Early Oncology Partnering forum presentation [Molecular Med TriCon Feb 2011]

8/7/2019 Early Oncology Partnering forum presentation [Molecular Med TriCon Feb 2011]

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Online molecular diagnostics &Online molecular diagnostics &

personalized medicinepersonalized medicine

�� WhatWhat && Why?Why?

�� ChipDX platformChipDX platform

�� Novel genomic signaturesNovel genomic signatures

�� IIn 5 years?n 5 years?



What is ChipDX?What is ChipDX?

� Background: Agendia/NKI (Netherlands) &Peter MacCallum Cancer Center (Australia)

�

A web start-up that develops, validates anddelivers In-Vitro Diagnostic Multi-Index Assays(IVDMIAs)

� A novel gene expression analysis platform:

± Bioinformatics tools

± Large publicly available genomic datasets

± Web application and database development



Why start ChipDX?Why start ChipDX?

CLINICALNEED

AVAILBLE

DATA

BIO-INFORMATICS



Overview: ChipDX.comOverview: ChipDX.com

ChipDX alysis SystemChipDX alysis System

Diagnostic est odules

Tumor

Origin

Br east

Cancer

Colon

Cancer

3rd Party

Modules

3rd PartyModules

3rd Party

odules

Shar ed cor e components

Ge eChipupload & pr e-

processing

ChipDXQuality

Module

Data

pr esentation

& resultsdow

load

Emailotificatio

system



� Based on experience with FDAstandards for clinical geneexpression analysis.

� Automatically run on eachGeneChip after upload

� Measure background intensity,replicate variation, signal-to-noiseratio, housekeeping genes«

� Results color-coded andpresented for easy interpretation

� Thresholds determined fromChipDX dataset of 3,000+GeneChip profiles.

GeneChip Quality ModuleGeneChip Quality Module



Tumor Origin ModuleTumor Origin Module

� Clinical need: Difficult to diagnosetumors (metastatic or poorlydifferentiated) limit treatment options,often resulting in poor survival times.

� Method: expression profile is generatedfrom a biopsy of the tumor & comparedto large database of tumors of known

origin.

� Validated on >1,000 primary tissues and>200 metastases,

� 89-94% agreement with clinical dx

� Used as additional QC step for otherprimary-tissue modules.



Background: Prognosis Prediction in OncologyBackground: Prognosis Prediction in Oncology

� Not all cancerdiagnoses require

aggressive treatment.

�

Early-stage tumors withlow risk of recurrence:often no benefit to

chemotherapy.

� Clinical predictors of

outcome: lead to overand under-treatment.

� Molecular risk predictors may be more

accurate & less

objective.

St e 1 l cancer (SOC: No CTx)

Pre-invasive breast cancer (SOC: CTx)

No

Ctx

Ctx

No

Ctx

CtxCtx

No

Ctx



Prognostic Test ModulesPrognostic Test Modules

Cancer type: Breast Colon Lung

Test type Prognosis PrognosisPrognosis +Tx response

Method of development

Whole-genome expression profiles, select genes associated withoutcome over and above clinical covariates, train ¶metagenes·

Number of genes insignature

200 163 160

Independentvalidation series

1,016 patients,multiple categories

60 stage 2/3 patients389 stage 1-3

patients

Improvement overtraditional methods

Yes Yes Yes

PublicationJournal of Molecular

Diagnostics, May

2011

British Journal of Cancer,November

2010

In progress«



y = -0.3249 + 1.0635 x

Cusum testfor linearity

No significant

deviation fr om

linearity (P>0.10)

Passing & Bablok Regression:

Intr aclass correlation coefficient:

0.939 (95% CI: 0.814 to 0.981)

The Intraclass corr elation coeff icient (ICC) is

a measur e of the r eliability of measur ements

or ratings.

Passing Bablok r egr ession is id eal f or comparing

clinical methods because it allows measur ement error ( impr ecision) in both the X and Y v ariabl es,

does not assume measur ement error is nor mally

distributed, and is robust against outliers.

Raw data: GenomeDxBiosciences Inc

Analysis by:

Frozen vs. FFPEFrozen vs. FFPE

tissuetissue

Matched Affymetrix U133a profiles, 2colon, 2 lung tumors x 3/4 biological

replicates.



Analysis

ModuleAnalysis

ModuleAnalysis

Module

Online delivery systemOnline delivery system

� Fully automated:

GeneChip CEL file in,

result out, ~10 mins.

�

ASP.net, SQL Server,R, Bioconductor

� HIPAA compliant

� Designed forscalability: modules &

throughput.

� Emphasis on data

accessibility & end-result visualization.

Quality

Module

Analysis

Module

www.ChipDX.comwww.ChipDX.com



Module DesignerModule Designer

Allow researchers to createcustomized diagnostic analysismodules using the ChipDX.comframework

Guided workflow:

1. Upload or copy/paste:

a) Probe list,

b) Classification template

c) Threshold

2. Select data pre-processing &normalization options

3. Design a customized results pageusing tools provided



ChipDX Vision for Global IVDMIA AccessChipDX Vision for Global IVDMIA Access

Genomicsignaturedeveloped

Genomicsignaturedeveloped

Genomicprofileanalyzed

Genomicprofileanalyzed

Upload to customChipDX AnalysisModule



ChipDX In Five YearsChipDX In Five Years

� Provide access to the latestdiagnostic, prognostic andpredictive molecular assays.

�

Contribute to universal standardsfor assessing the quality andreliability of genomic data forclinical use.

� A cloud-based processing engine for3rd party IVDMIA developers.

� Integrated with genomics equipmentand accessed via mobile technologyplatforms.





SummarySummary

� ChipDX has developedmultiple novel genomic

tests.

�

IP / Pre-IDE� Early-stage discussions with

clinical partners

� Expandable, secure andscalable analysis platform

� Created an automated QC

system designed for clinical

use

� Peer-reviewed publications



Thank Thank--you!you!

Ryan Van LaarRyan Van Laar

[email protected]@chipdx.com

((347) 857347) 857--94159415

@@chipdxchipdx

Please sign up at www.ChipDX.com



Additional slides«



1. Colon Cancer Module1. Colon Cancer Module

� Clinical need:Treatment of patients withstage 2 colon cancer is controversial.Standard of care varies geographically.

� Multivariate method of gene selectionused to identify genes with prognosticexpression patterns.

� 163-gene algorithm created andvalidated in independent population of

stage 2/3 colon cancer patients (n=60)� Published November 2010, British

Journal of Cancer 103, 1852²1857



2. Breast Cancer Module2. Breast Cancer Module

� Test predicts the likelihood of recurrence => chemotherapybenefit.

�Outputs a ¶prognostic index·,assigns individual to risk group(similar to OncoType DX)

� Training series: multi-centre cohortof 477 patients

� Validated on multiple independentseries, over 1,000 patients.

� Published in Journal of MolecularDiagnostics [In press]



Documents

Early Oncology Partnering forum presentation [Molecular Med TriCon Feb 2011]