Analytical and clinical validation of a novel, laboratory-developed, modular multiplex-PCR panel for fully automated high-throughput detection of 16 respiratory viruses

Background

: Viral respiratory Infections pose a health risk, especially to vulnerable patient populations. Effective testing programs can detect and differentiate these infections at an early stage, which is particularly important for high-risk clinical departments. The objective of this study was to develop and validate a multiplex PCR-panel for 16 different respiratory viruses on a fully-automated high-throughput platform.

Methods

Three multiplex-PCR assays were designed to run on the cobas5800/6800/8800 systems, consolidating 16 viral targets: RESP1: SARS-CoV-2, influenza-A/B, RSV; RESP2: hMPV, hBoV, hAdV, rhino-/ENV; RESP3: HPIV-1–4, hCoV-229E, hCoV-NL63, hCoV-OC43, hCoV-HKU1. Analytic performance was evaluated using digital-PCR based standards and international reference material. Clinical performance was determined by comparing results from clinical samples with reference assays.

Results

Analytical sensitivity (i.e. lower limit of detection (LoD), 95 % probability of detection) was determined as follows: SARS-CoV-2: 29.3 IU/ml, influenza-A: 179.9 cp/ml, influenza-B: 333.9 cp/ml and RSV: 283.1 cp/ml. LoDs of other pathogens ranged between 9.4 cp/ml (hCoV-NL63) and 21,419 cp/ml (HPIV-2). Linearity was verified over 4–7 log-steps with pooled standard differentials (SD) ranging between 0.18–0.70ct. Inter-/intra-run variability (precision) was assessed for all targets over 3 days. SDs ranged between 0.13–0.74ct. Positive agreement in clinical samples was 99.4 % and 95 % for SARS-CoV-2 and influenza-A respectively. Other targets were in the 80–100 % range. Negative agreement varied between 96.3–100 %.

Discussion

Lab-developed tests are a key factor for effective clinical diagnostics. The multiplex panel presented in this study demonstrated high performance and provides an easily scalable high-throughput solution for respiratory virus testing, e.g. for testing in high-risk patient populations.