Group B Streptococcus (GBS) remains a leading cause of neonatal mortality, underscoring the need for effective vaccination strategies. This study introduces a novel adaptation of an ODE-based immunological model to simulate the response to a Type V GBS-TT conjugate vaccine, with model calibration and validation performed against clinical data. Utilizing Differential Evolution, we accurately estimated immunological parameters across various dosages, revealing mechanistic differences between conjugated and unconjugated formulations. Our numerical results show that key parameters—specifically, the antigen-presenting cell maturation rate and the antibody-mediated vaccine clearance rate—were 93-fold and 1,700-fold higher, respectively, in conjugated vaccines compared to unconjugated formulations. These findings underscore the adjuvant effect of tetanus toxoid and demonstrate the model’s capacity for guiding rational vaccine design and optimization.

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Predicting Antibody Responses to Type V GBS-TT Conjugate Vaccine Using Computational Modelling

  • Matheus R. Ribeiro,
  • Bárbara de M. Quintela,
  • Ruy F. Reis,
  • Rodrigo W. dos Santos,
  • Marcelo Lobosco

摘要

Group B Streptococcus (GBS) remains a leading cause of neonatal mortality, underscoring the need for effective vaccination strategies. This study introduces a novel adaptation of an ODE-based immunological model to simulate the response to a Type V GBS-TT conjugate vaccine, with model calibration and validation performed against clinical data. Utilizing Differential Evolution, we accurately estimated immunological parameters across various dosages, revealing mechanistic differences between conjugated and unconjugated formulations. Our numerical results show that key parameters—specifically, the antigen-presenting cell maturation rate and the antibody-mediated vaccine clearance rate—were 93-fold and 1,700-fold higher, respectively, in conjugated vaccines compared to unconjugated formulations. These findings underscore the adjuvant effect of tetanus toxoid and demonstrate the model’s capacity for guiding rational vaccine design and optimization.