A standardised, high-throughput approach to diagnostic group testing method validation

Background Group testing, combining the samples of multiple patients into a single pool to be tested for infection, is an approach to increase throughput in clinical diagnostic and population testing by reducing the number of tests required. In order to further increase the throughput and accuracy of these approaches, mathematicians regularly devise novel combinatorial methods. However, although these novel methods are easily validated in silico, they are often never implemented in diagnostic laboratories because of the lack of clear and standardised pathways to clinical validation. Methods We develop a standardised analytical workflow that makes use of high-throughput automation and virus-like particle standards to validate theoretical group testing approaches. We then utilise specially developed virus-like particles for SARS-CoV-2, Influenza A, Influenza B, and Respiratory Syncytial Virus (RSV) to develop and validate a novel multiplex group testing approach based on simulated annealing and Bayesian optimization. Our approach improves the inference of positive samples in group testing, leveraging the quantitative nature of RT-qPCR test results. Results Our results show a higher positive predictive value of our novel approach for the inference of positive samples compared to the standard approach using binary test outcomes. In large-scale surveillance testing our method can greatly reduce the number of false positive identifications. Our in vitro findings show the viability of group testing for multiplexed testing of respiratory infections and demonstrate the potential of a novel inference method. Both innovations increase the number of people that can be tested with the available resources, which is particularly important in low-resource settings. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work is supported by the UK Dementia Research Institute which receives its funding from UK DRI Ltd, funded by the UK Medical Research Council, Alzheimers Society and Alzheimers Research UK. We also acknowledge funding from UKRI-EPSRC (EP/R014000/1) and Community Jameel. LU and LC acknowledge funding from the MRC Centre for Global Infectious Disease Analysis (reference MR/X020258/1), funded by the UK Medical Research Council (MRC). This UK funded award is carried out in the frame of the Global Health EDCTP3 Joint Undertaking. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes In vitro data are available online at