SLAS

How to Deal With High Assay Variability

From LabAutopedia

Content transcluded from a collaborative wiki site

How to Deal With High Assay Variability
From The NIH Chemical Genomics Center Assay Guidance Manual




High Variation in Single Concentration Determinations

The table below can be used as a reference to determine the number of replicates necessary for assays with high variability. For a given CV of the raw data values based on 1 well, it shows the number of replicates needed for the CV of a mean to be less than or equal to 10 or 20%. This table does not indicate how the IC50/Ki/Kb variability will be affected (See Section E.2 for high variation in IC50/Ki/Kb responses).

CV using 1 well Number of Wells so that CV < 10% Number of Wells so that CV < 20%
< 10 1 1
10.00 to 14.1 2 1
14.2 to 17.3 3 1
17.4 to 20.0 4 1
20.1 to 22.3 5 2
22.4 to 24.4 6 2
24.5 to 26.4 7 2
26.5 to 28.2 8 2
28.3 to 30.00 9 3
30.1 to 31.6 10 3
31.7 to 33.1 11 3
33.2 to 34.6 12 3
34.7 to 36.0 13 4
36.1 to 37.4 14 4
37.4 to 38.7 15 4
38.8 to 40.00 16 4

Adding replicates to reduce variability will also reduce the capacity (i.e., throughput) of the assay to test compounds. Further optimization of the assay could reduce variability and maintain or increase its capacity. The decision to further optimize or add replicates will have to be made for each assay.

Excess Variation in Concentration-Response Outcomes (EC50, IC50, Ki, or Kb)

If in Section D the assay fails either test (MSR > 3 or Limits of Agreement outside the interval 1/3-3) then the variability of the assay is too high. The following options should be considered to reduce the assay variability:

  1. Optimizing the assay to lower variability in the signal (see Section V) of the raw data values Check that the dose range is appropriate for the compound results. Adding doses and/or replicates may improve the results. A minimum of 8 doses at half-log intervals is recommended. In general, it is better to have more doses (up to 12) rather than more replicates.
  2. Consider adding replicates as discussed below. Note that the impact of adding replication may be minimal, and so the Replicate Experiment Study should be used to assess whether increasing the number of replicates will achieve the objective.
  3. Adopt as part of the standard protocol to re-run results. For example, each compound may be tested once per run on 2 or more runs. Then averaging the results will reduce the assay variability (NB. In such cases the individual run results are stored in the database and then the data mining/query tools are used to average the results).

To investigate the impact of adding replicate wells in the concentration-response assay you should conduct the Replicate-Experiment study with the maximum number of wells contemplated (typically 3-4 wells / concentration). To examine the impact of replication compute the MSR versus number-of-replicates curve. To construct this curve, make all data calculations using just the first replicate of each concentration to evaluate the MSR and Limits of Agreement for 1 well per concentration. Then repeat all calculations using the first two replicates per concentration, and so on until you are using all replicates. If the assay does not meet the acceptance criterion when all replicates are used then replication will not sufficiently impact the assay to warrant the replication. If it does meet the criterion using all replicates ascertain how many replicates are needed by noting the smallest number of replicates that are required to meet the Replicate-Experiment acceptance criterion. Two examples below will help illustrate the steps.

A binding assay was run using 1 well per concentration and the Replicate-Experiment study did not meet the acceptance criterion. To examine if replication would help a new Replicate-Experiment study was conducted using 4 wells per concentration. Using just the first replicate from each concentration, the results were normalized, curves fit and Ki’s were calculated for each concentration-response curve. The MSR and LsA were evaluated. The entire calculation steps were repeated using the first 2 replicates, first 3 replicates and all 4 replicates, with the following results:

Reps

MSR

LsA

2

3.62

0.35-4.59

3

3.32

0.43-4.74

4

2.44

0.53-3.16


From the table we can see that it takes all 4 replicates to meet the MSR acceptance criterion, and no amount of replication (up to 4 replicates) will meet LsA acceptance criterion.

In a second study, a pair of uptake inhibition assays (the project had two targets, each measured by one assay) the Plate Uniformity Study indicated two replicates would be required to meet the Plate Uniformity Signal acceptance criteria in Assay 2. However, plate uniformity criteria concerning replication do not readily translate to dose-response requirements, and so the requirements were investigated in both assays. The Replicate-Experiment Study was conducted using two replicates. The calculations were performed using both replicates, and the re-calculated using just the first replicate. The MSR and LsA are summarized in the following table:

Replicates Used

Assay 1

Assay 2

MSR

LsA

MSR

LsA

Rep 1 Only

2.27

0.44-2.27

3.30

0.28-3.08

Both Reps

1.71

0.57-1.67

2.15

0.44-2.03

Using two replicates both assays meet all acceptance criterion. Using just a single replicate Assay 1 still meets all criteria, while assay 2 does not. Note that in this instance both assays benefited from increased replication. However, assay 1 is a very tight assay and hence this benefit is not really needed in that case. So in this case the replication requirements were the same for both single dose screening and dose-response studies, but in general this will not be the case.

Click [+] for other articles on 
[+] High Throughput Screening (13)
 The Market Place for Lab Automation & Screening  Drug Discovery HTS Products
Retrieved from "http://www.labautopedia.com/mw/index.php/How_to_Deal_With_High_Assay_Variability"