Developing Reader Based Multiplex Lateral Flow Tests for Complex Biomarker Signatures

How structured data and algorithmic interpretation are shaping the next generation of lateral flow assays

Lateral Flow Assays are well established as rapid, portable and practical diagnostic tools. For many applications, a single marker assay remains the most appropriate format, particularly where the target is well defined and the result can be interpreted against a clear threshold. Depending on the intended use, that result may be read visually, measured with a reader or supported by a simple digital workflow.

However, some clinical questions require more information than one marker can provide. In areas such as triage, risk stratification and disease monitoring, the most useful result may come from a combination of markers or from the relationship between them. This is driving interest in multiplex lateral flow assays that can generate richer information from a single sample.

Reader based analysis is expanding what can be done with lateral flow. A multiplex strip can generate several signals from the same sample, while a reader can turn those signals into structured data that can be compared, trended and interpreted consistently. This opens the door to marker ratios, risk scores, longitudinal monitoring and algorithmic interpretation, while keeping the practical advantages that make lateral flow attractive in the first place.

This article follows that development pathway: identifying when a biomarker signature adds value, building evidence before strip development, translating candidate markers into a multiplex lateral flow format and designing the assay so that the reader and software can generate reliable data. It also considers the practical implications for manufacture, stability, cost, software control and regulatory planning.

Why biomarker signatures are becoming more important

Many clinical conditions are not defined by one biological signal. A single biomarker may be affected by disease stage, sample type, inflammation, comorbidities, treatment status or normal biological variation. It may provide useful information, but still fail to separate clinically relevant groups with enough sensitivity or specificity.

In these cases, diagnostic value may come from a biomarker signature. This could involve a combination of markers, ratios between markers, a host response pattern or a score that weights several signals together. One marker may improve sensitivity, another may improve specificity and another may help identify a subgroup where the clinical risk is different.

This type of approach can be relevant across several application areas. In suspected large vessel occlusion stroke, for example, the clinical value of a test may come from supporting rapid routing to the most appropriate care pathway. In cancer risk stratification, the key question may be whether a patient is at higher risk of aggressive disease or progression. In fertility or hormone monitoring, the trend or relationship between urinary hormone markers may be more informative than a single isolated measurement.

Each additional marker should be assessed against the performance requirement it is intended to improve. If two markers already meet the required sensitivity target, a third marker that gives only a marginal sensitivity gain may not justify the added antibody pair, conjugate and QC burden. If that marker improves specificity, reduces false positives or separates a clinically important risk group, the value proposition changes.

The analytical requirement still remains. Each marker must show a detectable and reproducible difference from baseline or from the relevant comparator group. Ratios and algorithms can improve interpretation, but they cannot rescue an assay from weak or inconsistent primary measurements.

This is where multiplexing and reader-based interpretation become linked. Once individual marker performance has been established, combining measurements can reveal patterns that may not be apparent from any single marker alone. The reader then becomes important not because it substitutes for analytical performance, but because it integrates these validated signals into a more informative interpretation.

Building evidence before lateral flow development

Before committing to a multiplex lateral flow format, developers may need to assess candidate markers and possible ratios using early feasibility sample sets. This type of work is intended to inform marker selection and assay direction, rather than act as formal clinical performance evaluation. Samples may be banked from previous studies or collected prospectively under an appropriate research protocol.

The first question is whether the biology is strong enough to justify translation. At this stage, quantitative measurement of clinical samples can help determine whether candidate markers are present in the relevant concentration range, whether they separate the intended sample groups and whether combinations or ratios are worth taking forward. Where suitable methods are already available, existing research use only (RUO) or diagnostic kits, established laboratory immunoassays or targeted biomarker assays may be the most efficient route.

The data generated then needs to be interpreted in the context of the final lateral flow format. ELISA and other laboratory methods often use longer incubation times, wash steps and controlled processing conditions and may therefore achieve lower limits of detection and better precision than a rapid strip format. A marker that is measurable in a laboratory assay may not automatically sit in a practical concentration range for lateral flow.

For each marker, developers need to consider the expected concentration range in the intended sample type, the required clinical cut off and whether the lateral flow format can provide enough sensitivity and dynamic range. This becomes more important in multiplex assays because all markers typically need to work under the same sample preparation and running conditions. If one marker requires dilution to bring it into range, that same dilution may move a lower-abundance marker below its useful detection range. These decisions help determine whether a marker is suitable for inclusion in the panel and what level of antibody performance will be required.

Gyrolab™, an automated microfluidic immunoassay platform, can be useful at this stage as a low-volume, flow through screening tool. Where suitable assays are available, it can support automated biomarker measurement when clinical sample volume is limited. Where antibody selection is required, it can help rank larger antibody panels and reduce them to a smaller pool before lateral flow feasibility work begins.

Compared with a standard ELISA, where binding typically occurs during longer static incubations, Gyrolab’s controlled flow through format exposes antibody-antigen interactions to defined flow and contact conditions. This makes it a useful upstream screen for prioritising candidate antibody pairs, while keeping the detailed assessment of strip performance for the next phase.

Designing the multiplex assay format

Once there is enough evidence to take a single marker or group of markers forward, the next step is to translate the selected reagents into a practical lateral flow format. At this point, the work shifts from upstream screening towards strip design, including conjugate preparation, reagent deposition, line placement, buffer compatibility, cross-reactivity assessment, and evaluation of how these variables affect signal balance, background, and interpretation across the assay.

The starting point may vary. Some projects may already have established antibody pairs. Others may have selected the markers or epitopes of interest, but still need suitable antibody pairs for lateral flow. If commercial antibodies are unavailable, unsuitable or do not provide the required control over intellectual property (IP), supply or clone ownership, an antibody development programme may be needed before strip feasibility can begin.

In the lateral flow format, these reagents are exposed to a different set of assay conditions. Reagents are dried and rehydrated, detector conjugates must release consistently, binding occurs during capillary flow, and the available contact time is limited. These constraints mean that antibody pairs prioritised during upstream screening still need to be confirmed in the final strip format.

In a multiplex assay, each test line may respond differently to the same assay conditions. Differences in antibody kinetics, antigen concentration, conjugate release, capture efficiency, local background or line position can affect one marker signal more than another. This matters where the final result depends on marker ratios, weighted scores or comparison between line intensities.

The development team therefore needs to establish strip design conditions that allow all markers to function together. This includes controlling cross-reactivity between reagents, optimising line placement and spacing, balancing conjugate release, maintaining acceptable background across all test lines, and confirming that each marker remains interpretable within the intended read window.

Multiplexing increases the number of possible interactions within the assay. Antibodies that behave well in singleplex may not behave the same way when combined with other antibody pairs, detector conjugates or capture lines. Antigens may also interact with non-intended test lines, particularly where related proteins, shared epitopes or complex clinical matrices are involved.

For this reason, cross reactivity should be screened early. It should not be treated only as a late verification activity. Early screening helps identify problematic pairings before the strip design is fixed and can guide antibody selection, conjugate strategy and line configuration.

Designing for reliable reader data

Reader based multiplex assays need to be designed so that each line can be captured and interpreted reliably. This means considering the strip layout, cassette design, read window, line morphology and reader method together during development.

Consistent line development is critical. The result may depend on relative signal intensity across several lines, so edge effects, hot spots, gaps or uneven background can affect both quantification and marker ratios.

Line spacing is also important. Lines need to be far enough apart to avoid interference with neighbouring lines, background regions and reader analysis windows. A weak line positioned close to a very intense line can be particularly challenging if the adjacent peak edge or raised background affects the reader’s ability to separate the signals.

Manufacturing tolerances must also be considered early. Line placement, membrane lamination, strip placement in the housing and cassette assembly can all affect how the reader sees the test line signals. Small shifts that may be acceptable for a visual single marker assay may become more significant when the reader is measuring several lines and comparing their relative intensities.

The housing can also influence performance. The read window must allow the reader to capture the signal area without shadows, reflections or edge effects. If the housing casts shadows onto the membrane, the effective read window may be smaller than expected, which can affect background correction and line quantification.

The reader method should also be challenged with representative failure modes and borderline cases. This may include image quality checks, background assessment, line position checks and line morphology criteria, with predefined rules for rejecting invalid or unreliable reads where possible. Software can help manage some sources of variation, but it should not be used to compensate for poor assay or cassette design.

Using reader data for algorithmic interpretation

The value of reader based multiplex assays is not only that several lines can be measured. It is that the measurements can be combined into a controlled interpretation. Depending on the intended use, this may involve test line to control line ratios, marker to marker ratios, weighted scores, statistical models or machine learning models trained to classify patterns that are not easily reduced to a single threshold.

This is often what is meant when AI is discussed in relation to camera phone or reader based lateral flow assays. The software is not only detecting whether a line is present. It may be combining several signals, weighting markers differently, classifying risk groups, identifying invalid reads or supporting interpretation where the marker pattern is complex.

This is one reason data has become an investment area for reader based diagnostics. The strip generates the result, but the data layer can show how that result behaves across users, lots, sites, devices, sample types and environmental conditions. Over time, this can support better interpretation, usability improvements, quality monitoring, post market surveillance and future product development.

In some systems, value may also come from monitoring signal development over time rather than relying only on a single endpoint read. This can provide information on line formation, flow behaviour and assay kinetics, and may support earlier or more refined interpretation. However, it also increases the need for controlled timing and robustness studies, particularly where signal is changing rapidly during the read window.

Any algorithmic interpretation method needs to be validated against the intended use. If the method is changed or updated after launch, those changes need to be controlled, versioned and validated before they affect the reported result. Learning from data does not mean uncontrolled changes to the live diagnostic output.

Considering manufacture, stability and cost

A multiplex lateral flow assay can be cheaper, faster and simpler than running several separate tests, but each additional marker adds cost and complexity. In a sandwich format, this usually means another antibody pair and may also require a separate detector conjugate, depending on the assay design. It also adds optimisation work, quality control requirements and stability considerations.

There are practical advantages to multiplexing. A well designed multiplex assay can reduce the number of separate tests, reduce sample volume, simplify the user workflow and reduce packaging and plastic waste compared with multiple individual devices. The development decision should therefore consider cost, performance and system level value.

Stability also needs to be assessed across the full multiplex system. Each antibody pair, conjugate and capture reagent may have a different stability profile. If one marker signal decreases faster than the others, this can affect not only sensitivity, but also the ratios, score or final interpretation.

For reader based multiplex assays, stability studies should also consider how ageing affects the interpreted result. A gradual change in one marker signal may alter a marker ratio, weighted score or algorithmic output, particularly where the final result depends on relative signal rather than individual line intensity alone. This should be considered when defining acceptance criteria and interpretation rules.

Managing software, data and regulatory control

Reader based tests may process data directly on the device, through a mobile phone, or through a cloud connected workflow. Device based processing can be useful where rapid local results are needed or where connectivity is unreliable. Cloud based processing may support centralised analytics, remote monitoring, software updates, quality surveillance and connection to wider health systems.

Connected systems introduce responsibilities around data protection, cybersecurity, access control, audit trails, data retention, connectivity failure, algorithm version control and governance of software updates. These factors affect the risk profile, user workflow and regulatory strategy.

Where the reader, software or algorithm contributes to diagnostic interpretation, it may form part of the regulated IVD system. Relevant frameworks may include ISO 13485 for quality management, ISO 14971 for risk management, IEC 62304 for medical device software lifecycle and IEC 62366 for usability engineering. Where software has a diagnostic role, Software as a Medical Device (SaMD) guidance may also be relevant, depending on how the final system is supplied and used.

In August 2025, the FDA issued final guidance on predetermined change control plans for AI enabled device software functions.¹ For developers, the practical point is that planned updates to an AI enabled interpretation method should be defined, validated and controlled before they affect the reported result. Learning from data does not mean uncontrolled change to the live diagnostic output.

Conclusion

Reader based multiplex lateral flow assays are part of a broader move towards more data rich point of care testing. By combining multiple markers with structured reader output and algorithmic interpretation, these assays can support applications where the overall pattern of marker signals, rather than any single marker alone, is important to interpretation.

The development challenge is to align the biomarker signature, strip format, reader method, manufacturing controls, stability strategy and software governance from the start. When these elements are developed as one system, multiplex lateral flow can turn complex biomarker patterns into clearer clinical decisions while retaining the practical advantages of rapid point of care testing.

Learn more about our Lateral Flow Assay Development services, or contact us to discuss how we can support multiplex lateral flow development from early feasibility through to reader compatible assay optimisation and transfer.

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¹ Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence-Enabled Device Software Functions | FDA