Development of monoclonal antibody based SPCE logistic regression model to predict the protective status of animals vaccinated against FMD virus type A.

Abstract

In enzootic regions like India, foot-and-mouth disease (FMD) is managed through vaccination and strict biosecurity. Traditionally, FMD vaccine potency is assessed via in vivo challenge, which raises animal welfare concerns. As an alternative, this study evaluated a serology-based indirect potency test using 87 serum samples derived from calves 28 days post-vaccination. Samples were analyzed via virus neutralization test (VNT) and SPCEs employing polyclonal (pAb) and monoclonal antibodies (mAbs 2C4G11 and 6E8D11). Log₁₀ serum titres (ti) were correlated with protection outcomes from live virus challenge (FMDV serotype A/40/2000) using logistic regression. Four logit models were developed, and ROC analysis determined ti cut-offs for 50 %, 75 %, and 95 % protection probabilities (pi). VNT and mAb SPCEs showed sigmoid logit curves, indicating strong ti-pi correlation. Based on AIC and Somers' D, mAb 2C4G11 SPCE was the best-fit model. At 75 % pi, ti thresholds for VNT, pAb, mAb 2C4G11, and mAb 6E8D11 were > 1.204, > 1.041, > 1.204, and > 1.204, respectively, with mAb 6E8D11 showing highest accuracy. Thus, mAbs 2C4G11 and 6E8D11 SPCEs are promising tools for predicting homologous protection. Further validation with larger sample sizes is recommended.