2007 CPSA - Poster - Automated Bioanalytical Sample Preparation
1
Abstract Objectives Results Conclusion Acknowledgements An Automated Dynamic BioAnalytical Sample Preparation Routine for Integration with Liquid Handlers Charles E. Taylor 1 , Qiner Yang 2 , John P. Walsh 1 and Robyn A. Rourick 1 Kalypsys, Inc. Pharmaceutical Sciences Department 1 and Informatics 2 10420 Wateridge Circle, San Diego, CA 92121 The Analytical Chemistry department at Kalypsys has developed and implemented an automated sample preparation method for its routine BioAnalytical work. The purpose of this system was to assume the work effort of protein precipitation sample preparation, reducing the FTE time required per study. Designed to process sample plates with any combination of matrices and layouts into methodical injection plates, the system is able to achieve much of the sample arrangement that a human analyst would provide. The system depends on proper plate map registration; a tool was developed to allow users to populate the database with a platemap containing animal number, compound number, dose type, matrix, model, time point and concentration for each well of a plate. A server based program crafts a liquid handler script that constructs the corresponding injection plate(s) from the sample plate(s), once the desired calibration curve is chosen on the web based user interface. The resulting script is a standalone file, not a work list, which is recognized and executed by Tecan’s Gemini software. The script generator optimizes the liquid handling by mimicking the logic a human analyst would use in injection plate construction. One representation is the ordering of samples into the densest arrangement. This allows, in some cases, multiple sample plates to be condensed into one injection plate. Another is the detection of multiple compounds in the plate, which triggers the generator to program the construction of corresponding calibration curves and CS0 samples. With the capabilities in place, the ruggedness testing and performance trials were initiated. The system met specification for standard curve construction and consistency of internal standard concentrations in multiple matrices. Tractability of preparation error is achieved by monitoring the liquid handling error log files, and making database tags of any samples that initiated a liquid handling error. Expansion efforts are targeted for the system and include: automated SPE, hemolysis tracking, liquid-liquid extraction, matrix expansion and high density plate use. These efforts look to capture a larger portion of the workflow and position this system as a multipurpose BioAnalytical platform. Stock Solution 200ug/mL of Analyte in 50:50 acetonitrile:water Vortexed and sonicated Internal Standard (IS) 500ng/mL deuterated Analyte (Analyte-D6) in acetonitrile Vortexed and sonicated CS0 Controls 25uL of blank plasma was combined with 100uL of IS and placed in the same precipitation plate as the standard concentration samples. Double Blank Controls 25uL of blank plasma was combined with 100uL of acetonitrile Placed in the same precipitation plate as the standard concentration samples. Plasma Standard Curve Generation Serial dilution of a concentrated, spiked solution was performed in blank plasma Each level was thoroughly mixed via aspiration/dispensation repetitions Plasma Preparation 25µL of each spiked standard concentration was transferred to a deep well plate. 100µL aliquot of the internal standard was added to each of the wells in the plate to track the extraction, analysis and to act as a precipitating agent. Precipitation Plate Preparation CS0 Controls and the Double Blank Controls added to the plate Mixed thoroughly on a multitube vortexer. Centrifuged at 35000rpm for 20min and Injection Plate Preparation 50µL of each supernatant from precipitation plate transferred to a deep-well microtitre plate. 50µL Milli-Q water was added 15µL injected according to the listed analysis method. Automated construction of standard curves by the liquid handler for different animal model plasmas was successful. Standard curves had greater than 6 points with weighted regression values exceeding 99% Data points within these curves passed tolerability for inclusion using the 85% to 115% rule The lower limits of quantification (LLOQ) for these automated prep samples were very linear, proving the ability for the method to carry out a precise serial dilution in viscous medium Server based liquid handler file generator is able to create production capable files This ability for an automated platform to produce injection ready samples from raw materials positions this method as a front running technology that is ready to be utilized in the Kalypsys BioAnalytical workflow. The authors would like to thank the following individuals for their input and contributions: Nahid Yazdani, Michael Herman and Tiffany Chea. Document Reference Subject AC-MethDev-2007-015v1 BioA Tecan Sample Prep Poster Contact Email Charles Taylor [email protected] Product Reference Manufacturer Freedom EVO 100 Tecan AG Costar Deep Well Plate Corning Costar Shallow V-Well Plate Corning 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 Analyte Area / IS Area C57 Male Mouse Plasma Figure 1a: Expanded view of Mouse Plasma LLOQ Figure 2a: Expanded view of Mouse Plasma LLOQ Manual Preparation Automated Preparation Male Rabbit Plasma Figure 5a: Expanded view of Rabbit Plasma LLOQ Figure 6a: Expanded view of Rabbit Plasma LLOQ Manual Preparation Automated Preparation 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 Analyte Area / IS Area Male Cynomolgus Monkey Plasma Figure 9a: Expanded view of Cyno Monkey Plasma LLOQ Figure 10a: Expanded view of Cyno Monkey Plasma LLOQ Manual Preparation Automated Preparation 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 Analyte Area / IS Area Sprague-Dawley Male Rat Plasma Figure 3a: Expanded view of Rat Plasma LLOQ Figure 4a: Expanded view of Rat Plasma LLOQ Manual Preparation Automated Preparation 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 Analyte Area / IS Area Male Beagle Plasma Figure 7: Automated Liquid Handler Generated Calibration Curve for Beagle Plasma Figure 7a: Expanded view of Beagle Plasma LLOQ Figure 8a: Expanded view of Mouse Plasma LLOQ Manual Preparation Automated Preparation 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 Analyte Area / IS Area Human Plasma Figure 11a: Expanded view of Human Plasma LLOQ Figure 12a: Expanded view of Human Plasma LLOQ Manual Preparation Automated Preparation Source Type Turbospray Ionization ESI + (positive) Source Temperature 500 Spray Voltage 5.5 kV Collision Gas (CAD) Medium Curtain Gas 10 Ion Gas 1 50 Ion Gas 2 60 Entrance Potential 22 Scan Type Multiple Reaction Monitoring (MRM) MS Parameters Equipment List Analytical Balance Mettler Toledo AX26 Liquid Handler Tecan Freedom EVO 100 Tip Configuration 8 Disposable Tip Mounts (DiTi) Tip Sizes Used 200 ∝ L DiTi Tips 1000 ∝ L DiTi Tips HPLC System Pump Agilent HP1100 Binary Pump Degasser Agilent HP1100 Autosampler CTC PAL HPLC Conditions Flow Rate 1000∝ L/min Mobile Phase A: 0.1% Formic Acid in Water B: 0.1% Formic Acid in Acetonitrile Gradient 0.0 – 1.0 min: 10%B to 95%B 1.0 – 1.9 min: 95%B 2.0 – 2.7 min: 10%B Injection Volume 5 ∝ L Column Phenomenex Polar-RP 2.0x30mm, 4∝ m Plasma Conc. Vol of Prev Vol of Blank Total Vol Remaining Vol (ng/mL) (uL) (uL) (uL) (uL) 10000 35 of stock 665 700 250 7500 450 150 600 240 5000 360 180 540 290 2500 250 250 500 250 1000 250 375 625 375 500 250 250 500 250 250 250 250 500 250 100 250 375 625 375 50 250 250 500 250 20 250 375 625 375 10 250 250 500 250 4 250 375 625 625 Table 2: Equipment used in the preparation and analysis. Table 4: Mass spectrometer parameters used in the MS/MS detection of the analyte and inter- nal standard. Table 3: HPLC parameters used in the analysis of the compounds. Table 1: Serial dilution used in the construction of the standard curves in each plasma type. Figure 3: Automated Liquid Handler Generated Calibration Curve for Rat Plasma Figure 14: The analyte peaks were consistent in retention time, with the higher concentrations maintaining good peak shape (14a). The IS trends for the studies are shown in Figure 14b, with the colors corresponding to the replicate as shown in the calibration graph section. The attenuation in intensity (Figure 14b) is due to the presence of two IS batches. The crosses in Figure 14b correspond to manually prepared trials; the circles represent automated trials. Figure 9: Automated Liquid Handler Generated Calibration Curve for Cyno Monkey Plasma 0 20 40 60 80 100 120 140 160 180 200 220 240 260 Analyte Conc. / IS Conc. 0.00 0.05 0.10 0.15 0.20 Analyte Area / IS Area 100807_Trial7_Manual_Mouse.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000244 x + 0.00143 (r = 0.9957) 101407_Trial24_Manual_Mouse.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000501 x + 0.004 (r = 0.9989) 101407_Trial30_Manual_Mouse.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000511 x + 0.0162 (r = 0.9986) 0.0 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 1.0 2.0 3.0 4.0 5.0 Analyte Area / IS Area Curve R 2 Slope 1st .9957 .000244 2nd .9989 .000501 3rd .9986 .000511 Figure 1: Automated Liquid Handler Generated Calibration Curve for Mouse Plasma 0 20 40 60 80 100 120 140 160 180 200 220 240 260 Analyte Conc. / IS Conc. 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 Analyte Area / IS Area 100507_Trial3_Manual_Rat.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000471 x + 0.00225 (r = 0.9958) 101407_Trial25_Manual_Rat.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000498 x + 0.00391 (r = 0.9969) 101407_Trial31_Manual_Rat.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000511 x + 0.0126 (r = 0.9990) 0.0 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 1.0 2.0 3.0 4.0 5.0 Analyte Area / IS Area Curve R 2 Slope 1st .9958 .000471 2nd .9969 .000498 3rd .9990 .000511 0 20 40 60 80 100 120 140 160 180 200 220 240 260 Analyte Conc. / IS Conc. 0.00 0.05 0.10 0.15 0.20 0.25 Analyte Area / IS Area 100807_Trial9_Manual_Rabbit.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000247 x + 0.0011 (r = 0.9978) 101407_Trial26_Manual_Rabbit.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.0005 x + 0.00472 (r = 0.9987) 101407_Trial32_Manual_Rabbit.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.00046 x + 0.0133 (r = 0.9992) 0.0 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 1.0 2.0 3.0 4.0 5.0 Analyte Area / IS Area Curve R 2 Slope 1st .9978 .000247 2nd .9987 .0005 3rd .9992 .00046 Figure 5: Automated Liquid Handler Generated Calibration Curve for Rabbit Plasma 0 20 40 60 80 100 120 140 160 180 200 220 240 260 Analyte Conc. / IS Conc. 0.000 0.020 0.040 0.060 0.080 Analyte Area / IS Area 101207_Trial11b_Manual_Beagle.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.00034 x + 0.00237 (r = 0.9977) 101407_Trial27_Manual_Beagle.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000504 x + 0.00544 (r = 0.9962) 101407_Trial33_Manual_Beagle.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000522 x + 0.00987 (r = 0.9951) 0.0 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 1.0 2.0 3.0 4.0 5.0 Analyte Area / IS Area Curve R 2 Slope 1st .9977 .00034 2nd .9962 .000504 3rd .9951 .000522 0 20 40 60 80 100 120 140 160 180 200 220 240 260 Analyte Conc. / IS Conc. 0.00 0.05 0.10 0.15 0.20 0.25 Analyte Area / IS Area 101407_Trial34_Manual_Cyno.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.00103 x + 0.0122 (r = 0.9974) 100807_Trial13_Manual_Cyno.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000231 x + 0.00366 (r = 0.9952) 101407_Trial28_Manual_Cyno.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000556 x + 0.00374 (r = 0.9973) 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 2.0 4.0 6.0 8.0 Analyte Area / IS Area Curve R 2 Slope 1st .9974 .0122 2nd .9952 .00366 3rd .9973 .00374 0 20 40 60 80 100 120 140 160 180 200 220 240 260 Analyte Conc. / IS Conc. 0.00 0.05 0.10 0.15 0.20 0.25 Analyte Area / IS Area 101407_Trial35_Manual_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000544 x + 0.00965 (r = 0.9964) 100807_Trial15_Manual_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000233 x + 0.00187 (r = 0.9953) 101407_Trial29_Manual_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000465 x + 0.00446 (r = 0.9983) 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 1.0 2.0 3.0 4.0 5.0 Analyte Area / IS Area Curve R 2 Slope 1st .9964 .000544 2nd .9953 .000233 3rd .9983 .000465 Figure 11: Automated Liquid Handler Generated Calibration Curve for Human Plasma 0 20 40 60 80 100 120 140 160 180 200 220 240 260 Analyte Conc. / IS Conc. -0.04 -0.02 0.00 0.02 0.04 0.06 0.08 Analyte Area / IS Area 100807_Trial17_FullAuto_Mouse.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000299 x + 0.00112 (r = 0.9977) 101507_Trial36_FullAuto_Mouse.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000295 x + 0.00198 (r = 0.9975) 101507_Trial42_FullAuto_Mouse.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000276 x + 0.00187 (r = 0.9971) 0.0 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 3.9 Analyte Area / IS Area Curve R 2 Slope 1st 0.9977 .000299 2nd 0.9975 .000295 3rd 0.9971 .000276 0 20 40 60 80 100 120 140 160 180 200 220 240 260 Analyte Conc. / IS Conc. -0.04 -0.02 0.00 0.02 0.04 0.06 0.08 Analyte Area / IS Area 101207_Trial22_FullAuto_Rat.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000232 x + 0.00116 (r = 0.9983) 101507_Trial37_FullAuto_Rat.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000307 x + 0.00293 (r = 0.9980) 101507_Trial43_FullAuto_Rat.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000284 x + 0.00217 (r = 0.9965) 0.0 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Analyte Area / IS Area Curve R 2 Slope 1st .9983 .000232 2nd .9980 .000307 3rd .9965 .000284 Figure 4: Automated Liquid Handler Generated Calibration Curve for Rat Plasma 0 20 40 60 80 100 120 140 160 180 200 220 240 260 Analyte Conc. / IS Conc. -0.040 -0.020 0.000 0.020 0.040 0.060 0.070 Analyte Area / IS Area 100807_Trial18_FullAuto_Rabbit.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000285 x + 0.00107 (r = 0.9971) 101507_Trial38_FullAuto_Rabbit.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000304 x + 0.000751 (r = 0.9969) 101507_Trial44_FullAuto_Rabbit.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000264 x + 0.00164 (r = 0.9994) 0.0 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Analyte Area / IS Area Curve R 2 Slope 1st .9971 .000285 2nd .9969 .000304 3rd .9994 .000264 Figure 6: Automated Liquid Handler Generated Calibration Curve for Rabbit Plasma 0 20 40 60 80 100 120 140 160 180 200 220 240 260 Analyte Conc. / IS Conc. -0.040 -0.020 0.000 0.020 0.040 0.060 0.076 Analyte Area / IS Area 100807_Trial19_FullAuto_Beagle.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000276 x + 0.00138 (r = 0.9995) 101507_Trial39_FullAuto_Beagle.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000277 x + 0.000817 (r = 0.9949) 101507_Trial45_FullAuto_Beagle.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000281 x + 0.00205 (r = 0.9972) 0.0 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Analyte Area / IS Area Curve R 2 Slope 1st .9995 .000276 2nd .9949 .000277 3rd .9972 .000281 Figure 8: Automated Liquid Handler Generated Calibration Curve for Mouse Plasma 0 20 40 60 80 100 120 140 160 180 200 220 240 260 Analyte Conc. / IS Conc. -0.04 -0.02 0.00 0.02 0.04 0.06 0.08 0.09 Analyte Area / IS Area 101407_Trial23_FullAuto_Cyno.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000363 x + 0.000573 (r = 0.9983) 101507_Trial40_FullAuto_Cyno.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000298 x + 0.00228 (r = 0.9982) 101507_Trial46_FullAuto_Cyno.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000287 x + 0.000583 (r = 0.9980) 0.0 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 1.0 2.0 3.0 4.0 Analyte Area / IS Area Curve R 2 Slope 1st .9983 .000363 2nd .9982 .000298 3rd .9980 .000287 Figure 10: Automated Liquid Handler Generated Calibration Curve for Cyno Monkey Plasma Figure 2: Automated Liquid Handler Generated Calibration Curve for Mouse Plasma 0 20 40 60 80 100 120 140 160 180 200 220 240 260 Analyte Conc. / IS Conc. 0.000 0.020 0.040 0.060 0.080 0.100 0.120 Analyte Area / IS Area 100807_Trial21_FullAuto_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000292 x + 0.00119 (r = 0.9979) 101507_Trial41_FullAuto_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.00031 x + 0.000469 (r = 0.9997) 101507_Trial47_FullAuto_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000276 x + 0.00183 (r = 0.9994) 0.0 2000.0 4000.0 6000.0 8000.0 1.0e4 Analyte Conc. / IS Conc. 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Analyte Area / IS Area Curve R 2 Slope 1st .9979 .000292 2nd .9997 .000310 3rd .9994 .000276 Figure 12: Automated Liquid Handler Generated Calibration Curve for Human Plasma Experimental Figure 14a Figure 14b 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000 6500 7000 7500 8000 8500 9000 9500 10000 1.002 1.018 1.035 1.052 1.068 1.085 1.102 1.118 1.135 1.152 1.168 1.185 1.202 1.218 1.235 1.252 1.268 1.285 1.302 1.318 1.335 1.352 1.368 1.385 1.402 1.418 1.435 1.452 1.468 1.485 1.502 Peak Area Time (min.) Studies Plasma samples for this study are to be prepared by protein precipitation and monitored with an internal standard Quantification is to be performed through the generation of a standard curve Liquid handler is to use file generated from the server based script generator Curves are to exceed R 2 values of 0.99 Tolerability of data points included in the curve are to be between 85% and 115% Minimum of 6 points in a calibration curve LLOQ for every curve is not to exceed CS20 after data exclusion Manually Prepared Liquid Handler Prepared Data Compilation Decision Point Legend Rat Automatic Conc. R1 R2 R3 AVG CV CV AVG R1 R2 R3 Conc. 4 93.1% 102% 97.8% 97.63% 4.56% 100.92% 231.83% 97.9% 502% 95.6% 4 10 115% 86.9% 104% 101.97% 13.89% 6.96% 105.17% 104% 98.5% 113% 10 20 120% 112% 100% 110.67% 9.1% 7.94% 99.77% 101% 107% 91.3% 20 50 110% 103% 108% 107% 3.37% 10.65% 101.03% 104% 89.1% 110% 50 100 125% 97.4% 103% 108.47% 13.45% 2.82% 100.47% 101% 97.4% 103% 100 250 101% 113% 101% 105% 6.6% 3.91% 103.33% 101% 108% 101% 250 500 107% 103% 98.6% 102.87% 4.08% 2.5% 98.4% 101% 98.1% 96.1% 500 1000 103% 96.6% 97% 98.87% 3.63% 2.16% 95.8% 95.2% 98.1% 94.1% 1000 2500 97.1% 96.3% 105% 99.47% 4.83% 5.12% 98.5% 94.1% 104% 97.4% 2500 5000 91.2% 97.1% 95.3% 94.53% 3.2% 6.14% 96.3% 91.8% 103% 94.1% 5000 7500 92% 95.7% 94.6% 94.1% 2.02% 2.19% 95.2% 96.3% 96.5% 92.8% 7500 10000 90.2% 95.7% 96.2% 94.03% 3.54% 4.52% 115% 112% 121% 112% 10000 Rat Manual Table 5: The back-calculated concentrations of the standard curve plasma samples were made by entering the analyte peak area into the calibration curve, which those samples were used to construct. The tolerability of the standard curve point to be included in the curve is measured by it’s statistical difference from the theoretical concentration. Exclusion from the standard curve occurs when the point is outside of the 85% to 115% tolerability range; the LLOQ is allowed 80% to 120% tolerability. The red cells denote excluded data points. The rat model is the most pertinent at Kalypsys, which is why it is displayed here. The results confirm that the automated method of preparing rat plasma samples is consistent in producing tight standard curves with minimal point exclusion due to intolerability. Replicates need to be consistent and inter trial tolerability CV for a given concentration should no exceed 15%
-
Upload
mrjpwalsh8941 -
Category
Documents
-
view
44 -
download
0
description
Charles Taylor's presented poster at the CPSA 2007 conference detailing a dynamic, automated bioanalytical sample preparation routine and the validation of the approach.
Transcript of 2007 CPSA - Poster - Automated Bioanalytical Sample Preparation
Abstract
Objectives
Results
Conclusion
Acknowledgements
An Automated Dynamic BioAnalytical Sample Preparation Routine for Integration with Liquid Handlers
Charles E. Taylor1, Qiner Yang2, John P. Walsh1 and Robyn A. Rourick1
Kalypsys, Inc. Pharmaceutical Sciences Department1 and Informatics2 10420 Wateridge Circle, San Diego, CA 92121
The Analytical Chemistry department at Kalypsys has developed and implemented an automated sample preparation method for its routine BioAnalytical work. The purpose of this system was to assume the work effort of protein precipitation sample preparation, reducing the FTE time required per study. Designed to process sample plates with any combination of matrices and layouts into methodical injection plates, the system is able to achieve much of the sample arrangement that a human analyst would provide. The system depends on proper plate map registration; a tool was developed to allow users to populate the database with a platemap containing animal number, compound number, dose type, matrix, model, time point and concentration for each well of a plate. A server based program crafts a liquid handler script that constructs the corresponding injection plate(s) from the sample plate(s), once the desired calibration curve is chosen on the web based user interface. The resulting script is a standalone file, not a work list, which is recognized and executed by Tecan’s Gemini software. The script generator optimizes the liquid handling by mimicking the logic a human analyst would use in injection plate construction. One representation is the ordering of samples into the densest arrangement. This allows, in some cases, multiple sample plates to be condensed into one injection plate. Another is the detection of multiple compounds in the plate, which triggers the generator to program the construction of corresponding calibration curves and CS0 samples. With the capabilities in place, the ruggedness testing and performance trials were initiated. The system met specification for standard curve construction and consistency of internal standard concentrations in multiple matrices. Tractability of preparation error is achieved by monitoring the liquid handling error log files, and making database tags of any samples that initiated a liquid handling error. Expansion efforts are targeted for the system and include: automated SPE, hemolysis tracking, liquid-liquid extraction, matrix expansion and high density plate use. These efforts look to capture a larger portion of the workflow and position this system as a multipurpose BioAnalytical platform.
Stock Solution
• 200ug/mL of Analyte in 50:50 acetonitrile:water
• Vortexed and sonicated
Internal Standard (IS)
• 500ng/mL deuterated Analyte (Analyte-D6) in acetonitrile
• Vortexed and sonicated
CS0 Controls
• 25uL of blank plasma was combined with 100uL of IS and placed in the same precipitation plate as the standard concentration samples.
Double Blank Controls
• 25uL of blank plasma was combined with 100uL of acetonitrile
• Placed in the same precipitation plate as the standard concentration samples.
Plasma Standard Curve Generation
• Serial dilution of a concentrated, spiked solution was performed in blank plasma
• Each level was thoroughly mixed via aspiration/dispensation repetitions
Plasma Preparation
• 25µL of each spiked standard concentration was transferred to a deep well plate.
• 100µL aliquot of the internal standard was added to each of the wells in the plate to track the extraction, analysis and to act as a precipitating agent.
Precipitation Plate Preparation
• CS0 Controls and the Double Blank Controls added to the plate
• Mixed thoroughly on a multitube vortexer.
• Centrifuged at 35000rpm for 20min and
Injection Plate Preparation
• 50µL of each supernatant from precipitation plate transferred to a deep-well microtitre plate.
• 50µL Milli-Q water was added
• 15µL injected according to the listed analysis method.
• Automated construction of standard curves by the liquid handler for different animal model plasmas was successful.
• Standard curves had greater than 6 points with weighted regression values exceeding 99%
• Data points within these curves passed tolerability for inclusion using the 85% to 115% rule
• The lower limits of quantification (LLOQ) for these automated prep samples were very linear, proving the ability for the method to carry out a precise serial dilution in viscous medium
• Server based liquid handler file generator is able to create production capable files
• This ability for an automated platform to produce injection ready samples from raw materials positions this method as a front running technology that is ready to be utilized in the Kalypsys BioAnalytical workflow.
The authors would like to thank the following individuals for their input and contributions: Nahid Yazdani, Michael Herman and Tiffany Chea.
Document Reference Subject
AC-MethDev-2007-015v1 BioA Tecan Sample Prep
Poster Contact Email
Charles Taylor [email protected]
Product Reference Manufacturer
Freedom EVO 100 Tecan AG
Costar Deep Well Plate Corning
Costar Shallow V-Well Plate Corning
100807_Trial15_Manual_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000243 x + 0.00118 (r = 0.9910)
2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
0.5
1.0
1.5
2.0
Ana
lyte
Are
a/I
SA
rea
C57 Male Mouse Plasma
Figure 1a: Expanded view of Mouse Plasma LLOQ Figure 2a: Expanded view of Mouse Plasma LLOQ
Manual Preparation Automated Preparation
Male Rabbit Plasma
Figure 5a: Expanded view of Rabbit Plasma LLOQ Figure 6a: Expanded view of Rabbit Plasma LLOQ
Manual Preparation Automated Preparation
100807_Trial15_Manual_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000243 x + 0.00118 (r = 0.9910)
2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
0.5
1.0
1.5
2.0
Ana
lyte
Are
a/I
SA
rea
Male Cynomolgus Monkey Plasma
Figure 9a: Expanded view of Cyno Monkey Plasma LLOQ Figure 10a: Expanded view of Cyno Monkey Plasma LLOQ
Manual Preparation Automated Preparation
100807_Trial15_Manual_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000243 x + 0.00118 (r = 0.9910)
2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
0.5
1.0
1.5
2.0
Ana
lyte
Are
a/I
SA
rea
Sprague-Dawley Male Rat Plasma
Figure 3a: Expanded view of Rat Plasma LLOQ Figure 4a: Expanded view of Rat Plasma LLOQ
Manual Preparation Automated Preparation
100807_Trial15_Manual_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000243 x + 0.00118 (r = 0.9910)
2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
0.5
1.0
1.5
2.0
Ana
lyte
Are
a/I
SA
rea
Male Beagle Plasma
Figure 7: Automated Liquid Handler Generated Calibration Curve for Beagle Plasma
Figure 7a: Expanded view of Beagle Plasma LLOQ Figure 8a: Expanded view of Mouse Plasma LLOQ
Manual Preparation Automated Preparation
100807_Trial15_Manual_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000243 x + 0.00118 (r = 0.9910)
2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
0.5
1.0
1.5
2.0
Ana
lyte
Are
a/I
SA
rea
Human Plasma
Figure 11a: Expanded view of Human Plasma LLOQ Figure 12a: Expanded view of Human Plasma LLOQ
Manual Preparation Automated Preparation
Source Type Turbospray Ionization ESI+ (positive)
Source Temperature 500
Spray Voltage 5.5 kV Collision Gas (CAD) Medium
Curtain Gas 10 Ion Gas 1 50
Ion Gas 2 60 Entrance Potential 22
Scan Type Multiple Reaction Monitoring (MRM)
MS Parameters
Equipment List Analytical Balance Mettler Toledo AX26
Liquid Handler Tecan Freedom EVO 100
Tip Configuration 8 Disposable Tip Mounts (DiTi)
Tip Sizes Used 200 µL DiTi Tips 1000 µL DiTi Tips
HPLC System Pump Agilent HP1100
Binary Pump
Degasser Agilent HP1100 Autosampler CTC PAL
HPLC Conditions
Flow Rate 1000µL/min
Mobile Phase A: 0.1% Formic Acid in Water
B: 0.1% Formic Acid in Acetonitrile
Gradient 0.0 – 1.0 min: 10%B to 95%B
1.0 – 1.9 min: 95%B
2.0 – 2.7 min: 10%B
Injection Volume 5 µL
Column Phenomenex Polar-RP 2.0x30mm, 4µm
Plasma
Conc.
Vol of Prev Vol of Blank
Total Vol
Remaining Vol
(ng/mL) (uL) (uL) (uL) (uL)
10000 35 of stock 665 700 250
7500 450 150 600 240
5000 360 180 540 290
2500 250 250 500 250
1000 250 375 625 375
500 250 250 500 250
250 250 250 500 250
100 250 375 625 375
50 250 250 500 250
20 250 375 625 375
10 250 250 500 250
4 250 375 625 625
Table 2: Equipment used in the preparation and analysis.
Table 4: Mass spectrometer parameters used in the MS/MS detection of the analyte and inter-nal standard. Table 3: HPLC parameters used in the analysis of the compounds.
Table 1: Serial dilution used in the construction of the standard curves in each plasma type.
Figure 3: Automated Liquid Handler Generated Calibration Curve for Rat Plasma
Figure 14: The analyte peaks were consistent in retention time, with the higher concentrations maintaining good peak shape (14a). The IS trends for the studies are shown in Figure 14b, with the colors corresponding to the replicate as shown in the calibration graph section. The attenuation in intensity (Figure 14b) is due to the presence of two IS batches. The crosses in Figure 14b correspond to manually prepared trials; the circles represent automated trials.
Figure 9: Automated Liquid Handler Generated Calibration Curve for Cyno Monkey Plasma
0 20 40 60 80 100 120 140 160 180 200 220 240 260Analyte Conc. / IS Conc.
0.00
0.05
0.10
0.15
0.20
Ana
lyte
Are
a/I
SA
rea
100807_Trial7_Manual_Mouse.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000244 x + 0.00143 (r = 0.9957)��101407_Trial24_Manual_Mouse.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000501 x + 0.004 (r = 0.9989)��101407_Trial30_Manual_Mouse.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000511 x + 0.0162 (r = 0.9986)��
0.0 2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
1.0
2.0
3.0
4.0
5.0
Ana
lyte
Are
a/I
SA
rea
Curve R2 Slope
1st .9957 .000244
2nd .9989 .000501
3rd .9986 .000511
Figure 1: Automated Liquid Handler Generated Calibration Curve for Mouse Plasma
0 20 40 60 80 100 120 140 160 180 200 220 240 260Analyte Conc. / IS Conc.
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
Ana
lyte
Are
a/I
SA
rea
100507_Trial3_Manual_Rat.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000471 x + 0.00225 (r = 0.9958)��101407_Trial25_Manual_Rat.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000498 x + 0.00391 (r = 0.9969)��101407_Trial31_Manual_Rat.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000511 x + 0.0126 (r = 0.9990)��
0.0 2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
1.0
2.0
3.0
4.0
5.0
Ana
lyte
Are
a/I
SA
rea
Curve R2 Slope
1st .9958 .000471
2nd .9969 .000498
3rd .9990 .000511
0 20 40 60 80 100 120 140 160 180 200 220 240 260Analyte Conc. / IS Conc.
0.00
0.05
0.10
0.15
0.20
0.25
Ana
lyte
Are
a/I
SA
rea
100807_Trial9_Manual_Rabbit.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000247 x + 0.0011 (r = 0.9978)��101407_Trial26_Manual_Rabbit.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.0005 x + 0.00472 (r = 0.9987)��101407_Trial32_Manual_Rabbit.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.00046 x + 0.0133 (r = 0.9992)��
0.0 2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
1.0
2.0
3.0
4.0
5.0
Ana
lyte
Are
a/I
SA
rea
Curve R2 Slope
1st .9978 .000247
2nd .9987 .0005
3rd .9992 .00046
Figure 5: Automated Liquid Handler Generated Calibration Curve for Rabbit Plasma
0 20 40 60 80 100 120 140 160 180 200 220 240 260Analyte Conc. / IS Conc.
0.000
0.020
0.040
0.060
0.080
Ana
lyte
Are
a/I
SA
rea
101207_Trial11b_Manual_Beagle.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.00034 x + 0.00237 (r = 0.9977)��101407_Trial27_Manual_Beagle.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000504 x + 0.00544 (r = 0.9962)��101407_Trial33_Manual_Beagle.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000522 x + 0.00987 (r = 0.9951)��
0.0 2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
1.0
2.0
3.0
4.0
5.0
Ana
lyte
Are
a/I
SA
rea
Curve R2 Slope
1st .9977 .00034
2nd .9962 .000504
3rd .9951 .000522
0 20 40 60 80 100 120 140 160 180 200 220 240 260Analyte Conc. / IS Conc.
0.00
0.05
0.10
0.15
0.20
0.25
Ana
lyte
Are
a/I
SA
rea
101407_Trial34_Manual_Cyno.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.00103 x + 0.0122 (r = 0.9974)��100807_Trial13_Manual_Cyno.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000231 x + 0.00366 (r = 0.9952)��101407_Trial28_Manual_Cyno.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000556 x + 0.00374 (r = 0.9973)��
2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
2.0
4.0
6.0
8.0
Ana
lyte
Are
a/I
SA
rea
Curve R2 Slope
1st .9974 .0122
2nd .9952 .00366
3rd .9973 .00374
0 20 40 60 80 100 120 140 160 180 200 220 240 260Analyte Conc. / IS Conc.
0.00
0.05
0.10
0.15
0.20
0.25
Ana
lyte
Are
a/I
SA
rea
101407_Trial35_Manual_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000544 x + 0.00965 (r = 0.9964)��100807_Trial15_Manual_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000233 x + 0.00187 (r = 0.9953)��101407_Trial29_Manual_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000465 x + 0.00446 (r = 0.9983)��
2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
1.0
2.0
3.0
4.0
5.0
Ana
lyte
Are
a/I
SA
rea
Curve R2 Slope
1st .9964 .000544
2nd .9953 .000233
3rd .9983 .000465
Figure 11: Automated Liquid Handler Generated Calibration Curve for Human Plasma
0 20 40 60 80 100 120 140 160 180 200 220 240 260Analyte Conc. / IS Conc.
-0.04
-0.02
0.00
0.02
0.04
0.06
0.08
Ana
lyte
Are
a/I
SA
rea
100807_Trial17_FullAuto_Mouse.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000299 x + 0.00112 (r = 0.9977)��101507_Trial36_FullAuto_Mouse.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000295 x + 0.00198 (r = 0.9975)��101507_Trial42_FullAuto_Mouse.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000276 x + 0.00187 (r = 0.9971)��
0.0 2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
3.9
Ana
lyte
Are
a/I
SA
rea
Curve R2 Slope
1st 0.9977 .000299
2nd 0.9975 .000295
3rd 0.9971 .000276
0 20 40 60 80 100 120 140 160 180 200 220 240 260Analyte Conc. / IS Conc.
-0.04
-0.02
0.00
0.02
0.04
0.06
0.08
Ana
lyte
Are
a/I
SA
rea
101207_Trial22_FullAuto_Rat.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000232 x + 0.00116 (r = 0.9983)��101507_Trial37_FullAuto_Rat.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000307 x + 0.00293 (r = 0.9980)��101507_Trial43_FullAuto_Rat.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000284 x + 0.00217 (r = 0.9965)��
0.0 2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Ana
lyte
Are
a/I
SA
rea
Curve R2 Slope
1st .9983 .000232
2nd .9980 .000307
3rd .9965 .000284
Figure 4: Automated Liquid Handler Generated Calibration Curve for Rat Plasma
0 20 40 60 80 100 120 140 160 180 200 220 240 260Analyte Conc. / IS Conc.
-0.040
-0.020
0.000
0.020
0.040
0.0600.070
Ana
lyte
Are
a/I
SA
rea
100807_Trial18_FullAuto_Rabbit.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000285 x + 0.00107 (r = 0.9971)��101507_Trial38_FullAuto_Rabbit.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000304 x + 0.000751 (r = 0.9969)��101507_Trial44_FullAuto_Rabbit.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000264 x + 0.00164 (r = 0.9994)��
0.0 2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Ana
lyte
Are
a/I
SA
rea
Curve R2 Slope
1st .9971 .000285
2nd .9969 .000304
3rd .9994 .000264
Figure 6: Automated Liquid Handler Generated Calibration Curve for Rabbit Plasma
0 20 40 60 80 100 120 140 160 180 200 220 240 260Analyte Conc. / IS Conc.
-0.040
-0.020
0.000
0.020
0.040
0.060
0.076
Ana
lyte
Are
a/I
SA
rea
100807_Trial19_FullAuto_Beagle.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000276 x + 0.00138 (r = 0.9995)��101507_Trial39_FullAuto_Beagle.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000277 x + 0.000817 (r = 0.9949)��101507_Trial45_FullAuto_Beagle.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000281 x + 0.00205 (r = 0.9972)��
0.0 2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Ana
lyte
Are
a/I
SA
rea
Curve R2 Slope
1st .9995 .000276
2nd .9949 .000277
3rd .9972 .000281
Figure 8: Automated Liquid Handler Generated Calibration Curve for Mouse Plasma
0 20 40 60 80 100 120 140 160 180 200 220 240 260Analyte Conc. / IS Conc.
-0.04
-0.02
0.00
0.02
0.04
0.06
0.080.09
Ana
lyte
Are
a/I
SA
rea
101407_Trial23_FullAuto_Cyno.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000363 x + 0.000573 (r = 0.9983)��101507_Trial40_FullAuto_Cyno.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000298 x + 0.00228 (r = 0.9982)��101507_Trial46_FullAuto_Cyno.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000287 x + 0.000583 (r = 0.9980)��
0.0 2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
1.0
2.0
3.0
4.0
Ana
lyte
Are
a/I
SA
rea
Curve R2 Slope
1st .9983 .000363
2nd .9982 .000298
3rd .9980 .000287
Figure 10: Automated Liquid Handler Generated Calibration Curve for Cyno Monkey Plasma
Figure 2: Automated Liquid Handler Generated Calibration Curve for Mouse Plasma
0 20 40 60 80 100 120 140 160 180 200 220 240 260Analyte Conc. / IS Conc.
0.000
0.020
0.040
0.060
0.080
0.100
0.120
Ana
lyte
Are
a/I
SA
rea
100807_Trial21_FullAuto_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000292 x + 0.00119 (r = 0.9979)��101507_Trial41_FullAuto_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.00031 x + 0.000469 (r = 0.9997)��101507_Trial47_FullAuto_Human.rdb (K932961): "Linear" Regression ("1 / (x * x)" weighting): y = 0.000276 x + 0.00183 (r = 0.9994)��
0.0 2000.0 4000.0 6000.0 8000.0 1.0e4Analyte Conc. / IS Conc.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Ana
lyte
Are
a/I
SA
rea
Curve R2 Slope
1st .9979 .000292
2nd .9997 .000310
3rd .9994 .000276
Figure 12: Automated Liquid Handler Generated Calibration Curve for Human Plasma
Experimental
Figure 14a Figure 14b
0500
10001500200025003000350040004500500055006000650070007500800085009000950010000
1.002
1.018
1.035
1.052
1.068
1.085
1.102
1.118
1.135
1.152
1.168
1.185
1.202
1.218
1.235
1.252
1.268
1.285
1.302
1.318
1.335
1.352
1.368
1.385
1.402
1.418
1.435
1.452
1.468
1.485
1.502
Peak
Are
a
Time (min.)Studies
• Plasma samples for this study are to be prepared by protein precipitation and monitored with an internal standard
• Quantification is to be performed through the generation of a standard curve
• Liquid handler is to use file generated from the server based script generator
• Curves are to exceed R2 values of 0.99
• Tolerability of data points included in the curve are to be between 85% and 115%
• Minimum of 6 points in a calibration curve
• LLOQ for every curve is not to exceed CS20 after data exclusion
Manually Prepared Liquid Handler Prepared
Data Compilation Decision Point
Legend
Rat Automatic
Conc. R1 R2 R3 AVG CV CV AVG R1 R2 R3 Conc. 4 93.1% 102% 97.8% 97.63% 4.56% 100.92% 231.83% 97.9% 502% 95.6% 4
10 115% 86.9% 104% 101.97% 13.89% 6.96% 105.17% 104% 98.5% 113% 10 20 120% 112% 100% 110.67% 9.1% 7.94% 99.77% 101% 107% 91.3% 2050 110% 103% 108% 107% 3.37% 10.65% 101.03% 104% 89.1% 110% 50
100 125% 97.4% 103% 108.47% 13.45% 2.82% 100.47% 101% 97.4% 103% 100 250 101% 113% 101% 105% 6.6% 3.91% 103.33% 101% 108% 101% 250 500 107% 103% 98.6% 102.87% 4.08% 2.5% 98.4% 101% 98.1% 96.1% 500
1000 103% 96.6% 97% 98.87% 3.63% 2.16% 95.8% 95.2% 98.1% 94.1% 1000 2500 97.1% 96.3% 105% 99.47% 4.83% 5.12% 98.5% 94.1% 104% 97.4% 2500 5000 91.2% 97.1% 95.3% 94.53% 3.2% 6.14% 96.3% 91.8% 103% 94.1% 5000 7500 92% 95.7% 94.6% 94.1% 2.02% 2.19% 95.2% 96.3% 96.5% 92.8% 7500
10000 90.2% 95.7% 96.2% 94.03% 3.54% 4.52% 115% 112% 121% 112% 10000
Rat Manual
Table 5: The back-calculated concentrations of the standard curve plasma samples were made by entering the analyte peak area into the calibration curve, which those samples were used to construct. The tolerability of the standard curve point to be included in the curve is measured by it’s statistical difference from the theoretical concentration. Exclusion from the standard curve occurs when the point is outside of the 85% to 115% tolerability range; the LLOQ is allowed 80% to 120% tolerability. The red cells denote excluded data points. The rat model is the most pertinent at Kalypsys, which is why it is displayed here. The results confirm that the automated method of preparing rat plasma samples is consistent in producing tight standard curves with minimal point exclusion due to intolerability.
• Replicates need to be consistent and inter trial tolerability CV for a given concentration should no exceed 15%
