1 / 21

Effort 1 – Voluntary Genomics Data Submission (VGDS)

This article discusses the efforts and initiatives in voluntary genomics data submission for pharmacogenomics research, including the FDA guidance to industry, the ArrayTrack tool, the development of best practice documents, and the MicroArray Quality Control project.

tinaa
Download Presentation

Effort 1 – Voluntary Genomics Data Submission (VGDS)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 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 Frueh Nat. Biotechnol. 24(9):1105-1107, 2006

  2. 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

  3. Microarray data Proteomics data Metabolomics data Public data ArrayTrack: An Integrated Solution for omics research Clinical and non-clinical data Chemical data ArrayTrack

  4. Protein Gene Metabolite

  5. Study domain Array domain TOOL TOOL Study DB Microarray DB LIB

  6. 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

  7. R Gene Expression vs Clinical Pathology Gene Gene name is hidden Clinical pathology data CLinChem name is hidden R=0.72 Each cell represents a gene-ClinChem correlation The color represents the degree of correlation Gene Clinical pathology

  8. ProteinTools MetaboliteTools Proteomics DB Metabonomics DB ToxicantLib ArrayTrack/SysTox- From VGDS to VXDS GeneTools Microarray DB GeneLib ProteinLib PathwayLib

  9. Storing Protein and Metabolite Lists Examining common pathways and functions shard by expression data from genomics, proteomics and metabolomics

  10. ArrayTrack-Freely Available to Public Web-access Local installation # of unique users access the locally installed version of ArrayTrack # of unique users access the web version of ArrayTrack

  11. Knowledge Base • ToxicantLib • Liver Tox Knowledge Base (LTKB) • Sex Determined Toxicity in Gene Expression • …

  12. 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

  13. Effort 4 - MicroArray Quality Control (MAQC) Project • 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 # of microarray-related publications indexed in PubMed has been increasing exponentially.

  14. Results from the MAQC Study Published in Nature Biotechnology on Sept and Oct 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 Validation Nat. Biotechnol. 24(9) and 24(10s), 2006 Plus: EditorialNature Biotechnology Foreword Casciano DA and Woodcock J Stanford Commentary Ji H and Davis RW FDA Commentary Frueh FW EPA Commentary Dix DJ et al.

  15. An Array of FDA Endeavors Best Practice Document MAQC VGDS ArrayTrack

  16. Bioinformatics Computational Toxicology Not One-Trick-Pony Regulation-Oriented Projects Bioinformatics Chemoinformatics statistics

  17. Input Tree 1 Tree 3 Tree 2 Tree 4 Combining Results Decision Forest – A robust consensus approach Key points • Combining several identical models produce no gain • Combining several highly correct models that disagree as much as possible • 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

  18. Bioinformatics Predictive Toxicology Computational Toxicology Not One Trick Pony Bioinformatics Chemoinformatics statistics

  19. 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 …

  20. 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

  21. Priority Setting of 58,000 Chemicals Prioritized Groups No. of Chemicals 124 317 3,183 6,186 30,012 • 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

More Related