Overview
Laboratory Optimizer for Mass Testing (LOMT) is laboratory software that manages pool testing workflows for molecular diagnostics or other qualitative testing methods in the epidemiological monitoring, mass screening, and clinical diagnosis for COVID-19 and other infectious diseases. By using advanced pool testing algorithms and advanced data analytics, LOMT allows laboratories to reduce testing cost and time, and increase capacity by up to 30 times.
LOMT extends existing testing processes by introducing additional steps of pooling design, mixing samples into pools, decoding the result of pools, and reporting the results of samples. Depending on the goals and conditions of the testing, these steps can be performed in the laboratory during the testing or outside the laboratory at the point of care or sample collection point.
This paper addresses the operational efficiency of different pool-testing strategies in typical scenarios of a PCR laboratory working in mass testing for COVID-19 with different values of prevalence, limitations and conditions of testing, and priorities of optimization.
Objectives & Challenges
The project addresses the development of the pool testing workflows in a laboratory, the development of the software tat supports these workflows, and the study of the operational efficiency of different pool-testing strategies in typical scenarios of a PCR laboratory working in mass testing for COVID-19 with different values of prevalence, limitations and conditions of testing, and priorities of optimization.
The efficiency indicators assessed are the number of assays needed to obtain results of a batch of specimens, the number of specimens identified after the first analysis, and total time to obtain all results. Depending on prevalence, constraints of testing, and priorities of optimization, different pool-testing strategies provide the best operational efficiency.
The main challanges are to develop a software tool implementing the most promising pooling strategies and supporting laboratory testing workflows, and to perform the simulation of pool testing workflows in different conditions to identify the optimal algorithms and parameters for these conditions.
Main Findings
The major indicator of the efficiency of a pool-testing strategy is the reduction of the number of assays for a certain number of specimens. The analysis process takes a long time, consumes reagents and requires significant manual labor. Other related processes require much less time and cost, and in most cases, a tenfold reduction in the number of assays increases the throughput of the laboratory by 9 times and also decreases the cost of the testing of one person by 9 times.
The number of assays primarily depends on prevalence (the proportion of positives samples) and the maximum pool size (the limit of dilution of a specimen). The lower the prevalence, the larger the pool size that can be used, and ultimately, fewer assays will be required. For example, for 1% prevalence, the maximal effective pool size is 69, for 10% prevalence it is 7 and for prevalence above 25% the pool size becomes less than 4 and the efficiency becomes too low to be worth using.
Different laboratories can operate with different values of prevalence, constraints of testing and priorities of optimization, and these values can change over time. LOMT supports several different pooling strategies and automatically searches for the optimal strategy for every specific condition.
For a high prevalence (10%) and the maximum pool size 8, the maximum reduction of the number of assays is 2.1x compared to the individual testing: for a batch of 1000 specimens the pool testing uses 477 assays on average, while the individual testing uses 1000 assays. For a medium prevalence (1%) and the maximum pool size 32, the maximum reduction of the number of assays is 11x, with 90 assays on avarage for a batch of 1000 specimens. For a low prevalence (0.1%) and the maximum pool size 32, the maximum reduction of the number of assays is 25x, with 39 assays on average for a batch of 1000 specimens.
Main Recommendations
We propose to use pool testing more widely in the mass testing for COVID-19 and to use Laboratory Optimizer for Mass Testing as a tool to support and improve pools testing in laboratories. By using advanced pool testing algorithms and advanced data analytics, LOMT allows laboratories to reduce testing cost, time, and errors, and increase laboratory capacity by up to 30 times.
LOMT can be used in the diagnostics, contact tracing, screening, and epidemiological monitoring, including frequent screening of high-risk groups (medical staff, teachers and students, public services, company employees) and epidemiological surveillance of the population for early detection of infected people and prevention the spread of infections by the localization of foci of infection. It can by applied in any qualitative test of the presence of a single target component — i.e., SARS-CoV-2 RNA with PCR or other techniques that allow mixing several specimens into an assay.
