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Copyright ©2015 Q2 Solutions. All rights reserved.
COMPANY CONFIDENTIAL
Precision Medicine: Shifting from One Drug for All Trials
to Targeted Therapy Trials
October 28, 2015
Patrice Hugo, Ph.D., Chief Scientific Officer, Q2 Solutions
Victor Weigman, Ph.D., Associate Director, Translational Genomics, Q2 Solutions
2 COMPANY CONFIDENTIAL
Q2 Scientific Differentiators
Early Engagement
• 12 Scientific Advisors in
key Therapeutic /
Technology areas with
reach to more than >75 Q2
scientific SMEs
• Access to Therapeutic
Centers of Excellence at
Quintiles CRO
• Access to technology
experts at Quest labs
Translational Laboratories
• Fully dedicated scientists
for high complexity assays
• 4(5) strategic locations
• Assay optimization &
validation expertise
• Flow, LC-MS/MS, mutation
analysis, Elisa, Cell-based
assays
• High science expertise
• Consulting expertise
End-to-End Lab Services
• Largest global footprint
• Access to one of the
broadest test menu
• Safety, Biomarkers, CDx,
Immunoassays, Flow
cytometry, AP/IHC/FISH,
Genomics, Vaccine,
Infectious Disease,
Microbiology, LC-MS/MS
Endocrinology, BioA/
ADME/Immunogenicity
• Centers of Excellences
• Q2 Solutions: 2nd Largest Central lab in the world
• Parent Quintiles: Largest CRO in the world
• Parent Quest: Largest reference lab in the world
3 COMPANY CONFIDENTIAL
Biomarker R&D services and CDx strategic consulting
Assay development expertise and Dx partnerships
Assay optimization/ Bridging study/ CLIA laboratory testing
Global study execution for pivotal CDx trials
Regulatory support, including BIMO/FDA inspection support
Commercial, diagnostic, and late-phase expertise
Q2 Solutions Laboratory Partner of Choice for CDx Development from biomarker ID to CDx launch
Rx
Research/
Biomarker ID
Develop
Prototype
Analytical
Validation Clinical Validation
Drug-diagnostic
Registration
Commercialization Dx Modification
1 2 3 4 5
1
2
3
4
5
6
6
Flexible Support Across the CDx Life Cycle CRO
Pre-Clinical
Clinical
Phase I Phase II Phase III
FDA Filing/Approval
Launch
Dx lab
4 COMPANY CONFIDENTIAL
• The era of precision medicine: “right drug, right patient, right dose”
– Predictive, prognostic, pharmacodynamics, and pharmacogenomics biomarker
assessments now routine for development of most drugs in most indications
• Increased need for earlier decision-making (green/red light) based on
biomarker-driven PD and safety/efficacy signals
• Shift away from protein or single-gene assessments to gene expression
‘signatures’ with R&D and clinical application
• Move towards adoption of genomic testing in the clinical space necessitates
incorporation of genomics in drug and Dx development
• Limitations in sample availability and quality
• Pharma must “do more with less”
– Need for higher sensitivity and multi-parameter solutions tempered with efficiency,
reduced sample input, and faster turnaround times
Industry Challenges The trends and demands of biomarker-driven decision making in drug development
5 COMPANY CONFIDENTIAL
Using Genomics to Power Trials
6 COMPANY CONFIDENTIAL
• Shift from single-analyte to multi-use panels
• Genomic pre-profiling as a successful model
• Bringing trials to the patient
• Immuno-Oncology applications of Genomics
• Custom assay design and specimen collection needs
Powering Clinical Trials through Genomics
Company Confidential
7 COMPANY CONFIDENTIAL
Image Source: Wikimedia Commons
Classic “One Size Fits All”
Treated
Population
Lack of Efficacy
Lack of Safety
Population of Interest
Responders
Non-responders
Adverse Event
Patients
Changing How Drugs are Delivered
Identify non-responders and safety issues before prescribing or treating
Personalized/ Precision Approach
Prescreened
Population
Predictive Bio-
marker Testing
Responders
Adverse Event
Patients
Non-responders
8 COMPANY CONFIDENTIAL
Landscape Changes: Explosion of Targeted Agents in Cancer Great if you have the target!
http://www.personalgenome.com/translating-cancer-genome-analyses
McDermott et al, N Engl J Med. 2011 Jan 27;364(4):340-50
• 22% of the pipeline agents
currently in pivotal trials are
being developed in a
biomarker-defined patient
population.
• of the 189 oncology
therapies currently under
development in the period of
2012-2015, 56% have an
associated biomarker.
• By 2017, 34 of these
pipeline therapies are
expected to launch, and 20
of these will be targeted to
biomarkers.
‘According to recent data from McKesson Specialty Health/US Oncology Network (MSH) http://www.nxtbook.com/nxtbooks/pharmcomm/20130910/?utm_source=Campaigner&utm_campaign=SeptOct_Digital_Edition_eBlast_8-28-13&campaigner=1&utm_medium=HTMLEmail#/0
A properly designed genomic panel + associated
bioinformatics can address both sides of the graph…
Reducing time to result with a single assay
9 COMPANY CONFIDENTIAL
Case Study: High Screen Failures for Targeted Therapy Increasing identification of difficult-to-find mutations
Situation:
• Phase 1 study of drug X indicates exquisite sensitivity in patients with a genomic
alteration in gene coding protein Y
• Effect seen in CRC and NSCLC patients only
• Literature for CRC and NCSLC estimates genomic alteration in gene Y to be:
› 2% of CRC specimens
› 10% of NSCLC specimens
Typical Solution:
• You design your phase 2 program accordingly:
› 2 strata – one of NSCLC and one for CRC
› All subjects must have genomic alteration in gene Y
• Phase 2 timeline expected to be 2 years with high screen failure rate and high zero
enrollers
Constraint:
• The portfolio committee will approve if timelines can be 1.5 years, with the same N
10 COMPANY CONFIDENTIAL
10
Answer: Genomic Pre-Profiling Solutions for identifying and enrolling biomarker defined oncology patients
Faster enrollment due to increases patient and
physicians interest
Faster study enrollment
• Improved access to patients with right genomic signature
• Quick start-up when potential patients are identified
Quicker to key
development decisions
• Faster enrollment
• Time to key decisions points is reduced
• Impacts overall R&D spend
More feasible to develop drugs in
niche settings
• Protocols with high screen failure rates are now feasible
• Opens up new commercial opportunities
How to cost-
effectively develop
a drug with an
anticipated high
screen failure rate
in a timely
fashion?
Genomic Profiling with Just-in-Time Start-up
11 COMPANY CONFIDENTIAL
Matching Panel to Trial Design Solutions for identifying and enrolling biomarker defined oncology patients
Model A - SOC
Model B – Big Registry
Model C –
Limited Scope Registry
Model D – One
Protocol – Fast TAT
Model E – One
Protocol –
Long Screening
Model F – Pre-Profiling
Operational
Design
Identify sites
where
genomic
sequencing is
occurring for
oncology pts
in indication
Longitudinal
Registry
Umbrella
Followed by Tx
Trial Enrollment
of + variant
Patients
Pre-profiling
limited scope
Registry
Followed by Tx
Trial Enrollment
of + variant
Patients
Pre-Screening /
Genomic Testing
Within One
Protocol
Test patients –
newly Dx, newly
recurred
Pre-Screening /
Genomic
Testing within
one Protocol
Test patients at
stable disease
Pre-profiling
limited scope
registry and JIT
for investigator
sites
Methods for Patient Identification
Genomic Panel
Genomic panels allow for increased biomarker information, finds the right patients
and bring the trial to them.
12 COMPANY CONFIDENTIAL
• Leveraged relationships between mutation and drug response / resistance
• Pan-Cancer biomarker approach identifying novel associations to indications
• Can help segment price-value comparisons for drug pricing
Q2 Solutions Comprehensive Cancer Panel: QCCP Focusing on pairing patient to treatment
13 COMPANY CONFIDENTIAL
Patient Pre-Profiling
Patient Presents- ICF, Patient Enrollment Sample Collection
Genomic Testing
Bioinformatic Analysis
Clinical Annotation and Reporting
Physician-Patient discuss options
Site request just-in-time start-up, ICF signed,
patient enrolled in treatment study
Matching patients to studies based on prospective genomic testing
Genomic testing registry
Genomic testing at
Q2 Solutions Labs
Clinical Report
Site staff activities of treatment
decisions and study initiation < 3 weeks
14 COMPANY CONFIDENTIAL
• Shifting from single-analyte to multiple increases risk
– Each variant has it own error and is compounded when
you interrogate 1.34M positions
• Validation showed variants < 10% of cells
• High sequencing depth is needed (which increases noise)
• In same assay we also want to look at breakpoints and
other complex indels
• Variant reporting should account for risks with sequencer error
Accuracy is Critical Search for low frequency variants & complex changes has risk
Ris
k
# loci assayed
Co
lin P
ritc
ha
rd (
Wa
sh
U)
Indels
Rare
Alleles
Breakpoints
15 COMPANY CONFIDENTIAL
• Having a pharmaceutical company be able to leverage the same assay in
different countries opens the door to multiple protocol delivery options
• No need to chase down labs to run the assay you are looking for an hoping the
results are similar across testing sites
• Can use vendor to help store and mine rapidly growing biomarker for indications
data across global network
Leveraging Global Laboratory Footprint Single panel can power multiple protocols across the world
Cancer patients in pre-profiling
network with alterations identified Protocols with specific genomic
alteration entry criteria
Pre-profiled cancer patients matched
to right protocol just-in-time
16 COMPANY CONFIDENTIAL
• Higher actionability increases patient and physician interest
– One test, one biopsy with quick turn times (2-3 weeks)
– General oncology assay can identify many pan-cancer biomarkers
– Increases chance for rare positive biomarkers to be found for various trials
– Patients can be matched with approved drug as first line Rx
• Enhanced Trial enrollment
– Large sample study shows that 11% (of 2000) went onto genotype-matched trials
– Many Groups facilitate this matching • Molecular Match
• Caris
• IBM (Watson)
• New Protocols are leveraging this power! – TAPUR (ASCO) M-PACT (NCI)
– Lung-MAP (NCI) IMPACT-2 (MD Anderson)
– FOCUS-4 (UK)
Increasing the Adoption of Genomic Pre-Profiling Good for the patient, good for Pharma
Meric-Bernstam F. et al JCO, May 2015
17 COMPANY CONFIDENTIAL
Genomics Powering
Immuno-Oncology Landscape
18 COMPANY CONFIDENTIAL
Current Landscape in Oncology Turning a fatal disease into a chronic treatable disorder
Over 800 cancer drugs in clinical trials - almost all are targeted at particular gene products
Some Fundamental Problems in Cancer Treatment
• Cancer is rarely detected early
• Cancer develops resistance rapidly to targeted therapies and chemotherapies due to the development/expansion of resistance mutations.
• Many patients do not respond to immunotherapies. Immunotherapies are changing the approach to treating cancer by treating the immune system rather than the cancer but not all patients respond.
Therapy Response
Rate
Toxicity Long term
Survival
Chemotherapy /
Radiation
Low High Poor
Targeted
Therapy
High Lower Poor
Immunotherapy Mid Lower Good
Source: Sharma, Allison: Cell, April 2015
19 COMPANY CONFIDENTIAL
Number of Products in Development for Selected Targets*
Source: BioMedTracker, copyright 2015
*as of May 2015
20 COMPANY CONFIDENTIAL
20
Routinely collected clinical samples
Data can be mined for molecular immune-oncology characterization
Immuno-Oncology Innovation New opportunities for molecular characterization
Samples Molecular Services Benefits
These characterizations can be used in drug studies
Saliva
Blood
Biopsy
Slides
Self-recognition HLA alleles
Immune activation B and T-cell
Tumor
characterization DNA and RNA
Stimulate T-cell response
• Cell therapies
Block immuno-suppression
• CTLA4
• PD1/PDL1
• IDO1
• OX40
Develop cancer-specific
vaccines (neoantigens)
• NY-ESO-1
• MAGE-3
• gp100
Through Immuno-oncology:
• Gain a deeper understanding of drug safety and PK/PD
• More precise tumor characterization
• More effective, personalized therapies
21 COMPANY CONFIDENTIAL
Situation:
– Patients in trial selected for receipt of Immunotherapy but does not respond
Solution:
– High Depth Exome Sequencing can identify new mutations in antigen coding genes
• Can identify allele-specific expression (ASE) of mutations with supplemental RNA-Seq
– Build associations of mutations across cohorts to highlight specific genes / mutations.
Result:
– Reduction in target identification through bypassing of screening of tumor-infiltrating
lymphocytes1
– Patients now have method to identify mutations in tumor for other biomarker identification,
along with neoantigens to facilitate biomarker discovery pipeline
– Collection of large-scale mutation information across indications allows for identification of
pan-cancer biomarkers that could extend existing immunotherapies to new indications
Case Study: Identification of Tumor-Specific Antigens Facilitating Drug Development by Identifying Novel Biomarker Classes
Source: 1. Yadev et al. Nature 2014
22 COMPANY CONFIDENTIAL
Situation:
– Targeted therapy has been selected for patient
– After treatment, certain patients develop hepatotoxicity to treatment, causing Drug
Induced Liver Injury (DILI) and potential post marketing withdrawal of drug.
Solution:
– Human Leukocyte Antigen (HLA) allele calling showcases toxicogenomics and
identifies
type that is associated to adverse reaction in affected population • ~30% of patients develop Colitis
– HLA gene association analysis will identify risk alleles
Result:
– Patients in trial with the risk allele can be more closely monitored / have treatment
amended
– Pharmacogenomics (PGx) data also generated for all trial participants
Case Study: Forecast Toxicity Risk HLA alleles have proven associations with toxicity
23 COMPANY CONFIDENTIAL
Immuno-oncology is Genomics Solutions Oriented
Technology
Service Need
Somatic Mutation Analysis DNA deep Sequencing, Breakpoint
analysis and Fusion Detection
Gene Expression Profiling RNA-Seq, Arrays, RNA panels
Germ Line Variant Analysis CNV, Structural and Small Variant
Detection
HLA Characterization HLA Calling (DNA, RNA, Arrays)
Immune Response B/T Cell Repertoire (DNA/RNA),
VDJ mutation (RNA)
24 COMPANY CONFIDENTIAL
• Immunotherapies offer significant advantage to cancer treatment for otherwise
untreatable patients
– Identification of those patients is not straightforward
• Earlier adoption of genomic panels into testing of trial patients can provide
mechanism for targeted therapy, along with ability to prognosticate on
immunotherapy toxicity
• High potential for novel biomarker identification, reducing drug development
pipelines
– Building broad genomic datasets across indications has high long-term potential for
data mining payoff
Immunotherapy Conclusion Case example using genomics + immunotherapy for increased gain
25 COMPANY CONFIDENTIAL
Developing Your Own Assay /
Patient Population
Company Confidential
26 COMPANY CONFIDENTIAL
CROs/laboratories provide access
to a diverse network of clinicians
and scientists
– Bioinformaticists, geneticists, flow
cytometrists, mass spectrometrists,
microbiologists, virologists,
immunologists, anatomic
pathologists, cytopathologists,
hematopathologists
– Regulatory experts,
bioanalytical/medical writers,
physicians
• Determine appropriate consent
• Develop data organization analysis
strategies for future studies
The Advantages of Laboratory Collaboration Engaging laboratory resources and expertise to complement Rx efforts
Diagnostics
Biomarkers
Clinical/Med
Lab
Operations
Insights to optimize
protocol design and
execution
Biomarker/
Drug R&D
Protocol
Development
Laboratory
Expertise
Pharma
Expertise
27 COMPANY CONFIDENTIAL
Graphic of assays and typical input amounts
– Different technologies can vary inputs below
Typical Specimen Collection is Already Sufficient Genomic assays are more obtainable than you think
10
30
40
150
150
500
500
1100
0 200 400 600 800 1000
ASSAY INPUT NEEDS
Input Amount (ng)
Blo
od
FF
PE
So
lid
Tis
su
e
Pla
sm
a
HLA Allele Calling
Genotyping Risk Alleles
IGVH Testing
Targeted (NGS) Panel
Whole Exome (NGS)
PCR-enriched (NGS)
qPCR
ctDNA Allele Calling
28 COMPANY CONFIDENTIAL
Integrated Bioinformatics Capabilities Performance, scalability, flexibility
Bioinformatics
Team
Translational
Genomics
Applications Development
Data
Generation
10,000s of samples per year
Pipeline execution / QC
Customized Delivery (HDs / Cloud)
Software creation / maintenance
Pipeline efficiencies
High performance computing
Preclinical biomarker development
Pipeline Creation / algorithm dev.
Assay CLIA / GxP compliance
Assay Validation Custom Panel
Design
•CLIA LDTs Method
Validations
•Fit for purpose
•Directed across central
labs
•> 45 Custom Assays
•>9000 samples
•3 Sequencing platforms
•3 PCR platforms
Preclinical
Biomarker
Development
•Senior PhD Staff
•Assigned to specific
Pharma
•Direct research efforts
across sites
Validation Analysis
Platforms
•NGS delivery to FDA
•HL7 formats
•Formal validation
procedures
Computer System
Validation
• GxP compliance
• Part 11 validated systems
• Automated execution of
workflows
• Comprehensive Cancer
Panel Case Study
Data Mining /
Associations
•Comb results from
genomic panels to find
novel biomarkers
•Integrate genomics with
EHR
29 COMPANY CONFIDENTIAL
Situation:
– Looking to identify samples with specific
biomarkers, traditional testing limits the types of
biomarkers assays for patients across trials
Solution:
– Adoption of genomic panels for trial testing, along
with modified consenting / data usage criteria
– Efficient storage of genomic results allows for
robust querying of large numbers of biomarkers
– Combination of clinical variant annotation
databases (ClinVar, TCGA, 1000Genomes, etc)
Result:
– Database of genomic variants combined with
sample information can rapidly identify samples of
interest
Case Study: Mining Genomic Data for Patient Selection Leveraging legacy genomic data to identify patients with specific biomarker status
30 COMPANY CONFIDENTIAL
Genomic assays (multi-analyte) provide a mechanism for powering precision
medicine
– Numerous successful examples of genomics-based LDTs pairing patient to treatment
– Also examples of identifying biomarkers for enrollment in Trials
Existing trials are already collecting specimens that can run genomics
Genomics assays can power targeted therapy and Immuno-Oncology applications
Working with your lab provider early can help with trial design and CDx
applications (along with diagnostic manufacturer)
Long term payoff of genomic panels provides a wellspring of information for
identifying novel biomarkers
Overall Conclusion Enhancing trial design with genomics
31 COMPANY CONFIDENTIAL
Thank You
Questions