Vaccines have played a huge role in improving human health, but there is still a great need for new and improved vaccines. Despite decades of innovation, vaccine development remains challenging. Immunological responses are frequently difficult to measure and the mechanisms underlying how an immunological response confers protection remain poorly understood.
Traditionally, vaccines are tested in late-stage trials against naturally circulating viruses in the community. Many thousands of people are inoculated with the developmental vaccine in the hope that a sufficient number will encounter the virus for its protective index to be calculated. This approach can be hit and miss. For example, if the incidence of infection at the time is low, there may be insufficient responses to provide statistically significant results. Other circulating viruses can also interfere with the observation of symptoms, making for “noisy” data. In addition, trials of this type are expensive – and often fail when early evaluations of efficacy or safety in small numbers of healthy volunteers don’t translate into larger, more heterogeneous populations. Indeed, a key question for vaccine development is, how can predictions of a vaccine’s real-world effectiveness be improved?
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