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Navigating IVDR & WHO TSS-1 Compliance for In Vitro Diagnostic Devices

Bioexcel News

  • Scientific Validity – Establishing a proven link between the analyte and the clinical condition.

  • Analytical Performance – Demonstrating accuracy, precision, and reproducibility of test results.

  • Clinical Performance – Proving the test’s correlation with the clinical condition in the intended population.

  • Unique Device Identification (UDI) for better traceability.

  • Post-Market Surveillance (PMS) and Post-Market Performance Follow-up (PMPF) planning.

  • Class A – Low Risk

  • Class B – Low-Moderate Risk

  • Class C – Moderate to High Risk

  • Class D – High Risk

  • Determined by intended use, target population, and technology employed.

  • Defines the conformity assessment route.

  • Determines Notified Body involvement.

  • Sets the scope of clinical evidence & performance evaluation.

  • Establishes PMS requirements.

  • Class D devices face the most rigorous scrutiny, often requiring EU Reference Laboratory testing.

  • Class A non-sterile devices may follow a self-declaration route.

Device ClassDeadline
Class D26 May 2025
Class C26 May 2026
Class B & Class A (sterile)26 May 2027

  • Continued compliance with IVDD requirements.

  • No significant changes in design/intended use.

  • Submission of an IVDR conformity assessment application to a Notified Body with a signed contract before the deadline.

Defining the intended use is the foundation for WHO PQ compliance. Manufacturers must:

  • Clearly define the device function — for example, detecting antibodies to HIV-1/HIV-2 and/or p24 antigen in human specimens.

  • Specify the intended population — e.g., adults, pregnant women, high-risk groups, or the general population.

  • Identify the intended setting — point-of-care clinics, community-based testing, laboratory use, or self-testing scenarios.

  • State the test type — whether the device is qualitative (reactive/non-reactive), semi-quantitative (relative levels of the analyte), or quantitative (absolute measurement values).

Analytical performance evaluates how the test behaves under controlled laboratory conditions, focusing on accuracy and reliability of detection.

WHO TSS-1 specifies that manufacturers must demonstrate:

  • Analytical Sensitivity – the lowest detectable level of the target analyte (e.g., HIV antibodies or p24 antigen) that the test can identify with high reliability.

  • Analytical Specificity – the ability to accurately detect only the intended analyte without producing false positives due to cross-reactivity with other substances, infections, or conditions.

  • Precision & Reproducibility – the consistency of results when tested by:
    • Different operators (inter-operator reproducibility) At different sites (inter-laboratory reproducibility)
    • Across different times or test runs (inter-assay reproducibility)

  • Specimen Equivalency – validation that the test produces equivalent results across different claimed specimen types such as capillary whole blood, serum, plasma, or oral fluid.

Clinical performance measures how the test performs in real-world settings with the intended population. WHO TSS-1 outlines key parameters:

  • Diagnostic Sensitivity – the probability that the test correctly identifies individuals with HIV (true positives).

  • Diagnostic Specificity – the probability that the test correctly identifies individuals without HIV (true negatives).

  • Predictive Values
    • Positive Predictive Value (PPV): likelihood that a reactive result is a true positive.
    • Negative Predictive Value (NPV): likelihood that a non-reactive result is a true negative.
      These values are population-dependent and must be calculated for the intended testing scenario.

  • Inclusivity – ability to detect a wide range of HIV-1 and HIV-2 subtypes and groups, ensuring the test remains effective globally, even in regions with high subtype diversity.

  • Exclusivity – ability to avoid false positives caused by other infections (e.g., hepatitis, syphilis, malaria) or medical conditions.

  • Lay-user Performance Studies – evidence that individuals without formal training can perform the test and correctly interpret results.

  • Human Factors Engineering – ensuring that test design minimises errors in handling and reading results.

  • Clear Labelling & Instructions for Use (IFU) – all instructions should be:
    • Written in plain language Supported by diagrams or images
    • Available in relevant local languages

IVD

PMCF

regulatory affairs

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