Effort 1 – Voluntary Genomics Data Submission (VGDS)

• FDA Guidance to Industry: Pharmacogenomics data submission (Draft

2003, final publication 2005)

– Invite industry to submit microarray data at the voluntary basis – A VGDS

mechanism

– Facilitate scientific progress in the area of pharmacogenomics.

Felix FruehNat. Biotechnol. 24(9):1105-1107, 2006

Effort 2 - ArrayTrack

• Need a bioinformatics tool to accomplish:– Objective 1: Data repository

– Objective 2: Reproduce the sponsor’s results

– Objective 3: Conduct alternative analysis

• ArrayTrack – A FDA genomic tool

– AT version 1 (2001): Filter array; data management tool

– AT version 2 (2002): in-house microarray core facility

– AT version 2.2 (late 2003): Open to public

– AT version 3.1 (2004): VGDS

– AT version 3.2 (2005): MAQC

– AT version 4 (2006 – present): VGDS VXDS

Microarray data

Proteomics data

Metabolomics data

Chemical data

Clinical and non-clinical

data

Public data

ArrayTrack

ArrayTrack: An Integrated Solution for omics research

ProteinGeneMetabolite

Study DB

TOOL

Study domain

MicroarrayDB

TOOL

Array domain

LIB

Study Data Management and Analysis

• FDA eSubmission efforts

– Clinical data: Clinical Data Interchanges Standards

Consortium (CDISC)

– Non-clinical data: Standard for Exchange of Nonclinical Data

(SEND)

• Subject, treatment, Clinical pathology, histopathology, …

• Conforming to SDTM used for CDISC/SEND

• Microarray data management and analysis are processed

in Array Domain and the findings are available to correlate

with data in Study Domain

Gene Expression vs Clinical PathologyC

linical p

athology d

ata

R=0.72

Gen

e

Clinical pathologyR

Each cell represents a gene-ClinChem correlation

The color represents the degree of correlation

CL

inC

hem

nam

e is hid

den

Gene name is hidden

Gene

ProteinLib PathwayLib

ProteinTools

ProteomicsDB

MetaboliteTools

MetabonomicsDB

ToxicantLib

ArrayTrack/SysTox- From VGDS to VXDS

MicroarrayDB

GeneLib

GeneTools

Storing Protein and Metabolite Lists

Examining common pathways and functions shard by expression data from genomics, proteomics and metabolomics

ArrayTrack-Freely Available to Public

0

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# of unique users access the web version of ArrayTrack

# of unique users access the locally installed version of ArrayTrack

Web-access Local installation

Knowledge Base1. ToxicantLib 2. Liver Tox Knowledge Base (LTKB)3. Sex Determined Toxicity in Gene Expression4. …

Effort 3 - Best Practice Document

• One of the VGDS objectives is to communicate with the private industry and gain experience on – How to exchange genomic data (data submission)

– How to analyze genomic data

– How to interpret genomic data

• Lessons Learned from VGDS has led to development of Best Practice Document (Led by Federico Goodsaid)– Recommendations for the Generation and Submission of Genomic Data

(Nov 2006) (http://www.fda.gov/cder/genomics/conceptpaper_20061107.pdf)

• ArrayTrack translates “Best Practice” into real practice

• QC issue – How good is good enough?– Assessing the best achievable

technical performance of microarray platforms (QC metrics and thresholds)

• Analysis issue – Can we reach a consensus on analysis methods?– Assessing the advantages and

disadvantages of various data analysis methods

• Cross-platform issue – Do different platforms generate different results? – Assessing cross-platform consistency

Effort 4 - MicroArray Quality Control (MAQC) Project

The number of microarray-related publications indexedin MEDLINE has been increasing exponentially.

3823

2 8 15 51 190 621

1760

6815

(Estimated)11000

0

2000

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6000

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10000

12000

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005Year

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# of microarray-related publications indexed in PubMed has been increasing exponentially.

Results from the MAQC Study Published in Nature Biotechnology

on Sept and Oct 2006

Nat. Biotechnol. 24(9) and 24(10s), 2006

Six research papers:

• MAQC Main Paper

• Validation of Microarray Results

• RNA Sample Titrations

• One-color vs. Two-color Microarrays

• External RNA Controls

• Rat Toxicogenomics ValidationPlus:

Editorial Nature BiotechnologyForeword Casciano DA and Woodcock JStanford Commentary Ji H and Davis RWFDA Commentary Frueh FWEPA Commentary Dix DJ et al.

An Array of FDA Endeavors

ArrayTrack

MAQCVGDS

Not One-Trick-Pony

Computational Toxicology

statistics

Bioinform

aticsC

hem

oinf

orm

atic

s

Regulation-Oriented Projects

Bioinformatics

Decision Forest – A robust consensus approach

DF-Array: Classification using gene expression data

DF-SELDI: Classification using proteomics data

DF-SNPs: Classification using SNPs profiles

DF-Seq: Sequence-based classification of protein function

DF-SAR: Predictive tox using chemical structure

Tree 1 Tree 4Tree 3Tree 2

Input

Combining Results

Key points• Combining several

identical models produce no gain

• Combining several highly correct models that disagree as much as possible

Not One Trick Pony

Computational Toxicology

statistics

Bioinform

aticsC

hem

oinf

orm

atic

s

Bioinformatics

Predictive Toxicology

Endocrine Disruptors• An international issue

• Two laws passed by US congress require evaluation of

chemicals found in foods and water for endocrine

disruption.

• Similar regulation is also implemented in Europe and

Asia

• ~ 90,000 commercial chemicals needs to be screened

• EPA has identified ~58,000 eligible chemicals

• A minimum of 8,000 of the 58,000 chemicals are FDA-

regulated, including cosmetic ingredients, drug products

…

Overview of NCTR’s Endocrine Disruptor Knowledge Base (EDKB)

• Begun 1996, prior to endocrine disruptor (ED) issues

• ED issues emerge - ACC and EPA collaboration & support results

• Program expands:– Separately assayed over >200 chemicals for estrogen (ER),

androgen (AR), serum protein (AFP and SHBG) receptor binding

– Web-based relational database with in vitro and in vivo assay data, bibliography and chemical structure search

– Exhaustive SAR/QSAR model development for both ER and AR binding, guided by data and crystal structures

3

5

412

12345

124

317

3,183

6,186

30,012

PrioritizedGroups

No. ofChemicals

Priority Setting of 58,000 Chemicals

• Only ~3600 chemicals need to be tested

• ~6200 chemicals might be active with activity below 100,000-fold less than estradiol

• 30,000 chemicals are predicted to be inactive