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Comparison of Performance of Laboratory Equipment 1 Manginelli , 2 Hoyer , 3 Brestrich Dr. Angela A. Dr. Walter Dr. Gordon 1) R&D Statistics, 2) CMC Statistical Science, 3) Clinical Laboratory Science Emil-von-Behring-Straße 76 D-35041 Marburg, Germany. Abstract The Three Liquid Handlers • Within the validation of a new highly automated assay, the Clinical Laboratory Science tested several clinical samples in order to evaluate precision and linearity of the assay. • The equipment utilized for the testing includes three liquid handlers (highly automated pipetting robots). • The statistical evaluation of the data revealed a significantly poorer performance of one liquid handler compared to the other two. • To detect the root cause of the issue, an intensive work including complete dismantling of the machine with help of a technician of the vendor was conducted. • A tiny difference in the programming code of the liquid handlers was detected. • JMP 11.0.0 was used for the statistical evaluation before and after the adjustment of the setting of the liquid handlers. Maja Bonnie Kriemhild Comparison of Performance of Laboratory Equipment 1 Manginelli , 2 Hoyer , 3 Brestrich Dr. Angela A. Dr. Walter Dr. Gordon 1) R&D Statistics, 2) CMC Statistical Science, 3) Clinical Laboratory Science Emil-von-Behring-Straße 76 D-35041 Marburg, Germany. How The Assay Works – Serial Dilution Scheme Automated pipetting 384 Well – Micro titer plate Transfer 14 µL Bacteria Step 1 Sample + Buffer Mix 1:2 28 µL Predilution Buffer 14 µL Buffer 14 µL Buffer 14 µL Transfer 14 µL Step 2 Mix 1:2 Mix 1:4 Buffer Buffer (diluent) 384 Well – Micro titer plate Buffer Transfer 14 µL Step 3 .... Mix 1:2 .... Mix 1:4 .... Mix 1:8 .... Buffer .... • After incubation time, the number of surviving bacteria is determined by means of measurement of fluorescence intensity. Sample 1 Sample 1 1:2 Sample 1 1:4 Sample 2 Sample 2 1:2 Sample 2 1:4 Normalized values Human complement Serum of vaccinated donors Predilution and Titer Determination Inflection Point Log(Dilution) • Serial dilution is used to determine titer. • The bactericidal antibody titer is the reciprocal dilution of the serum at which 50% of bacteria are killed. Comparison of Performance of Laboratory Equipment 1 Manginelli , 2 Hoyer , 3 Brestrich Dr. Angela A. Dr. Walter Dr. Gordon 1) R&D Statistics, 2) CMC Statistical Science, 3) Clinical Laboratory Science Emil-von-Behring-Straße 76 D-35041 Marburg, Germany. Dilutional Linearity • Samples are tested on three liquid handlers which are expected to deliver identical results. Results Error bars: 95% confidence interval of the mean • Relative accuracy of the assay is evaluated by means of dilutional linearity. Liquid Handler Bonnie Kriemhild Maja • Dilutional linearity is assessed by computing Recovery Rate (RR): ratio between the geometric mean (GM) of the two replicates at one predilution and the GM at previous predilution. • 20 samples (serum) 40 RRs on each robot (one for 1:2 and one for 1:4 predilution). Mean RR [%] 90 98 97 Std Dev RR 0.28 0.10 0.12 • Lower RR and higher variability on Bonnie. • Difference in RRs was significant (GLM) when removing the outlier circled in red (p = 0.0102). Statistician The reaction of the team Lab Manager Lab Operator Comparison of Performance of Laboratory Equipment 1 Manginelli , 2 Hoyer , 3 Brestrich Dr. Angela A. Dr. Walter Dr. Gordon 1) R&D Statistics, 2) CMC Statistical Science, 3) Clinical Laboratory Science Emil-von-Behring-Straße 76 D-35041 Marburg, Germany. Investigation and Solution Statistical Confirmation • Lab operator and technician of the vendor were locked for three weeks in the lab to investigate the issue. • They compared the setting of the three liquid handlers ... • ... and found out that the pipet of Bonnie was set to a different mixing speed compared to the other two: ~16 µl/sec vs ~24 µl/sec • The setting was adjusted and the experiment was repeated: 24 Samples: undiluted, 1:2 and 1:4 prediluted 2 Replicates (to be averaged) for each predilution on each robot 18 measurement for each sample, 6 per robot 2 RRs for each sample on each robot (for predilutions 1:2 and 1:4) Conclusion • Stay calm, keep trying! • Never underestimate the importance of small things! • Luckily with JMP it is possible to write very nice and useful scripts! Add Image Comparison of Performance of Laboratory Equipment 1 Manginelli , 2 Hoyer , 3 Brestrich Dr. Angela A. Dr. Walter Dr. Gordon 1) R&D Statistics, 2) CMC Statistical Science, 3) Clinical Laboratory Science Emil-von-Behring-Straße 76 D-35041 Marburg, Germany. JMP Platform/Script Used • Graph Builder and ANOVA model 4. Log function • Script to do the analysis BEFORE and AFTER the issue: 1. Import xlsx file 5. Lag function to create RR 2. Stack and adjust column names 3. Munger function