Reproducibility, also known as replicability and or repeatability, is a scientific method in which results obtained by an experiments should be achieved again when it is being performed multiple times under same experimental conditions irrespective of who is running it and where.
In research, the ELISA is an invaluable method to detect biological samples and is a simple and cost-effective way to analyse a sample. When working with ELISA, poor replicability or reproducibility can compromise gathered data, and make the experiment a time-consuming and laborious process.
The overall precision in immunoassay is defined by examining reproducibility of reported results through examining variation between wells within a single run of a plate (intra-assay precision) or between runs/trials or plate-to-plate (inter-assay precision) by evaluating the %CVs, respectively. Good precision and accuracy results reliability.
Though ELISA in a simple immunoassay, with several high quality kits easily available, all critical assays are prone to errors, especially when human involvement is concerned. The most important challenge is to generate consistent data with no variability within assays, between labs, and within the plate itself.
Effects of Poor Reproducibility on Scientific Research
It was observed in study by Nature magazine that over 70% of researchers cannot reproduce another scientist’s experiments. This irreproducibility leads to loss of great amount of time, money and, efforts, in addition to the negative impact on individual’s publication and career success.
Poor reproducibility also, of course, reduces the integrity of the data in question – if it cannot be reproduced, was it tampered with?
A Few Basic Measures to Improve Reproducibility
-
To get accurate and reproducible data, first and most importantly, follow all the basic lab instructions like sterilizing lab ware, reagents, buffer, pipette including tips etc. to avoid any contamination and arrange them in lab prior to performing test. Cross contamination is one of the leading causes of poor reproducibility.
-
Read the kit insert instructions carefully and follow the assay protocol deliberately. Use reagents in the incorrect order and do-not accidentally omit a step.
-
If possible, use a multichannel pipette to dispense all reagents at the same time without any time lapse between the wells. Similarly, use separate tips for each regent to avoid any cross contamination. If you are using a manual pipette, ensure it has been calibrated recently and pipette reagents with careful, repetitive movements.
-
Do not mix components from different kit lots. All reagents are kit- and lot-specific.
-
Do not make the working solution too far in advanced, and ensure minimal freeze-thaw cycles.
-
Ensure proper washing to remove any contaminants, and to avoid unspecific antigen-antibody interactions.
-
Handle all wells in the same order and time sequences.
-
Do not modify test procedure or sample handling, unless you intend to internally validate the amended protocol.
-
Use a pipetting scheme to verify an appropriate plate layout
-
Pipette in duplicate to be able to identify potential pipetting errors
Meanwhile, Krishgen’s high quality, specific ELISA will ensure that the reagents and antibodies-antigens you use show high affinity to each other. Our seven step validation process including reproducibility studies helps to streamline data.
References:
Getting to the root of poor ELISA data reproducibility. Magali Fischer. Tecon.com
1,500 scientists lift the lid on reproducibility. Nature. 25 May 2016.
Six factors affecting reproducibility in life science research and how to handle them. Nature portfolio.
