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!