Effect simulation method and system for serum type 2 riemerella anatipestifer inactivated vaccine

Abstract

The invention relates to the technical field of biology, in particular to an effect simulation method of serum type 2 riemerella anatipestifer inactivated vaccines, which comprises the following steps: S1, inputting vaccine dosage and inoculation schemes, inputting information of high, medium and low dosage inactivated vaccines, and single inoculation and booster immune schemes; s2, an immune response simulation model is established, the immune response of the ducks after vaccination is simulated through a biodynamic model, and the model is divided into two parts including a primary immune response and a subsequent immune memory response based on a mechanism of a vaccine stimulation immune system. The immune response, antibody generation and protective efficacy of the vaccine in a duck group are accurately simulated to help to determine the dose, immune cycle and effect of the vaccine. The scheme is different from the prior art, a more intelligent calculation model and an experimental method are adopted, and a data-driven vaccine efficacy simulation system is combined, so that the efficiency and scientificity of vaccine research and development can be effectively improved.

Description

Technical Field

[0001] The invention relates to the field of biotechnology, in particular to a method and system for simulating the efficacy of a serotype 2 Riemerella anatipestifer inactivated vaccine. Background Art

[0002] Riemerella anatipestifer (RA) infection is a highly pathogenic, contagious disease of many bird species, including ducks, geese, and turkeys. The disease is more common in ducklings aged 10-35 days, with an incidence rate of more than 90% and a mortality rate of 5%-75%. It is one of the major infectious diseases affecting the duck farming industry.

[0003] The efficacy evaluation of the existing Riemerella anatipestifer inactivated vaccine relies on traditional animal experiments, which observe the clinical manifestations, antibody production and survival rate of ducks after vaccination with different doses. This method has the following defects:

[0004] Long experimental cycle: Traditional animal experiments require long-term monitoring and observation, which is time-consuming.

[0005] Limited sample size: The experimental sample size is limited, making it difficult to conduct large-scale data analysis, which may lead to data bias.

[0006] Delayed effect evaluation: The effect can only be observed after vaccination. If the vaccine is not effective, a lot of time and resources will be wasted.

[0007] Therefore, a method and system for simulating the efficacy of an inactivated vaccine of Riemerella anatipestifer serotype 2 was proposed. Summary of the invention

[0008] The purpose of the present invention is to provide a method and system for simulating the efficacy of an inactivated vaccine of Riemerella anatipestifer serotype 2, which helps determine the dosage, immunization cycle and effect of the vaccine by accurately simulating the immune response, antibody production and protective efficacy of the vaccine in ducks. This solution is different from the prior art, adopts a more intelligent computational model and experimental method, and combines a data-driven vaccine efficacy simulation system, which can effectively improve the efficiency and scientificity of vaccine research and development to solve the problems raised in the above background technology.

[0009] To achieve the above object, the present invention provides the following technical solution: a method for simulating the efficacy of an inactivated vaccine of Riemerella anatipestifer serotype 2, comprising the following steps:

[0010] S1. Input of vaccine doses and vaccination schedules, input information on high, medium, and low doses of inactivated vaccines, as well as single-dose and booster vaccination schedules;

[0011] S2, immune response simulation model, through the biodynamic model, simulates the immune response of ducks after vaccination. The model is based on the mechanism of vaccine stimulating the immune system and is divided into two parts: the primary immune response and the subsequent immune memory response;

[0012] S3, antibody titer curve simulation, based on the relationship between vaccine dose and immune response, simulates the generation and changes of antibody levels in serum, and combines immunological principles to predict the duration of antibody titer;

[0013] S4. Protection effect simulation: predicting the protection effect through antibody levels, simulating the protection efficacy of vaccines in different time periods based on the antibody protection threshold of immunological research;

[0014] S5. Infection simulation: in a simulated infection environment, the protective effect of the vaccine is evaluated by calculating the immune response and survival rate of ducks after exposure to pathogens;

[0015] S6. Simulation results output, including antibody titer curve, vaccine protection efficacy, optimal immunization cycle, and protection effects of different doses.

[0016] Preferably, in the antibody titer curve simulation step, the antibody generation and decay formula is:

[0017] A(t)=A0(1-e -αt ) -βt

[0018] Where: A(t) is the antibody concentration at time t, A0 is the maximum antibody concentration, α is the antibody generation rate constant, and β is the antibody decay rate constant.

[0019] Preferably, the primary immune response and the memory immune response in the S2 immune response simulation model are modeled separately, and the activation process of T cells and B cells is combined, and a two-phase kinetic model is used to simulate the generation and decay of IgM and IgG respectively, so as to simulate the immune response more comprehensively.

[0020] Preferably, the gM generation and attenuation model:

[0021]

[0022] Among them: A IgM (t) is the IgM antibody titer at time t, k M,gen is the rate constant for the generation of IgM antibodies, k M,dec is the decay rate constant of IgM antibody, and S(t) is the stimulatory effect of the vaccine dose, which depends on the vaccination dose and time.

[0023] Preferably, the IgG generation and attenuation model:

[0024]

[0025] Among them: A IgG (t) is the IgG antibody titer at time t, k G,gen and k G,dec are the generation and decay rate constants of IgG, respectively.

[0026] Preferably, in the activation process of T cells and B cells, in the role of assisting T cells in the production of antibodies by B cells, the activation process of T cells can be described by the following formula:

[0027]

[0028] Where: T(t) is the number of activated T cells, α T is the T cell activation rate, β T The activation of T cells affects the antibody production of B cells through feedback, making the vaccine produce a more sustained immune effect.

[0029] Preferably, the vaccine is administered multiple times, such as primary and booster vaccinations, and each vaccination will produce new antibody effects based on the existing antibody titer;

[0030] Formula for antibody effect after multiple vaccinations:

[0031]

[0032] Among them: A dose (tt i ) is the generation and decay curve of antibodies after the i-th vaccination, -t i is the time of the i-th vaccination, and n is the total number of vaccinations. Each vaccination will stimulate the immune system to produce new antibodies. The cumulative effect makes the antibody titer increase gradually and last longer.

[0033] Preferably, the antibody titer is not only proportional to the vaccination dose, but also has a nonlinear relationship. When the dose is low, the antibody production rate increases rapidly with the increase of the dose; and when the dose is high, the antibody production rate tends to be saturated;

[0034] Non-linear antibody generation formula:

[0035]

[0036] Among them: A0 is the maximum antibody titer, k gen is the antibody generation rate constant, D is the vaccine dose, K D is the half-saturation constant.

[0037] Preferably, the persistence of the antibody is affected by differences in individual immune system responses, vaccine quality, and immune escape factors of pathogens. The antibody decay rate is adjusted individually according to experimental data to improve prediction accuracy.

[0038] Exponential decay model of antibody decline:

[0039] A(t)=A0·e -βt

[0040] Where: A(t) is the antibody concentration at time t, β is the antibody decay rate, which is adjusted according to individual and environmental conditions.

[0041] The efficacy simulation system of the inactivated vaccine of Riemerella anatipestifer serotype 2 includes a data input module: input vaccine dose, duck flock age, vaccination scheme, and environmental factors such as pathogen exposure probability;

[0042] Immune response simulation module: Based on the biokinetic model, it simulates the antibody generation and disappearance process after vaccination, and uses a differential equation model to describe the immune response and changes in antibody levels;

[0043] Infection exposure simulation module: Combined with the infection model, it simulates the protective effect of ducks exposed to Riemerella after vaccination, and simulates the impact of factors such as pathogen exposure probability and vaccine effective protection time on the survival rate of ducks;

[0044] Data analysis and visualization module: Generates visualization results from simulated data, including antibody production curves, protection efficacy time charts, generates experimental reports, and provides recommendations on optimal vaccine dosage and immunization cycle.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] Intelligent simulation: Different from the traditional method that relies on a large number of animal experiments, this method predicts vaccine efficacy through simulation models, reducing experimental cycles and costs.

[0047] Automated system: Introducing automated data input, simulation and output processes to reduce manual intervention and improve experimental efficiency and accuracy.

[0048] Biokinetic model: Modeling the immune response through complex mathematical models makes the evaluation of vaccine effectiveness more accurate.

[0049] The designed method and system for simulating the efficacy of the inactivated Riemerella anatipestifer vaccine serotype 2 adopts an intelligent biokinetic model and an automated system, which can efficiently and accurately evaluate the efficacy of the vaccine and provide optimized vaccination plans and dosage recommendations. It is significantly different from existing technologies and improves the efficiency and scientificity of vaccine research and development. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 The flowchart of the efficacy simulation method of the serotype 2 Riemerella anatipestifer inactivated vaccine of the present invention is as follows;

[0052] Figure 2 It is a block diagram of the efficacy simulation system of the serotype 2 Riemerella anatipestifer inactivated vaccine of the present invention;

[0053] Figure 3 This is a data table showing the effects of different doses of the vaccine of the present invention on antibody titers;

[0054] Figure 4 This is a data table showing the effect of the same immunization cycle on the protective efficacy of the vaccine of the present invention;

[0055] Figure 5 The following is a simulated data table showing the protective effect of the vaccine of the present invention under infection exposure. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] See also Figures 1 to 5 , the present invention provides a technical solution:

[0058] The method for simulating the efficacy of an inactivated vaccine of Riemerella anatipestifer serotype 2 comprises the following steps:

[0059] S1. Input of vaccine doses and vaccination schedules, input information on high, medium, and low doses of inactivated vaccines, as well as single-dose and booster vaccination schedules;

[0060] S2, immune response simulation model, through the biodynamic model, simulates the immune response of ducks after vaccination. The model is based on the mechanism of vaccine stimulating the immune system and is divided into two parts: the primary immune response and the subsequent immune memory response;

[0061] S3, antibody titer curve simulation, based on the relationship between vaccine dose and immune response, simulates the generation and changes of antibody levels in serum, and combines immunological principles to predict the duration of antibody titer;

[0062] S4. Protection effect simulation: predicting the protection effect through antibody levels, simulating the protection efficacy of vaccines in different time periods based on the antibody protection threshold of immunological research;

[0063] S5. Infection simulation: in a simulated infection environment, the protective effect of the vaccine is evaluated by calculating the immune response and survival rate of ducks after exposure to pathogens;

[0064] S6. Simulation results output, including antibody titer curve, vaccine protection efficacy, optimal immunization cycle, and protection effects of different doses.

[0065] Specifically, in the antibody titer curve simulation step, the antibody generation and decay formula is:

[0066] A(t)=A0(1-e -αt ) -βt

[0067] Where: A(t) is the antibody concentration at time t, A0 is the maximum antibody concentration, α is the antibody generation rate constant, and β is the antibody decay rate constant.

[0068] Specifically, in the S2 immune response simulation model, the primary immune response and the memory immune response are modeled separately, and the activation process of T cells and B cells is combined, and a two-phase kinetic model is used to simulate the generation and attenuation of IgM and IgG respectively, so as to simulate the immune response more comprehensively.

[0069] Specifically, the gM generation and decay model:

[0070]

[0071] Among them: A IgM (t) is the IgM antibody titer at time t, k M,gen is the rate constant for the generation of IgM antibodies, k M,dec is the decay rate constant of IgM antibody, and S(t) is the stimulatory effect of the vaccine dose, which depends on the vaccination dose and time.

[0072] Specifically, the IgG generation and attenuation model:

[0073]

[0074] Among them: A IgG (t) is the IgG antibody titer at time t, k G,gen and k G,decare the generation and decay rate constants of IgG, respectively.

[0075] Specifically, in the activation process of T cells and B cells, in the role of assisting T cells in the production of antibodies by B cells, the activation process of T cells can be described by the following formula:

[0076]

[0077] Where: T(t) is the number of activated T cells, α T is the T cell activation rate, β T The activation of T cells affects the antibody production of B cells through feedback, making the vaccine produce a more sustained immune effect.

[0078] Specifically, multiple vaccinations, such as primary and booster vaccinations, will each produce new antibody effects on the basis of existing antibody titers;

[0079] Formula for antibody effect after multiple vaccinations:

[0080]

[0081] Among them: A dose (tt i ) is the generation and decay curve of antibodies after the i-th vaccination, -t i is the time of the i-th vaccination, and n is the total number of vaccinations. Each vaccination will stimulate the immune system to produce new antibodies. The cumulative effect makes the antibody titer increase gradually and last longer.

[0082] Specifically, the antibody titer is not only proportional to the vaccination dose, but also has a nonlinear relationship. When the dose is low, the antibody production rate increases rapidly with the increase in dose; while at a high dose, the antibody production rate tends to saturation;

[0083] Non-linear antibody generation formula:

[0084]

[0085] Among them: A0 is the maximum antibody titer, k gen is the antibody generation rate constant, D is the vaccine dose, K D is the half-saturation constant.

[0086] Specifically, the persistence of the antibody is affected by differences in individual immune system responses, vaccine quality, and immune escape factors of pathogens. The antibody decay rate is adjusted individually based on experimental data to improve prediction accuracy.

[0087] Exponential decay model of antibody decline:

[0088] A(t)=A0·e-βt

[0089] Where: A(t) is the antibody concentration at time t, β is the antibody decay rate, which is adjusted according to individual and environmental conditions.

[0090] Threshold model of vaccine protection effect

[0091] The optimized protection effect simulation model is based on the **threshold model** of antibody titer and protection efficacy. When the antibody titer A(t) exceeds a specific threshold A threshold When the virus is present, the vaccine is effective in preventing infection; otherwise, it provides no protection.

[0092] Protection effect determination formula:

[0093]

[0094] in:

[0095] P(t) is the protection effectiveness at time t (1 for effective protection, 0 for ineffective protection).

[0096] Infection exposure model

[0097] In order to simulate the protective efficacy of the vaccine under different exposure conditions, the optimized model introduced the **infection exposure model**, considering the protective effect of ducks exposed to pathogens after vaccination. The effective protection time of the vaccine was evaluated by simulating the survival rate after exposure to pathogens at different time points.

[0098] Infection exposure probability model:

[0099] I(t)=P exposure ·(1-e -γA(t) )

[0100] Where: is the infection probability at time t, P exposure is the probability of exposure to pathogens, and γ is the neutralizing effect of antibodies on pathogens.

[0101] Through this model, the infection risk under different exposure conditions can be dynamically simulated, and combined with the antibody titer, the protective effect of the vaccine in different time periods can be predicted.

[0102] Long-term protection efficacy evaluation

[0103] The optimized model adds a long-term protection efficacy evaluation mechanism, combines the antibody titer curve and the pathogen exposure model, predicts the vaccine's protection efficacy at different time points, and outputs the protection period. For example, the system can calculate the time point when the vaccine's protection efficacy drops below the safety threshold based on the attenuation of the antibody titer, helping to determine the time for booster immunization.

[0104] The efficacy simulation system of the inactivated vaccine of Riemerella anatipestifer serotype 2 includes a data input module: input vaccine dose, duck flock age, vaccination scheme, and environmental factors such as pathogen exposure probability;

[0105] Immune response simulation module: Based on the biokinetic model, it simulates the antibody generation and disappearance process after vaccination, and uses a differential equation model to describe the immune response and changes in antibody levels;

[0106] Infection exposure simulation module: Combined with the infection model, it simulates the protective effect of ducks exposed to Riemerella after vaccination, and simulates the impact of factors such as pathogen exposure probability and vaccine effective protection time on the survival rate of ducks;

[0107] Data analysis and visualization module: Generates visualization results from simulated data, including antibody production curves, protection efficacy time charts, generates experimental reports, and provides recommendations on optimal vaccine dosage and immunization cycle.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for simulating the efficacy of an inactivated vaccine of Riemerella anatipestifer serotype 2, characterized in that: The steps include: S1. Input of vaccine doses and vaccination schedules, input information on high, medium, and low doses of inactivated vaccines, as well as single-dose and booster vaccination schedules; S2, immune response simulation model, through the biodynamic model, simulates the immune response of ducks after vaccination. The model is based on the mechanism of vaccine stimulating the immune system and is divided into two parts: the primary immune response and the subsequent immune memory response; S3, antibody titer curve simulation, based on the relationship between vaccine dose and immune response, simulates the generation and changes of antibody levels in serum, and combines immunological principles to predict the duration of antibody titer; S4. Protection effect simulation: predicting the protection effect through antibody levels, simulating the protection efficacy of vaccines in different time periods based on the antibody protection threshold of immunological research; S5. Infection simulation: in a simulated infection environment, the protective effect of the vaccine is evaluated by calculating the immune response and survival rate of ducks after exposure to pathogens; S6. Simulation results output, including antibody titer curve, vaccine protection efficacy, optimal immunization cycle, and protection effects of different doses.

2. The method for simulating the efficacy of the inactivated vaccine of Riemerella anatipestifer serotype 2 according to claim 1, characterized in that: In the antibody titer curve simulation step, the antibody generation and decay formula is: A(t)=A0(1-e -αt )And -βt Where: A(t) is the antibody concentration at time t, A0 is the maximum antibody concentration, α is the antibody generation rate constant, and β is the antibody decay rate constant.

3. The method for simulating the efficacy of the inactivated vaccine of Riemerella anatipestifer serotype 2 according to claim 2, characterized in that: In the S2 immune response simulation model, the primary immune response and the memory immune response are modeled separately, and the activation process of T cells and B cells is combined, and a two-phase kinetic model is used to simulate the generation and decay of IgM and IgG respectively, so as to simulate the immune response more comprehensively.

4. The method for simulating the efficacy of the inactivated vaccine of Riemerella anatipestifer serotype 2 according to claim 3, characterized in that: The gM generation and decay model: Among them: A IgM (t) is the IgM antibody titer at time t, k M,gen is the rate constant for the generation of IgM antibodies, k M,dec is the decay rate constant of IgM antibody, and S(t) is the stimulatory effect of the vaccine dose, which depends on the vaccination dose and time.

5. The method for simulating the efficacy of the inactivated vaccine of Riemerella anatipestifer serotype 2 according to claim 4, characterized in that: The IgG generation and decay model: Among them: A IgG (t) is the IgG antibody titer at time t, k G,gen and k G,dec are the generation and decay rate constants of IgG, respectively.

6. The method for simulating the efficacy of the serotype 2 Riemerella anatipestifer inactivated vaccine according to claim 5, characterized in that: In the activation process of T cells and B cells, the role of T cells in assisting B cells in producing antibodies. The activation process of T cells can be described by the following formula: Where: T(t) is the number of activated T cells, α T is the T cell activation rate, β T The activation of T cells affects the antibody production of B cells through feedback, making the vaccine produce a more sustained immune effect.

7. The method for simulating the efficacy of the serotype 2 Riemerella anatipestifer inactivated vaccine according to claim 6, characterized in that: Multiple vaccinations, such as primary and booster vaccinations, will produce new antibody effects based on existing antibody titers each time; Formula for antibody effect after multiple vaccinations: Among them: A dose (tt i ) is the generation and decay curve of antibodies after the i-th vaccination, -t i is the time of the i-th vaccination, and n is the total number of vaccinations. Each vaccination will stimulate the immune system to produce new antibodies. The cumulative effect makes the antibody titer increase gradually and last longer.

8. The method for simulating the efficacy of the inactivated vaccine of Riemerella anatipestifer serotype 2 according to claim 7, characterized in that: The antibody titer is not only proportional to the vaccination dose, but also has a nonlinear relationship. When the dose is low, the antibody production rate increases rapidly with the increase of the dose; while at a high dose, the antibody production rate tends to be saturated; Non-linear antibody generation formula: Among them: A0 is the maximum antibody titer, k gen is the antibody generation rate constant, D is the vaccine dose, K D is the half-saturation constant.

9. The method for simulating the efficacy of the serotype 2 Riemerella anatipestifer inactivated vaccine according to claim 8, characterized in that: The persistence of the antibody is affected by differences in individual immune system responses, vaccine quality, and immune escape factors of pathogens. The antibody decay rate is adjusted individually based on experimental data to improve prediction accuracy. Exponential decay model of antibody decline: A(t)=A0·e -βt Where: A(t) is the antibody concentration at time t, β is the antibody decay rate, which is adjusted according to individual and environmental conditions.

10. The efficacy simulation system of the inactivated vaccine of Riemerella anatipestifer serotype 2 according to any one of claims 1 to 9, characterized in that: Includes data input module: input vaccine dose, duck flock age, vaccination schedule, environmental factors, such as pathogen exposure probability; Immune response simulation module: Based on the biokinetic model, it simulates the antibody generation and disappearance process after vaccination, and uses a differential equation model to describe the immune response and changes in antibody levels; Infection exposure simulation module: Combined with the infection model, it simulates the protective effect of ducks exposed to Riemerella after vaccination, and simulates the impact of factors such as pathogen exposure probability and vaccine effective protection time on the survival rate of ducks; Data analysis and visualization module: Generates visualization results from simulated data, including antibody production curves, protection efficacy time charts, generates experimental reports, and provides recommendations on optimal vaccine dosage and immunization cycle.

Images