precision immuno-oncology)
Survival time
Su
rviv
al P
rop
ort
ion
A . Anti-PD-1+SOC agents
Anti-PD-1+novel immunotherapy
B. Anti-PD-1 monotherapy
C. Standard or other therapy
D. Control
A
B
C
D
Baseline Post-treatment Changes in peripheral blood and tumor microenvironment
Tumor (FFPE or Fresh) • Gene Expression (RNA) - Nanostring: Immune Signatures - RNAseq- complete expression profile • Genetics (DNA) - Whole exome sequencing (WES) - TcR sequencing (t-cells) - Liquid biopsy (cell free DNA, ctDNA) • Protein (PD-L1, PD-L2 IHC ) Peripheral Blood • Gene expression (RNA) - Nanostring : Immune genes - RNAseq –complete expression • Genetics (DNA) - TcR sequencing (t-cells) - WES - GWAS & HLA genotyping • Protein (serum – PD-L1 ELISA) • Flow assays – immunophenotyping
Goal: Generate a comprehensive molecular & genetic understanding of PD1 patients to understand MOA and
predictors of response
Cancer Patient
• Gene Expression (RNA) - Nanostring-immune gene - RNAseq-complete profile
• Genetics (DNA) - TcR sequencing (t-cells) - Liquid biopsy (cell free DNA, ctDNA) • Protein
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Exploratory biomarkers in MSD’s oncology programs
Keytruda biomarkers: Biology assessed by MSI/Mutation load vs. PD-L1/GEP
MSI and
mutational
load: measure
tumor
antigenicity
PD-L1 and T-
cell inflamed
gene
expression
profile (GEP):
measure
activated T-
cells in tumor
PD-L1
PD-1
Tumor
APC
CTLs
FFPE Tumor
Tissue
Collected
Discover
Genes and
Signatures
associated
with
response to
Keytruda
Gene Expression Profiling Technologies
FFPET block
or unstained
slides (~27
patients)
RNA profiling (baseline assessment)
•Affymetrix platforms
•Already being performed with Covance
Depending on DNA yield (200 ng per slide?)
• Affy SNP 6.0 CNV
• Genotyping (Sequenom); should see Kras mutations etc.
• To be initiated
MET IHC (baseline assessment)
MET amplification status (baseline for only responders)
• Already being performed with Ventana
(N=3)
(N=4)
(N=3)
Phase I
Patients
Enrolled In Keytruda
Clinical Studies
Focused On Discovery Of Genes Associated With Response To Keytruda Therapy
Data
Mid-density
Immune
focused
RNA-seq
(genome wide)
RNA
Building a molecular database from Keytruda clinical studies over time
GEP Delineates Categories of Non-Responders
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Nanostring 57 genesignature
PFS
A B
C
Group A: T-cell non-inflamed tumors rarely respond to pembrolizumab
Group C: almost all responders have baseline T-cell inflammation
Group B: some non-responders have T-cell inflamed tumors • Predict Keytruda monotherapy response
• New target identification/validation
• Inform drug combinations
T-Cell Inflamed GEP
PF
S (
day
s)
Combined data from KEYNOTE 001 melanoma and KEYNOTE 012
(SCCHN, bladder and gastric) cohorts
Mutational load and neoantigen burden predict response to Keytruda in NSCLC
0 4 8 1 2 1 6 2 0 2 4
0
5 0
1 0 0
C o h o r t 1 - D is c o v e r y
M o n th s
Pe
rc
en
t p
ro
gre
ss
ion
-fre
e
H ig h n o n s y n o n y m o u s b u rd e n (n = 8 )
L o w n o n s y n o n y m o u s b u rd e n (n = 8 )
0 4 8 1 2 1 6 2 0 2 4
0
5 0
1 0 0
N e o a n t ig e n b u rd e n
M o n th s
Pe
rc
en
t p
ro
gre
ss
ion
-fre
e
H ig h n e o a n tig e n b u rd e n (n = 1 7 )
L o w n e o a n tig e n b u rd e n (n = 1 7 )High non-synonymous burden
Low non-synonymous burden High neoantigen burden
Low neoantigen burden
Rizvi et al. Science 2015
ML and GEP Associated with BOR (HNSCC)
• ML and GEP were weakly correlated and remained significant predictors in a multivariate model
adjusted for each measure (ML P=0.0349; GEP P=0.0056)
• Response was higher in patients with high ML or GEP; highest in those with both high ML and GEP
All patients, r = 0.17; P=0.1633
PR/CR, r = 0.029; P=0.9276
Not PR/CR, r = 0.077; P=0.5647 • ML High and Low: ≥ and < 86†
• GEP High and Low : ≥ and < -0.318‡
Not PR or CR
PR or CR
†Cutoff associated with ROC Youden Index; ‡Cutoff selected via analysis of pan-cancer data; equivalent but numerically different clinical assay cutoff is
currently under evaluation in some Merck trials.; §B1+B2 WES cohorts
18 gene inflammation signature
WE
S N
S M
L (
log
sca
le)
-0.8 -0.6 -0.4 -0.2 0 0.2 0.4
10
30
100
300
1000
3000
-0.318
YI = 86
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Future State: “Straw Man” Decision Tree for Cancer Immunotherapy
T-cell poor tumors T-cell rich tumors
Biomarker 1:
T-cell inflamed signature
Tumor cell
pathway
activation
Extrinsic factors
(vasculature,
fibroblasts)
Biomarker 2
Failed
T-cell
priming
Biomarker 4
Low mutation load, low
neoepitope burden
Poor antigen
presentation
Additional immune
suppression
PD-1 is dominant
suppressive mechanism
Biomarker 3
Biomarker 5
Myeloid cells or Treg
cells
Other immune
Checkpoints
αPD-1 monotherapy αPD-1 +
targeted therapies αPD-1 +
VEGF Inhibition
αPD-1 +
myeloid targeting
αPD-1 + LAG-3 αPD-1 +
vaccines, oncolytics,
αPD-1 +
mutagenic chemo,
epigenetic modifiers
Challenge
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• Breakthroughs such as those presented here require genomic research for the initial discoveries
• We have an extremely unique opportunity for such discovery in our Keytruda program (with hundreds of global studies)
• We are not able to conduct such research in all countries due to various concerns about genomic data
• Genetic predictors of response can vary by population/ethnicity
• EMA and other regulatory agencies are now asking for genetic/biomarker data
We want to work collaboratively to enable discoveries for all patient populations
International requirements to return results (per MSD’s experience)
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Country Requirement What
Brazil CONEP Resolution 340/2004
(Human Genetics research
Right to access genetic data
Italy Authorization on Genetic Data
Treatment
Right to access genetic data
Argentina Personal Data Protection Act (Act
No. 25326)
Right to access personal data
Spain Biomedical Research Act 14-2007 Right to access genetic data
Norway Health Research Act 2008-06-20
no. 44
Right to access personal data
Denmark National Health Research Ethics
Committee (DNVK) Guidelines on
Genome Mapping
Clinically significant
Returning results of NGS tests in clinical trials: the Sponsor’s perspective
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Challenges
Accuracy/validity of test
Relationship to patient
and clinical interpretation
What to return
Timing of research relative
to trial
Summary of current status
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• Currently we do not consent patients in Denmark for NGS based BMx research because no infrastructure is in place to return data
• Therefore, association between these biomarkers and drug response for patients from Denmark are not being studied
• We welcome an opportunity to develop a path forward in collaboration with DNVK so that we can enable discoveries to benefit the Danish population
THANK YOU
BACK-UPS
R&D therapeutic areas
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Past, recent past, and present
Past
Recent
Past
Present
BMx 1
BMx 2
BMx 3
Breakthrough in Oncology Precision Medicine
(Tue May 23 2017)
ACMG recommendations
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