Tackling Assay Development Failures in High-Throughput Screening

High-throughput screening (HTS) is a cornerstone of modern drug discovery, enabling the evaluation of thousands to millions of potential drug compounds. Advances in automation and miniaturization have elevated the number of compounds that can be studied to new heights; however, larger compound libraries amplify both discovery potential and experimental error. Even well-designed HTS assays can yield misleading results and lead to costly attrition.

Assay failure in HTS can take several forms, including false positives, poor reproducibility, and loss of biologically meaningful hits. This article will explore why HTS assays fail, how these failures manifest, and strategies researchers can use to improve reliability and confidence.

The anatomy of HTS assay development failures

One of the most common issues HTS assays face is false-positive results, in which a compound appears to have the desired effect against a target when, in fact, it is actually a non-specific artifact.

“A high-throughput screen will typically identify many thousands of ‘hits’ (compounds that appear to give the desired response). Some of these ‘hits’ will be genuine, some will be due to low resolution in the signal or assay interference, and some due to assay interference resulting from compound aggregation, generation of reactive oxygen species, and similar mechanisms,” Dr. Matthew Lloyd, senior lecturer (associate professor) at the University of Bath, told Technology Networks.

Pan-assay interference compounds (PAINS) are molecules that can act as inhibitors or activators by non-specifically interfering with assay components. Publicly available filters can help identify PAINS suspects; however, not all mechanisms of inhibition will be flagged as PAINS. In addition, compounds can be flagged as PAINS even if they do not exhibit high assay promiscuity. For example, multitarget-directed ligands can be inappropriately labelled as PAINS if the incorrect biochemical tests are used. Knowledge of the target’s sensitivity to common interference mechanisms is therefore vital when designing a HTS assay.

Another common issue in HTS assays is incorrect interpretation of assay signals.

HTS assays often measure compound activity by changes in fluorescent signals. “This is because fluorescent assays are sensitive and can be readily adapted to an HTS format,” Lloyd said. Unfortunately, compounds in the high-throughput screen can interfere with signal generation, resulting in false positives. “The risk of this happening can be reduced by measuring the fluorescent signal at long wavelengths (>500 nm),” stated Lloyd.

Commonly, each plate in an HTS assay contains positive and negative controls and tool compounds, which are used to monitor assay performance using statistical methods. One such measure of assay performance is the Z prime (Z’) factor.

“A Z’ value of 0.5 is considered to be the threshold where an assay is sufficiently good to differentiate a genuine signal from random noise,” said Lloyd. “Positive and negative controls are run alongside the screen in every plate, and any plate which has a Z’ value of less than 0.5 is run again.”

Unlike signal‑to‑noise or signal‑to‑background ratios, the Z’-factor captures both assay window and data dispersion, making it more predictive of real screening performance under HTS conditions. While the Z’-factor has become central to many HTS assays, its interpretability in complex cell-based assays can be limited.

Considerations for HTS assay failure start even before the experiment itself, beginning with the creation of the compound library. Lloyd emphasized the importance of having an appropriate balance between diversity and redundancy within a library. “High diversity means that more chemical space is screened, but the disadvantage is that useful scaffolds could be missed if the specific compound within the library is inactive,” he explained. “Typically, 4 to 12 representatives of each scaffold will give an appropriate balance between diversity and compound redundancy.” 

Strategies to prevent assay development failures

One of the main strategies for overcoming false positives in HTS assays is to design out artifacts, including those caused by aggregates and reactive oxygen species. “Compound aggregation is a common problem, as many drugs have limited solubility in water. For this reason, assays often include detergents as these reduce aggregation,” said Lloyd. “Reactive oxygen species can be detected using a specialized assay that measures formation.”

Hit validation consists of a series of steps designed to determine whether a result is genuine or a false positive. “This involves repeating the assay under identical conditions in the presence of hit compounds, repeating the assay in the presence of higher detergent concentrations with hit compounds, measuring reactive oxygen species formation by the hit compound, etc.,” Lloyd stated.

By designing orthogonal assays that challenge initial hit assumptions, it's possible to improve the biological relevance of the screening program and reduce downstream attrition. “This step eliminates many of the false positive compounds which exert their effects by interfering with fluorescent read-out or interfering with the HTS assay in other ways,” said Lloyd.

Early consideration of downstream validation requirements can inform better primary assay design. Primary assays should be designed with known secondary validation pathways and in anticipation of common assay artifacts. In addition, sensitivity and specificity should be balanced across the screening phases.

Many HTS campaigns in industry use libraries containing millions of compounds; ensuring assays can be “miniaturized” in these instances is key, Lloyd suggested. Fluorescent assays are often chosen because of their compatibility with miniaturization “despite the risk of false positive results,” said Lloyd.

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The goal of developing a HTS assay is to mimic a pathological or physiological process as closely as possible. This often involves a trade-off between biological relevance and throughput. Lloyd used the examples of proteins—common targets in many HTS campaigns—to illustrate this point: “It is usually not possible to produce ‘native’ protein from the disease source, and recombinant proteins are often used because production is more consistent and scalable…There are examples where identified compounds behave completely differently when targeting different versions of the same protein.”

Navigating this trade-off can be done using hybrid approaches that implement primary biochemical assays for rapid, high-density primary screening, followed by secondary phenotypic, 3D cell culture, or CRISPR-based assays for lower-throughput, high-relevance validation.

Emerging strategies for reducing HTS assay attrition

In the 1990s and early 2000s, advances in robotics and data analysis allowed miniaturization of HTS assays, and screens moved away from 96-well plates to 384- and 1536-well plates. However, “further miniaturization is difficult because the miniaturization process itself can result in assay artefacts,” explained Lloyd.

“There have, of course, been many advances since then in detection technology, enabling faster screening and the use of newer types of assay methods. Systems for analyzing data have also significantly improved,” he continued.

The integration of AI and machine learning in HTS workflows has enabled more efficient hit identification, improved assay quality control, and enhanced predictive modeling. AI models are particularly well suited to identifying non-linear relationships and subtle phenotypic signatures that conventional statistical approaches to data analysis may miss.

In addition to the rise of AI in drug discovery, there has also been a notable shift away from traditional small molecule drugs as treatments. This has been driven by the widespread recognition that some conditions are intractable using small molecule approaches.

“There are newer therapeutic approaches in development, such as targeted protein degradation using compounds such as PROTACs. Compounds of this type are catalytic in the sense that the compound is regenerated once the protein target has been degraded. Understanding the complex cellular machinery involved in targeted protein degradation and the ‘design rules’ for compounds that exploit these processes is essential for further development as treatments,” Lloyd said. “Because of the complexity of this process, new types of cellular assays will be needed to allow compound development.”

The success of HTS campaigns depends on understanding the biology it seeks to replicate. Improving assay design as new therapeutics take the forefront is therefore essential to unlocking more reliable, translatable drug discovery.