Assay Design Using Process Optimization Ideology: A Case For Coupling Assay Development And Liquid Handler Qualification

Size: px

Start display at page:

Download "Assay Design Using Process Optimization Ideology: A Case For Coupling Assay Development And Liquid Handler Qualification"

Arron Griffith
6 years ago
Views:

1 Assay Design Using Process Optimization Ideology: A Case For Coupling Assay Development And Liquid Handler Qualification Sponsored by Artel, presented by Nathaniel Hentz, Ph.D. and Rebecca Kitchener, Ph.D. 1

2 Outline Assay development: current practices Liquid handler optimization: current practices Process optimization What? Why? How? Example: model assay & findings Conclusions 2

3 OVERVIEW: ASSAY DEVELOPMENT 3

4 Foundations Of Assay Development Train Sample Matrix Risk Assessment Select Method Set Specifications Identify Process Steps Characterize Define Assay Purpose Document Assay Components Validate 4

5 High Throughput Screening Assay Validation Plate Uniformity Signal Variability Assay Reagent Stability DMSO Compatibility Reaction Stability 5

6 So, What Does A Good Assay Look Like? Let s define a couple of parameters: First, let s consider the assay variability Second, let s consider the assay window Z 1 3 max max 3 min min Z-Factor Value Assay Quality 1 Ideal assay 1 > Z 0.5 Excellent assay 0.5 > Z > 0 Marginal assay 0 Yes/no assay <0 Assay not useful 6

7 The Result S ig n a l (R F U ) Z = 0.74 S ig n a l (R F U ) Z = W e ll ID W e ll ID

8 OVERVIEW: LIQUID HANDLER OPTIMIZATION 8

9 Liquid Dispense Technologies Dispense Principle Air displacement Positive displacement Droplet (acoustic) Droplet (solenoid/inkjet) Capillary (pintool) Peristaltic Attributes Problematic for volatile liquids Possible cross contamination Wide range of volumes Useful for volatile solvents Cross contamination possible Wide range of volumes Non-contact Useful for small volumes (pl nl) Useful for small volumes (nl) Sensitive to fluid types Useful for small volumes Direct contact with sample (contamination) Sensitive to fluid type Useful for bulk dispense; More frequent calibrations needed 9

Parameters that Effect Volume Transfer Hardware/labware plate format, tip types, tubing type ALH settings target (or off-set) volume, single/multi dispense, aspirate/dispense rate, aspirate/dispense

10 Parameters that Effect Volume Transfer Hardware/labware plate format, tip types, tubing type ALH settings target (or off-set) volume, single/multi dispense, aspirate/dispense rate, aspirate/dispense height, liquid class, pre and post air gaps, accuracy/precision of volume transfer, transfer speed/time delays, on-board mixing Assay reagent mixing, incubation, centrifugation, number of liquid transfers, wash steps, dilution steps, serial dilutions Sample viscosity, density, surface tension, temperature, volatility Environment temperature, humidity, light, vibration 10

11 Typical Liquid Handler Optimization: Usually performed as a stand-alone activity Precision is always checked, but accuracy is not as easy Several methods for volume verification In-house (e.g., fluorescence, gravimetric, absorbance, etc.) Commercial (e.g., dual-dye spectrophotometry) Volume verification is typically performed with ideal solutions Liquid handler is certified, calibrated, or repaired (if necessary) Then.someone programs ALH for assay use Default method Specific to basic assay requirements 11

12 ADOPTING A PROCESS OPTIMIZATION APPROACH 12

13 Sources Of Assay Variability What can we control or optimize? Biology Diffusion Binding equilibrium Steric hindrance Cell population diversity Protein activity Environment Temperature Light Humidity People Instrumentation Liquid handlers Detectors Mixers Incubators Centrifuges Consumables Reagents Tips Plate type Plate seals 13

14 What Do We Mean By Process Optimization? Two levels of HTS assay optimization: Level 1 performed by development scientist basis: biology (mostly) Level 2 performed by (or with) the automation scientist basis: meeting predefined assay specifications Process Optimization minimizes assay variability through the study of the entire process rather than individual components. Goal is to optimize the LH system based on assay design specifications, coupled with the assay itself. 14

15 LH OVERALL PROCESS OPTIMIZATION How Is Process Optimization Accomplished? Step 1 break down proposed assay into operational units Step 2 convert assay into MVS readable format; Replace proposed assay components with Artel MVS reagents Step 3 read MVS plates to determine performance of liquid handler, order of addition, incubation and mixing efficiencies Step 4 insert assay reagents back into process based on new information N. Hentz and E. Avis, SLAS2017, Improving Assay Performance Using a Process Optimization Approach 15

16 The Value of Process Optimization Minimize overall assay variability Maximize data quality and reproducibility Improve efficiency by reducing assay transfer problems Process can be optimized to its fullest extent before the assay is transferred e.g. mixing, incubation time, liquid handler and order of reagent addition Only requirement is knowledge of basic assay configuration (e.g., volumes, incubation times, incubation temperatures, etc.) Optimizing the process as a whole (assay and ALH together) allows for better control to be gained over the process, thus reducing variability and minimizing assay transfer time. 16

17 CASE STUDY 17

18 Assessing Effects Of Liquid Handling On The Assay Phase I: Using a well-characterized model assay, develop and optimize the assay platform at bench scale. Phase II: Perform method transfer to ALH: examine effects of automated liquid handling parameters on the same assay. Phase III: Deconstruct the assay: decide which parameters, when altered, significantly vary assay outcome. 18

Streptavidin: Biotin-Fl Assay Principle Streptavidin (SA) is a tetravalent biotin-binding protein that is isolated from Streptomyces avidinii and has a mass of 60.0 kda.

19 Streptavidin: Biotin-Fl Assay Principle Streptavidin (SA) is a tetravalent biotin-binding protein that is isolated from Streptomyces avidinii and has a mass of 60.0 kda. SA has a very high affinity for biotin (K d = to -15 M). Fl Fl Fl Fl SA SA Biotin-Fluorescein (B-Fl) Quenched fluorescence Enhanced fluorescence 1. Waner, MJ; Mascotti DP. Journal of Biochemical and Biophysical Methods 70(6), 2008, A simple spectrophotometric streptavidin biotin binding assay utilizing biotin-4-fluorescein. 2. Ebner, A; Marek, M; Kaiser, K; Kada, G; Hahn, CD; Lackner, B; Gruber, HJ. Methods in Molecular Biology, 418, 2008, Application of biotin-4-fuorescein in homogeneous fluorescence assays for avidin, streptavidin, and biotin or biotin derivatives. 19

20 Streptavidin Assay Details Assay Components Phosphate buffered saline, ph 7.4, containing 0.1% BSA Black, non-binding 96-well plates Streptavidin (SA) Biotin-fluorescein (labeled ligand) Inhibitors, various concentrations Experimental Conditions Add 25 µl of Biotin-FL Add 25 µl of inhibitor Add 25 µl of SA Incubate for 30 min at room temperature Read fluorescence: Ex = 485 nm and Em = 515 nm Compare inhibitor potency (IC 50 ) 20

21 Assay Development Parameters Evaluated 21

22 Sources Of Error: Assay Buffer Fluorescence Signal (RFU) PBS + BSA PBS PBS + Glycerol Manual Fluorescence Signal (RFU) PBS + BSA PBS PBS + Glycerol ALH Log Inhibitor Concentration (nm) Log Inhibitor Concentration (nm) Effect of buffer on assay outcome (potency) varies between the two liquid handling methods. 22

23 Sources Of Error: Mixing Fluorescence Signal (RFU) No Mixing Mix 3X Manual pipette Fluorescence Signal (RFU) No Mixing Mix 3X ALH Log Inhibitor Concentration (nm) Log Inhibitor Concentration (nm) For this assay, mixing affects potency, but the discrepancy is more pronounced on the ALH. 23

24 Sources Of Error: Reagent Stability Fluorescence Signal (RFU) < 30 min on ALH 6 h on ALH Log Inhibitor Concentration (nm) Reagent stability must be determined on the ALH as well as during bench scale assay development. 24

25 Sources of Error: Assay Plate Type 600 Potency (IC 50, nm) % 0 Uncoated Coated (non-binding surface) Consumables are often considered interchangeable not so! 25

26 Sources of Error: ALH Parameters 2500 ALH Dispense Rate Fluorescence Signal (RFU) Dispense Rate: 1 Dispense Rate: 3 Dispense Rate: Log Inhibitor Concentration (nm) For this assay: Aspiration rate: no effect Air gaps: no effect Dispense rate: critical 26

27 Study Conclusions Four assay parameters were identified which required optimization both during development at bench-scale and on the ALH. Assay buffer selection Mixing Reagent stability Plate type One LH parameter was determined to be critical to assay outcome: dispense rate. 27

28 Overall Conclusions Performing assay optimization AND liquid handler optimization together as a whole process reduces potential for error introduction and prolonged/difficult method transfer. Evaluate critical liquid handling parameters and potential sources of variability at bench scale and on the ALH for each new assay. Assay optimization or LH qualification alone isn t enough. 28

29 Putting It Together Assays depend on reagent concentrations Assay results are impacted by liquid handling variability Reagent concentrations are volumedependent THEREFORE: Assay integrity is dependent on accurate volume delivery 29

30 THANK YOU FOR YOUR ATTENTION! 30

Effect of Liquid Handling QC on Biological Assay Performance. 06 Feb 2012 Artel Tutorial Nathaniel Hentz, PhD

Effect of Liquid Handling QC on Biological Assay Performance 06 Feb 2012 Artel Tutorial Nathaniel Hentz, PhD Outline Review accuracy vs. precision Review common liquid handler QC methods Artel MVS technology