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Application of DOE Methodology to SNP Assay Development

Application of DOE Methodology to SNP Assay Development. Geetha Rajavelu Gretchen Kiser 2002 Quality & Productivity Research Conference Tempe, AZ June 5-7, 2002. Presentation Outline. Background Info Overview of SNP Assay Identifying Variables for Screening Experiment

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Application of DOE Methodology to SNP Assay Development

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  1. Application of DOE Methodology to SNP Assay Development Geetha Rajavelu Gretchen Kiser 2002 Quality & Productivity Research Conference Tempe, AZ June 5-7, 2002

  2. Presentation Outline • Background Info • Overview of SNP Assay • Identifying Variables for Screening Experiment • Screening Experiment Results • Optimization Work • Overall Performance Improvements • Concluding Remarks

  3. Background Info • In Q3 2000, CodeLink slides were affected by unexplained background. • All aspects of slide manufacturing and assay processes were examined for root causes. • An effort was launched to thoroughly characterize all processes (with no apriori assumptions).

  4. Target Amplification Scanning Drying Target Pooling & Fragmentation SBE Slide Washing, SA-Alexa Labeling & Post-labeling Slide Washing SBE Thermal Cycling SNP Assay Modules

  5. S N P DNA genomic primers primers PCR S N P Whole target DNA S N P Fragmented target S N P Allele on Bioarray ready to scan S N P S S s S S S s S Extension reaction on Bioarray Mediated by a DNA polymerase and labeled nucleotides Target hybridizes to probes on Bioarray SNP Assay Overview PCR clean-up & Fragmentation Washing & Secondary Labeling Add reaction mixture to Bioarray S = major allele s = minor allele Allele-Specific Extension

  6. Screening Experiment Info Objective: • To evaluate the contribution of any one variable, and the interactive contribution of any two variables of the SBE Thermal Cycling module, to the assay performance, as measured by the Signal/Noise ratio, the Call Rate and Accuracy, the Mean Pad IOD, and the Mean Blank Pad IOD. Preliminary Info: • Factor ranges based on single-variable experiments • Nuisance Factors: Dispense Slide Batches, Thermal Cyclers Design Details: • 212-6 fractional factorial design • Involved 65 runs, 2 slides/run • Took around 9 days to complete experiment

  7. Identifying Variables for the Allele-Specific Extension Reaction Reaction Mixture Target Concentration (F) Enzyme Concentration (G) tNTP Concentration (H) Salt1 Concentration (J) Salt2 Concentration (K) Buffer Concentration (L) Buffer pH (M) Thermal Cycler Number of Cycles (A) Extension Time (B) Denaturation Time (C) Extension Temperature (D) Denaturation Temperature (E)

  8. Selecting Significant Factor Effects

  9. Screening Experiment Analysis Results

  10. Interaction Effects

  11. Interaction Effects

  12. Interaction Effects

  13. Screening out Variables for Optimization Phase Parameters shaded in green represent subset chosen for inclusion in the optimization experiment.

  14. Response Surface Experiment Info Objective: • To determine factor settings which optimize the assay performance, as measured by the Signal/Noise ratio, the Call Rate and Accuracy, the Mean Pad IOD, and the Mean Blank Pad IOD. Variables: -- # of Cycles (A) -- Enzyme Conc (E) -- Extension Time (B) -- tNTP Conc (F) -- Extension Temp (C) -- Salt2 Conc (G) -- Denaturation Temp (D) Design Details: • Screening design augmented with axial runs using face-centered cube & D-Optimality criterion (24 runs total)

  15. Response Surface Modeling Results

  16. Numerical Optimization Criteria

  17. Numerical Optimization Results

  18. Optimal Region

  19. Optimal Region

  20. Optimal Region

  21. SNP Assay Modules – Characterized & Optimized Target Amplification Scanning Drying Target Pooling & Fragmentation (23 factorial; face-centered design in 3 factors) SBE Slide Washing, SA-Alexa Labeling & Post-labeling Slide Washing (27-2 fractional factorial; face-centered design in 5 factors) SBE Thermal Cycling (2 12-6 fractional factorial; face-centered design in 7 factors)

  22. Overall Performance Improvements Group 1 DOE specified master mix DOE specified thermocycle program Low salt TNT mix Low SA-Alexa 532 dilution Optimized Staining/Washing conditions Group 2 DOE specified master mix DOE specified thermocycle program High salt TNT mix High SA-Alexa 532 dilution Optimized Staining/Washing conditions Current Protocol Group 3 Current master mix Current thermocycle program Current TNT mix Current SA-Alexa 532 dilution Current Staining/Washing conditions

  23. Higher Call Rate with DOE-derived Conditions

  24. Higher Call Accuracy with DOE-derived Conditions

  25. 3X Improvement in Probe Intensity

  26. 3X Improvement in Signal/Noise

  27. Lower Background with DOE-derived Conditions

  28. Group 1 Group 2 Current Protocol Group 3

  29. Concluding Remarks • All experiments were planned and executed using Project Management approach (risks/assumptions, scheduling, etc.) • Sequential approach to experimentation is critical to studying complex processes. • Able to beat all odds!! The probability of successfully completing an experiment is inversely proportional to the number of runs, i.e.,1/65.

  30. Acknowledgements • SNP Assay Development Team • Project Management Team

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