Optimization and analisys of vaccination schedules using simulated annealing and agent based models

Vaccines represent nowadays one of the most efficient weapons against foreign pathogens. To be effective, vaccines need a proper administration strategy that requires multiple administrations in order to ensure the acquisition of immunological memory. Vaccination schedules are usually based on past experience, and economical, ethical and time constraints have limited the research for better combinations of timing and dosage. We present here a computational approach based on the use of stochastic optimization techniques and validated “in silico” models to study and optimize vaccination protocols. We use Simulated Annealing in conjunction with a validated agent based model to suggest some interventions that may improve the efficacy of a candidate vaccine composed by influenza-A virosome and natural citrus-derived adjuvants to prevent influenza-A infection.