Risa Yokokawa1, Hyeongki Park2, Hiroki Koshimichi1, Ryosuke Shimizu1, Masaharu Shinkai3, Shingo Iwami2, Ryuji Kubota1
1Clinical Pharmacology & Pharmacokinetics, Medical Science Department, Shionogi & Co., Ltd. , 2interdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University, 3Tokyo Shinagawa Hospital
Introduction: Vaccination is the most effective and economical intervention for controlling the spread of epidemics, and various techniques have been employed in the development of COVID-19 vaccines [1]. S-268019-b is a recombinant protein prophylactic vaccine comprising a modified recombinant spike protein of SARS-CoV-2 [2]. Although some studies have investigated using mathematical modeling approaches about dynamics of antibodies following mRNA vaccination against COVID-19 [3, 4], there have been no reports addressing the dynamics of antibodies following protein vaccination against COVID-19 and dynamics of T cell responses. Those models are expected to contribute to a better understanding of the immunological mechanisms involved in vaccine-induced protection and inform future vaccination strategies. Objectives: The objective of this study is to characterize immune responses following mRNA- or protein-based vaccination of SARS-CoV-2 based on mathematical model models for neutralizing antibody titers and T cell responses. Methods: Two mathematical models for neutralizing antibody titers and T cell responses were constructed with neutralizing antibody titers in phase 2/3 study of S-268019-b [5], and IFN-?-producing cell count by ELISPOT assay in phase 1/2 [2], 2/3 [5], and 3 [6] [7] studies of S-268019-b. A neutralizing antibody titer model was constructed with neutralizing antibody titer from participants who received a single booster vaccination of protein-based vaccine (S-268019-b, N=102) or mRNA-based vaccine (Tozinameran, N=104). The model consists of three compartments representing the amount of vaccinated protein or mRNA, the number of antibody-secreting cells, and the neutralizing antibody titer at time t. To fit this model to each participant’s neutralizing antibody titer data, we estimated two key parameters (the maximum rate constant for neutralizing antibody increase [?] and decrease rate constant for the number of antibody-secreting cells [d]) using the non-linear mixed effects model. Parameter estimation was performed with MONOLIX2023R1. Using the estimated parameter, we reconstructed neutralizing antibody dynamics for each participant. Then, we calculated three features of the reconstructed antibody dynamics for each participant: the maximum antibody titer (Peak_A), Time to maintain neutralizing antibody titer above of 10 (Duration), and Area under the titer-time curve (AUC_A). T cell response model was constructed with IFN-?-producing cell counts by ELISPOT assay after vaccination with the protein-based vaccine (S-268019-b, N=148) or the mRNA-based vaccines (Tozinameran or Elasomeran, N=59). This model assumes that the response (dt), proliferation or differentiation or disappearance (ßET) of two types of T cells, effector T cells and memory T cells, to vaccine stimulation changes before and after the time elapsed after vaccination (t), and RESP, kin, and kout explain dt (d(t)=(RESP·kin)/(kin-kout)(e^(-kout·t)-e^(-kin·t))). The five parameters (RESP, kin, kout, ßET, t) were estimated using non-linear linear model. We estimated the maximum number of activated T cells (Peak_T), half-life (T1/2), and Area under the number of activated T cells-time curve (AUC_T) for the participants who received S-268019-b (N=29) or Tozinameran (N=29) in phase 2/3 study of S-268019-b [5]. Parameter estimation was performed with NONMEM. Results: We constructed a model that effectively captures the long-term dynamics of the observed immune response of neutralizing antibody titers and T cell responses after vaccination through parameters reflecting its key characteristics. These models quantitatively evaluate the characteristics of the immune response after vaccination, and the following results showed interesting characteristics in particular; The mean of the parameter estimates for Duration using neutralizing antibody titer model were 530 days in S-268019-b and 391 days in Tozinameran. The mean of the parameter estimates for Peak_T using T cell responses model were 173 cells (/1.0×10^5cells) in S-268019-b and 99 cells (/1.0×10^5cells) in Tozinameran. Conclusion: We constructed new models to characterize immune responses following mRNA- or protein-based vaccine of SARS-CoV-2. Those models facilitate more precise interpretation of individual immune response.
[1] Fang, E. et al., Signal Transduction and Targeted Therapy, Volume 7, Article number: 94 (2022) [2] Iwata, S. et al., Vaccine, Volume 40, Issue 27, 15 June 2022, Pages 3721-3726 [3] Nishiyama, T. et al., Vaccine, Volume 41, Issue 52, 18 December 2023, Pages 7655-7662 [4] Nakamura, N. et al., PLOS Digital Health, 3 May 2024 [5] Shinkai, M. et al., Vaccine, Volume 40, Issue 32, 30 July 2022, Pages 4328-4333 [6] Sonoyama, T. et al., 2023, Vaccine:X, Volume 15, December 2023, 100390 [7] Iwata, S. et al., Scientific Reports volume 14, Article number: 9830 (2024)
Reference: PAGE 33 (2025) Abstr 11760 [www.page-meeting.org/?abstract=11760]
Poster: Drug/Disease Modelling - Infection