The Power of Malaria Vaccine Trials Using Controlled Human Malaria Infection

Controlled human malaria infection (CHMI) in healthy human volunteers is an important and powerful tool in clinical malaria vaccine development. However, power calculations are essential to obtain meaningful estimates of protective efficacy, while minimizing the risk of adverse events. To optimize power calculations for CHMI-based malaria vaccine trials, we developed a novel non-linear statistical model for parasite kinetics as measured by qPCR, using data from mosquito-based CHMI experiments in 57 individuals. We robustly account for important sources of variation between and within individuals using a Bayesian framework. Study power is most dependent on the number of individuals in each treatment arm; inter-individual variation in vaccine efficacy and the number of blood samples taken per day matter relatively little. Due to high inter-individual variation in the number of first-generation parasites, hepatic vaccine trials required significantly more study subjects than erythrocytic vaccine trials. We provide power calculations for hypothetical malaria vaccine trials of various designs and conclude that so far, power calculations have been overly optimistic. We further illustrate how upcoming techniques like needle-injected CHMI may reduce required sample sizes.Author Summary: Controlled human malaria infection (CHMI) in healthy human volunteers is an important and powerful tool in clinical malaria vaccine development. However, to obtain meaningful estimates of protective efficacy, it is important to include an appropriate minimum number of participants, while minimizing the risks and burden for volunteers. Existing power calculations have limited value due to important influential assumptions. To optimize power calculations for malaria vaccine trials, we developed a non-linear, Bayesian statistical model for parasite kinetics as measured by quantitative real-time polymerase chain reaction, using existing data from mosquito-based CHMI experiments. Using our model, we provide improved, robust power calculations for various hypothetical malaria vaccine trials, taking account of important sources of variation between and within individuals. We conclude that so far, power calculations for malaria vaccine trials have been overly optimistic. We further illustrate how upcoming techniques like needle-injected CHMI may reduce required sample sizes.