Genomic Analysis Solutions from SAS

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1 Genomic Analysis Solutions from SAS Russell Wolfinger Gerhard Held Development Director Solutions Manager Genomics Analytical Applications SAS Institute Inc. SAS International Pictures: Human Genome Program

2 Genome: the entire DNA sequence of an organism Genes and Genomics Genomics: acquiring genome knowledge and determining what genes do Functional Genomics: The study of genes, their resulting proteins, and the role played by the proteins in the body's biochemical processes. Pictures: Human Genome Program

3 Genomics Relevance Pharma and more Medicine Disease management Regenerative biology Cloning Diagnostics Disease research reproduction Government Military Research/R&D Epidemiology Pharmaceuticals Drug discovery Phamacogenomics Target gene therapy Aging Viral vectors Genomics Agribusiness Hybrid processing Disease resistant strains Medical researach Drug discovery Genetically modified stock Gene therapy Nutrition Environment Waste management Environment cleanup Detoxification Chemicals Environment Manufacturing Petroleum IT Nanotechnology Biocomputers Quantum computing Source: The Convergence of Biology and IT, IDC 2001 Academia Research Software development Alliances/collaboration

4 Pharma Industry Problem Points Revenue Genomics and Target Research potentially useful for 1, 2, and 5 3. Shorten Period from Launch to Peak Sales 4. Maximize Peak Sales Patent Expiration 5. Extend Patent / Fight Generics Generic Erosion Patent Launch 20 Time 2. Speed Clinical Development of Winners and Minimize Risk by stopping Losers 1. Pick the Winners in Research

5 Discovery Process Changes Traditional linear process Drug discovery (6-12 yrs) Drug development (4-6 yrs) Identify drug target Lead discovery Lead Optimization Target validation Pre-Clinical studies Development Moving to concurrent processes Drug development (3 yrs) Drug discovery (3-5 yrs) Identify drug target Lead discovery Lead Optimization Development Process Goal: Identify failures early Target validation Pre-Clinical studies

6 Pharma Industry R&D Trends! R&D costs increasing! $ million to launch a new drug! Massive Changes in Discovery Research! Data Volume requires both data management and analysis solutions! Genomics/Proteomics major driver! High Throughput Screening (HTS)! Promise of personalized Medicine! In-silico research

7 Scientific Discovery Requirements Boston Consulting Group, 2001! optimized information flow across the newly industrialized research and development value chain! centralized knowledge management system! capture and store the data! integrate it with external data! make it available throughout the company! powerful analytical tools to mine and make sense of the data - sophisticated algorithms, visualization tools, and so on Boston Consulting Group, A Revolution in R&D: How genomics and genetics are transforming the pharmaceutical industry. November 2001

8 Scientific Discovery and SAS! Refers to SAS core competencies: data warehousing, integrated meta data management, data mining and statistical analysis! Engels, Knapen, Tollenaere: Approaches for mining HTS Data Sets, European QSAR Symposium, Oct 2000! Kistemaker, Bouman (TNO), Bioinformatics as a Datawarehousing Approach, HUGS 2001

9 SAS Scientific Discovery Solutions! Available now - current technology solutions warehousing, mining, web technologies, EG! Targeted solutions in preparation, value proposition:! Streamlines data management through integration and centralization! Brings centralized data access vehicle to the end user- analysis, visualization, data transformations! Leverages investments made in other systems

10 SAS Scientific Discovery Solutions G23 Research Data Management RDM will be core to the product line SNP/ Marker Solution (1Q03) HTS Solution 2003 Proteomics Solution 2003 Microarray Solution (4Q02) Analytics Analytics Analytics Analytics Visualization Visualization Visualization Visualization Data models Data models Data models Data models Data engines Data engines Data engines Data engines

11 SAS Research Data Management! Centralized access and management vehicle for all discovery research data! SAS Research Data Management(RDM) based on WA, added capabilities include:! Automation of routine data transformations (Input Engines, Output engines)! Centralization of all metadata contained in warehouses within RDM (PMR, Pooled Metadata Repository)! Information exchange across groups (internet access, object types, search tools)! Enable compliance with 21CFR11 regulations (security, audit trail)

12 RDM Platform Input Engine Source A SAS/WA M M M Pooled Metadata Repository (PMR) SAS/WA M Input Engine Source B Other Data Sources User Interface Search & Access Upload Results Interactive Output Engine A Output Engine B User Specified Location Analysis-Ready Data and Reports

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15 SAS Microarray Solution Brings sound statistical methods to analyze microarray experimental results, create consistency! Identify related genes with confidence! Achieve repeatability! Standardize across chips, experiments, labs Packaged Solution Approach: Analytics Visualization Storage(RDM) Data models for microarray data

16 Analyses Flexibility Select analyses! Set up experimental design! Descriptive statistics! Mixed models! Multivariate analyses Stored processes! Set up and store your standard analyses

17 Graphics Flexibility Graphics in line with statistical analysis Residual plots Histograms (data, R 2, variance components) Volcano plots Visual data mining Heat maps Dendrograms

18 Drosophila Example from Gibson Lab at NC State Split-Plot Design: 2 lines X 2 genders (whole plot) 2 ages X 2 dyes (sub plot) 6 reps including dye swaps 24 total arrays Jin et al. (2001) Nature Genetics 29:

19 Genetic Marker Data ACATGGCTATGTCC ACATGGATATGTCC

20 Genetics Terminology! Locus: place on a chromosome where a gene or marker is located! Marker: section of DNA that differs among individuals and whose inheritance can be followed! Allele: one particular form of a gene or marker (e.g. A,a)! Genotype: the pair of alleles (one from mother, one from father) at a single locus (e.g. A/A, A/a, a/a)! Haplotype: set of alleles from a single chromosome ACATGGCTATGTCC ACATGGATATGTCC

21 SAS/Genetics Consists of 5 procedures and 1 macro for DNA marker data! Proc Allele! Proc Casecontrol! Proc Family! Proc Haplotype! Proc Psmooth

22 Graphical Presentation of Results

23 SAS/Genetics Status! Available immediately! Limited availability your feedback appreciated! Experience will be re-integrated into SAS Discovery Solutions (SNP/Marker solution)

24 SAS Scientific Discovery Solutions G23 Research Data Management RDM will be core to the product line SNP/ Marker Solution (1Q03) HTS Solution 2003 Proteomics Solution 2003 Microarray Solution (4Q02) SAS/Genetics Analytics Analytics Analytics Visualization Visualization Visualization Visualization Data models Data models Data models Data models Data engines Data engines Data engines Data engines

25 Genomic Analysis Solutions from SAS! Genomic solutions require optimized information flow, centralized meta data management, scalability, and powerful analytics! SAS offers many required technologies now: warehousing, mining, stat, web, EG! SAS Scientific Discovery solutions will package these in a comprehensive research-driven framework

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