Introduction In vaccine development, dose-response curves are commonly assumed to be saturating. Evidence from tuberculosis (TB) vaccine, H56 + IC31 shows this may be incorrect. Mathematical modelling techniques may be useful in efficiently identifying the most immunogenic dose, but model calibration requires longitudinal data across multiple doses and time points. Aims We aimed to (i) generate longitudinal response data in mice for a wide range of H56 + IC31 doses for use in future mathematical modelling and (ii) test whether a ‘saturating’ or ‘peaked’ dose-response curve, better fit the empirical data. Methods We measured IFN-γ secretion using an ELISPOT assay in the splenocytes of mice who had received doses of 0, 0.1, 0.5, 1, 5 or 15 μg H56 + IC31. Mice were vaccinated twice (at day 0 and 15) and responses measured for each dose at 8 time points over a 56-day period following first vaccination. Summary measures Area Under the Curve (AUC), peak and day 56 responses were compared between dose groups. Corrected Akaike Information Criteria was used to test which dose-response curve best fitted empirical data, at different time ranges. Results (i) All summary measures for dose groups 0.1 and 0.5 μg were higher than the control group (p < 0.05). The AUC was higher for 0.1 than 15 μg dose. (ii) There was strong evidence that the dose-response curve was peaked for all time ranges, and the best dose is likely to be lower than previous empirical experiments have evaluated. Conclusion These results suggest that the highest, safe dose may not always optimal in terms of immunogenicity, as the dose-response curve may not saturate. Detailed longitudinal dose range data for TB vaccine H56 + IC31 reveals response dynamics in mice that should now be used to identify optimal doses for humans using clinical data, using new data collection and mathematical modelling.
Rhodes, S. J., Zelmer, A., Knight, G. M., Prabowo, S. A., Stockdale, L., Evans, T. G., … Fletcher, H. (2016). The TB vaccine H56 + IC31 dose-response curve is peaked not saturating: Data generation for new mathematical modelling methods to inform vaccine dose decisions. Vaccine, 34(50), 6285–6291. https://doi.org/10.1016/j.vaccine.2016.10.060