Assaying refers to the practice of breaking down problems into their component parts in order to find solutions, often in fields such as mining, pharmacology or biological science.

Assays can either be quantitative (involving chemical titration) or qualitative. Quantitative assays can be divided into three categories shown below. These assays can also be FLIPR and HERG assay.


Although assay and quantitative are often used interchangeably, they represent two different processes. Assay refers to an umbrella of testing techniques; on the other hand, quantitative analysis produces precise numerical results.

Quantitative assays are commonly employed to measure the concentration, amount or activity of substances. These assays use various reagents, instruments and protocols to identify presence/absence and often utilize calibration curves to ensure accuracy of results. Quantitative endpoint assays also exist and often measure reactions’ final end points.

There are various quantitative assays, such as spectrophotometry, calorimetry and chemiluminescence, to measure reactions. These assays use light or heat to monitor reactions as they progress – often continuous enzyme assays offer more accurate readout than discontinuous ones.

Information derived from assays can be immensely useful and are utilized across industries. Mining assays help determine mineral quality while medical assays assist in developing new drug treatments and vaccines. Furthermore, assay results have significant financial market implications: for instance a mining company reporting positive assay results could see their stock prices surge, while negative results could send prices plummeting significantly.


Qualitative data refers to any non-numerical information; words, descriptions and concepts – collected through interviews, open-ended survey responses, document analysis or archiveal work and then often analyzed using coded text or content analysis techniques.

As with quantitative assays, qualitative research can present unique challenges when it comes to validity and reliability. Replicating data from various settings is difficult due to researchers’ primary role of analyzing and interpreting information preventing traditional measures of statistical significance or accuracy from being applied accurately.

Quantitative assays typically only provide “yes/no” results rather than quantifying analyte concentrations present. An example would be pregnancy testing which measures for human chorionic gonadotrophin (hCG) presence but cannot provide exact data as to its amount present in urine samples.

For any qualitative test to be accurate, it must first undergo calibration – this involves subjecting it to testing against known samples with known concentrations or levels and then comparing this test against an international standard such as CDC COVID-19 serological assay. In addition, regular storage, interfering substance studies as well as sensitivity and specificity studies should also be conducted, in order to verify manufacturer claims regarding Sensitivity Specificity Agreement within test kit package inserts.


Bioassay is an investigative or analytical procedure used in lab medicine, mining, pharmacology and environmental biology to qualitatively or quantitatively measure the presence or amount of a particular biological entity such as drugs, microorganisms, chemical elements or compounds present in samples taken from living organisms. Furthermore, biological standardisation forms part of this category.

EIM bioassays typically involve collecting field collected freshwater or sediment samples that are then exposed in a laboratory according to established methods for an extended duration, prior to being measured for their effects on organisms (known as endpoints).

Bioassays will usually depend on the objectives of their respective projects and will typically expose test organisms to specific media identified as potential contaminants.

These tests are typically completed in a laboratory and can be compared with data from the same project area to help identify where contamination may be most likely occurring. It is crucial that these data be evaluated for validity and consistency – any tests whose results fall outside specified protocols should be marked “U” in column AK of EAP Ecology and site investigation data reports as unusable in column AK for better tracking purposes (for more details please see Data Quality section of Template).


Cell-based assays offer an alternative to biochemical methods for screening and analyzing cellular activities like apoptosis, cell migration, growth or cytotoxicity. These assays typically use colorimetric or fluorometric detection and are performed using microplate format; cell-based assays provide greater accuracy and throughput than protein assays.

Cell-based assays boast multiple advantages over biochemical assays; these tests simulate more complex biological systems and can predict drug responses more physiologically. They also provide more data than simple biochemical assays which only report binding or activity of single molecules while often relying on population averages as a basis for analysis.

Cell-based assay kits provide an effective method for studying the effects of compounds on cell function, such as monitoring intracellular phosphorylation events or assessing apoptosis. Furthermore, these assays can also be used to study phenotypic characteristics like cell migration or angiogenesis in vitro.

Cell-based assay development can be challenging. To create reliable yet high-throughput assays, it is crucial that researchers clearly define their endpoints for measurement as well as understand the effects that variables (e.g. cell line, sample dilution and exposure time) will have on data variability. BMG LABTECH offers tools that can help reduce sample variation in cell-based assays such as software-controlled reagent injectors with automatic delivery timing and volume for plates up to 638 wells as well as matrix scan options which further reduce data variability by averaging individual wells within each plate.

The FLIPR & hERG Assay

These assays can also include the FLIPR (Fluorometric Imaging Plate Reader) assay and the hERG (human Ether-à-go-go-Related Gene) assay, both of which play crucial roles in drug discovery and safety assessment.

  1. FLIPR Assay: The FLIPR assay is a high-throughput screening method used in drug discovery to measure changes in intracellular calcium levels. It employs fluorescent calcium-sensitive dyes to monitor the influx or efflux of calcium ions in response to a drug compound’s interaction with specific cellular targets. This assay is particularly valuable for identifying compounds that modulate G protein-coupled receptors (GPCRs), ion channels, and other membrane proteins involved in cell signaling pathways. The FLIPR assay provides real-time, quantitative data on calcium signaling, making it an essential tool for lead compound screening and optimization.
  2. hERG Assay: The hERG assay assesses the potential of a drug candidate to block the hERG potassium ion channel, which plays a crucial role in cardiac repolarization. Inhibition of the hERG channel can lead to QT interval prolongation in the electrocardiogram (ECG), increasing the risk of life-threatening cardiac arrhythmias, such as Torsades de Pointes. Therefore, evaluating a compound’s hERG liability is a critical safety consideration in pharmaceutical research. The hERG assay employs various techniques, including patch-clamp electrophysiology and automated high-throughput assays, to measure the compound’s impact on hERG channel function. Compounds with significant hERG inhibition may undergo further scrutiny or optimization to mitigate potential cardiac safety concerns.

These assays, including the FLIPR and hERG assays, are indispensable tools for pharmaceutical and biotechnology companies in the early stages of drug development. By employing these assays, researchers can quickly identify lead compounds with the desired therapeutic properties while minimizing the risk of adverse effects on cellular functions and cardiac safety. Additionally, the data generated from these assays inform decision-making processes, guiding researchers toward the development of safer and more effective drug candidates.