Simulate immune responses to vaccines with C-IMMSIM

Because of the diversity of the immune repertoires, it is very challenging to predict the efficacy of a vaccine to properly stimulate all components of the immune system and ultimately protect against infectious diseases, that is it’s immunogenicity.

To aid researchers in the design and set up of their vaccination/infection protocols, Dr. Filippo Castiglione and colleagues from the Institute for Applied Computing in Rome have developed C-IMMSIM. Here, he talks about the features and benefits of his tool.

A novel and free tool to perform in silico experiments about vaccinations and/or infections

To date, this is the only simulation tool for the immune response which combines epitope/peptide prediction algorithms with agent-based methodology to predict the follow-up of virtual infection experiments.

It represents the immune system in its most fundamental universal requirements such as the concept of diversity in all specific repertoires (the model is poly-clonal), the use of stochasticity actions in cell meeting and cooperation, the definition of an affinity potential on the bases of amino-acid avidity, the concept of clone division and immune memory (i.e., the clonal selection theory), specific controls of innate and adaptive immunity to avoid self-reactions, the thymus selection, the concept of danger, and other things.

Overall architecture of the simulation tool

Predicting tailored responses to the antigen

The user can specify the antigen to be injected in terms of its constitutional protein primary structures, that is, the linear sequences or amino acids.  The model also allows a certain degree of “patient” specificity by indicating of the Major Histocompatibility Complexes (both class I and II).

The algorithm identifies the portions of the linear sequences composing the antigen that are likely to be seen by the immune system. In other words the algorithm detects the B-cell epitopes and the T-cell peptides assigning a score that is eventually used throughout the simulation to identify the immunogenic portion of the antigen.

Simulation of an immunization experiment

The user can choose to inject a vaccine, a bacterium or a virus. He can also combine those kinds of antigens to simulate, for instance, vaccination and challenge or combined infections by different pathogens. He can also choose the simulated volume and the time horizon.

The outcome is a detailed description of the epitopes and peptides used to mount the specific immune response and a series of plots showing time dependent cell counts and cytokines’ concentrations.

Since the web tool exports only a small fraction of the toggles that can be used to specify the characteristics of both antigen and immune system, the tool could appear somehow limited to some user. In this case one could contact the author (me) to start a collaboration on a specific well-reasoned scientific question.

Challenges to face

The scientific issue this simulation tool faces is to simulate the immune response to vaccination and to include elements of the immune system relevant to the issue of vaccine design (such as the use of specific adjuvants).

Another challenge is to use the simulator as an alternative to animal models to compare alternatives in vaccine formulations, to evidence strengths and weaknesses of this approach and to identify points of intervention to increase biological fidelity of the results.


The combination of genomic information and simulation of the dynamics of the immune system, in one single tool, can offer new perspectives for a better understanding of the immune system.