A Minimal Framework for Optimizing Vaccination Protocols Targeting Highly Mutable Pathogens
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2024
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866913327783870464 |
|---|---|
| author | Mahdisoltani, Saeed Murugan, Pranav Chakraborty, Arup K Kardar, Mehran |
| author_facet | Mahdisoltani, Saeed Murugan, Pranav Chakraborty, Arup K Kardar, Mehran |
| contents | A persistent public health challenge is finding immunization schemes that are effective in combating highly mutable pathogens such as HIV and influenza viruses. To address this, we analyze a simplified model of affinity maturation, the Darwinian evolutionary process B cells undergo during immunization. The vaccination protocol dictates selection forces that steer affinity maturation to generate antibodies. We focus on determining the optimal selection forces exerted by a generic time-dependent vaccination protocol to maximize production of broadly neutralizing antibodies (bnAbs) that can protect against a broad spectrum of pathogen strains. The model lends itself to a path integral representation and operator approximations within a mean-field limit, providing guiding principles for optimizing time-dependent vaccine-induced selection forces to enhance bnAb generation. We compare our analytical mean-field results with the outcomes of stochastic simulations and discuss their similarities and differences. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_15634 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Minimal Framework for Optimizing Vaccination Protocols Targeting Highly Mutable Pathogens Mahdisoltani, Saeed Murugan, Pranav Chakraborty, Arup K Kardar, Mehran Populations and Evolution Statistical Mechanics Biological Physics A persistent public health challenge is finding immunization schemes that are effective in combating highly mutable pathogens such as HIV and influenza viruses. To address this, we analyze a simplified model of affinity maturation, the Darwinian evolutionary process B cells undergo during immunization. The vaccination protocol dictates selection forces that steer affinity maturation to generate antibodies. We focus on determining the optimal selection forces exerted by a generic time-dependent vaccination protocol to maximize production of broadly neutralizing antibodies (bnAbs) that can protect against a broad spectrum of pathogen strains. The model lends itself to a path integral representation and operator approximations within a mean-field limit, providing guiding principles for optimizing time-dependent vaccine-induced selection forces to enhance bnAb generation. We compare our analytical mean-field results with the outcomes of stochastic simulations and discuss their similarities and differences. |
| title | A Minimal Framework for Optimizing Vaccination Protocols Targeting Highly Mutable Pathogens |
| topic | Populations and Evolution Statistical Mechanics Biological Physics |
| url | https://arxiv.org/abs/2404.15634 |