Tissue Phenomics™: From Biomarker Discovery to … Phenomics™: From Biomarker Discovery to...
Transcript of Tissue Phenomics™: From Biomarker Discovery to … Phenomics™: From Biomarker Discovery to...
Tissue Phenomics™: From Biomarker Discovery to Clinical Diagnostic Assay Commercialization
Thomas Nifong, M.D.
Executive Vice President, Diagnostic Tests
Definiens
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Contents
The Basics of Tissue Phenomics™
Diagnostics Use Cases
Predictive Tissue Diagnostics – Patient Stratification
Prognostic Tissue Diagnostics – Immune Response
Molecular Diagnostics – Sample Selection & Normalization
Considerations & Strategies for Diagnostics Commercialization
The Basics of Tissue Phenomics™: Definiens Cognition Network Technology®
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Example: Cell Classification Based on Context Object Color and Shape is Highly Ambiguous
Epithelial cells
Lymphocytes
Granulocytes
Stroma cells
Tumor cells …
Stroma cell
Epithelial cell
Nuclei
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Context: Objects Set in Context Create New Context
Cognition depends on the context
Cognition Network Technology®
Nucleus
Object to be classified
Nucleus Nucleus
Epithelial cells
Lymphocytes
Granulocytes
Stroma cells
Tumor cells …
Stroma cell
Epithelial cell
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Context: Objects Set in Context Create New Context
Lumen
Epithelial cells
Lymphocytes
Granulocytes
Stroma cells
Tumor cells …
Cognition depends on the context
Stroma
Epithelium
Cognition Network Technology®
Nucleus
Object to be classified
Nucleus Nucleus
Hierarchy
Context
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Context: Objects Set in Context Create New Context
Epithelial cells
Lymphocytes
Granulocytes
Stroma cells
Tumor cells …
Cognition depends on the context
Lumen
Epithelium
Stroma
Stroma cell
Epithelial cell
Cognition Network Technology®
Nucleus
Object to be classified
Nucleus Nucleus
Hierarchy
Context
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Definiens Cognition Network Technology® The Unique Asset for Tissue Datafication™
Tissue
Conventional Tacit phenes
Single features Manual assessment
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Definiens Cognition Network Technology® The Unique Asset for Tissue Datafication™
From: Konrad Aumann et al. Lung Cancer 81 (2013) 382– 387
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Definiens Cognition Network Technology® The Unique Asset for Tissue Datafication™
Automatic Detection and Quantification of All Phenes, Features and Morphology Based on Objects, Context and Knowledge
Tissue Tissue Phenome
Cognition Network Technology®
Conventional Tacit phenes
Single features Manual assessment
Definiens 1,000‘s of features each Computational Analysis
Tissue Datafication™ (applied to any type of stained tissue)
Histologic scoring, intensity measurements, morphologic parameters, object enumeration
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Tissue Phenomics™ - A Big Data Approach to Clinical Oncology
Automatic morphological feature classification
Contextual spatial analysis
Correlation with patient demographics, gene expression profiles, & clinical outcome data
A pivotal study that demonstrated the power of combining Quantification to Pathology Scoring to
yield novel set of image based biomarkers
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Tissue Phenomics™ Mines Multiple Data Sources The Key to Better Biomarkers
Tissue Marker Signature
Tissue Phenomes
Patient Outcomes and Molecular Data
Data Mining and Correlation
Tissue Phenomics™ combines tissue data with patient outcomes & molecular data to: Discover novel biomarkers Improve or refine biomarker candidates Automate or quantitate existing biomarkers
Predictive TDx for better
patient stratification
Prognostic TDx for improved
treatment decision
Molecular Dx for improved
sample selection
Diagnostics Use Cases
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Predictive Tissue Diagnostics (TDx) Patient Stratification
HercepTest™ Patients with Breast Cancer NEGATIVE
POSITIVE
Herceptin® (trastuzumab)
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Predictive Tissue Diagnostics (TDx) Patient Stratification
HercepTest™ Patients with Breast Cancer NEGATIVE
POSITIVE
Herceptin® (trastuzumab)
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CDx Development in Phase I-II Clinical Trial Single Cell Quantitative Receptor Measurements
Problem • Need IHC assay to improve accurate selection of patients in
prospective oncology drug trials as early as Phase I.
Solution • Designed IHC assay with Definiens advanced image analysis • Quantitatively assessed receptor numbers on a cell by cell
basis using multiplex IF.
Benefits • Identified patient subgroups previously undetected using
established IHC and IF methods. • Comprehensive & consistent tumor heterogeneity assessment. • Higher throughput with greater reproducibility of readouts. • Identification of promising CDx candidate for patient
stratification in Phase III.
Implications • Better IHC assays when assay developmet and IHC
quantification approached in tandem. • Rigorous IHC assays are achievable for CDx usage. • Methodology is transferable to other markers.
Images from: Onsum et al.; Am J Pathol. 2013 Nov;183(5):1446-60
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Prognostic Tissue Diagnostics (TDx) Automated Assessment of Immune Response
Problem • Immune status in tumor and invasive margin strongly
influences clinical outcome.
• Need to quantify immune cells on colorectal cancer using whole slides.
Solution • Annotation of tumor and invasive margin regions.
• Cytotoxic T cells detected and quantified in tumor (CT) vs. invasive margin (IM).
Benefits • Development of prognostic Immunoscore™ test.
• Better identification of high and low risk cancer patients.
• Improved selection of patients for adjuvant therapy.
Implications • Currently being validated in a global, multi-center study.
• Automated annotation of morphology along with quantification of immune cells is capable of providing required readouts despite tumor heterogeneity and variable staining conditions.
Images from: Anitei et al.; Clin Cancer Res 2014;20:1891-1899
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Immunoscore™ in Rectal Cancer
Prognostic for DFS and OS • 34% of the patients with a localized
cancer (stage I–II) presented with an Immunoscore associated with a very poor outcome
• 16% of the patients with an advanced rectal cancer (stage III–IV) presented with an Immunoscore associated with a very good outcome
Images from: Anitei et al.; Clin Cancer Res 2014;20:1891-1899
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Immunoscore™ as Predictive
Prognostic +
Predictive
Images from: Ascierto et al.; Journal of Trans Medicine 2013;11:54.
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Molecular Diagnostics (MDx) Sample Selection & Normalization
Definiens used in Clinical Oncology Research to assess use in MDx Definiens solution is used for detection of tumor-only regions
Automatically classified regions are used for microdissection which is then used for gene expression profiling
Automated tissue classification helps to improve genomic signal to noise ratio
Image analysis + gene expression profiling yields improved p-values
Definiens automated tumor detection + image feature classification & quantification then use micro-dissection to enrich gene expression profile
Tissue Image Automated Image Analysis NGS + Gene Analysis
Considerations & Strategies for Diagnostics Commercialization
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Automated Clinical Workflow
Bar code through LIS
Local PC storage
Server storage
Repository for Bioinformatics
LIS
Clinical Interface
Tissue Datafication
Automated Image Processing
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Image Analysis-Based Assays
Patients
Image analysis-based assays can be commercialized for both prognostic and predictive (CDx) indications
Must navigate a complex environment with many stakeholders
Regulatory environment is fluid and must be balanced with economic incentives
Early drug development can be accelerated with image analysis-based patient stratification:
For resulting CDx global deployment is required to ensure appropriate drug access
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FDA Update on LDT Regulations
Comment period began October 3, 2014.
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FDA Update on LDT Regulations: All Labs, All “LDTs”
Comment period began October 3, 2014.
Low Risk and “discretionary” LDTs Medium to High Risk LDTs
“Well-established” tests (No definition)
LDTs for rare tests (less than 4000 tests / yr.)
LDTs for unmet needs (No approved test for this intended use, manufactured & used by the lab)
Other high risk LDTs
LDTs with the same intended use as cleared LDTs
Basic statutory requirements: • Notify the FDA • Submission of Medical Device Reports (MDR) • Submission of notices for corrections or removals • Procedures to comply with MDR and reporting regulations • Complaint handling & reporting to FDA
Basic requirements plus: • Register with the FDA • Premarket review (510(k) / PMA) • Quality System Regulation Implementation will be phased in (12 months after final regulations are published).
Class I Class III
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Two Options to Deploy Image-based IVD
Option 1 (Deploy from a single lab):
Laboratory Developed Test (LDT) utilizing Definiens technology; obtain a PMA for a Prognostic or CoDx indication
Option 2 (Distribute as an IVD kit):
Partner with an assay provider and either file in parallel or include Definiens portion of system in partner PMA
Systems Approach
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Value-based Pricing: Breaking a Vicious Cycle
Images from: Hayes et al.; Science Trans Medicine 2013;5(196).
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Reimbursement Options
Combine existing codes •88361 – Computer-assisted IHC •88367 – FISH/ISH •G0461 – IHC •Under radar but lower reimbursement
Use unlisted code •88399 – Unlisted surgical pathology procedure •88599 – Unlisted MAAA •Will be reviewed manually by payers
Apply for specific MAAA code •Multianalyte Assay with Algorithmic Analysis •88599 – Unlisted MAAA •May take two years to obtain code
Need Value-based Pricing
Methodology/ Procedural Codes
Unlisted Codes
MAAA
Reserve for single-marker assays
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Drug and CDx Timelines
Phase I Phase IIA Phase IIB Phase III POC
Design Lock
Prototype Assay
Design Transfer
PMA Submission
NDA
Development Phase Validation Phase
Assess Biomarker
Establish Performance
Verify Performance
Validate Design
Locked Assay
Final Assay
IVD Pre-Sub Meeting
IDE Pre-Sub Meeting
PMA Pre-Sub Meeting
IDE Submission
Feasibility Phase
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Drug Development
Preclinical Models • Measure efficacy • Measure toxicology
Biomarker Discovery: • Pharmacodynamic: measure biological response
• Predictive: toxicity or response
Assay Development (IHC, ISH, FISH)
Image analysis-based qIHC, ISH, FISH Life Sciences
Measure Biological Activity Observe Biological Activity
Clinical Trials
Stratification
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IHC Assay Development Process
Preclinical through Phase I: Assess Biomarker
IHC assay optimization (antibody selection,
dilutions, antigen retrieval, detection
method)
Assay analytical validation – specificity, LOD, reproducibility,
pre-analytical variation
Test IHC assay on tumor survey of
archived tumors of intended use
Define/refine cutpoint
Apply to clinical trial samples
retrospectively or prospectively
Further optimization and analytical
validation if required
Re-optimize if necessary and lock-
down, transfer to CLIA facility or work with IVD manufacturer
Prospective Clinical Validation
Companion Diagnostic (Predictive Value)
Phase III: Validate Design
Phase II: Establish & Verify Performance
Further optimization and analytical
validation if required
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Analytical Validation
Accuracy
Concordance with Pathologists (ROI determination)
Correlation with Standard Curve (quantitative BM level)
Precision
Intra-system Reproducibility (same slide, same scanner)
Inter-system Reproducibility (same slide, across scanners)
Inter-system Reproducibility (serial sections across stainers,
scanners, lot#, techs)?
Technical System Calibration, Limits of Detection, Dynamic Range?
IVD Pre-Sub Meeting
IDE Pre-Sub Meeting
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IHC Assay Development Process
Preclinical through Phase I: Assess Biomarker
IHC assay optimization (antibody selection,
dilutions, antigen retrieval, detection
method)
Assay analytical validation – specificity, LOD, reproducibility,
pre-analytical variation
Test IHC assay on tumor survey of
archived tumors of intended use
Define/refine cutpoint
Apply to clinical trial samples
retrospectively or prospectively
Further optimization and analytical
validation if required
Re-optimize if necessary and lock-
down, transfer to CLIA facility or work with IVD manufacturer
Prospective Clinical Validation
Companion Diagnostic (Predictive Value)
Phase III: Validate Design
Phase II: Establish & Verify Performance
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Drug Development
Preclinical Models • Measure efficacy • Measure toxicology
Biomarker Discovery: • Pharmacodynamic: measure biological response
• Predictive: toxicity or response
Assay Development (IHC, ISH, FISH)
Image analysis-based qIHC, ISH, FISH Life Sciences
Measure Biological Activity Observe Biological Activity
Clinical Trials
Re-evaluate and lock-down for Phase III trial • How should the assay
be commercially deployed?
Partner with an IVD provider and include
Definiens algorithm in IVD PMA for CDx
Laboratory Developed Test (LDT) utilizing
Definiens technology; obtain a lab-based
PMA for CDx
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Summary
Thousands of features derived from the CNT® can be correlated with patient genomic and clinical outcome data in an approach known as Tissue Phenomics™
Use cases include CDx for improved patient stratification for HER2 antagonists, prognostic testing for colorectal cancer, and molecular diagnostic ROI purification and normalization.
In particular immunoprofiling is a promising application for both prognostics and companion diagnostics
Regulatory, reimbursement, and deployment of advanced diagnostic tests using image analysis can be accomplished by both LDTs and IVDs
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Thank You!