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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
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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
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4000
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10000
12000
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005Year
To
tal
Nu
mb
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of
Pu
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ati
on
s
# 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
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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