Inferon Life Sciences

Developing a successful vaccine takes an average of 15 years and over 800 million dollars. The largest share of that cost does not come from successful projects, but from candidates that fail along the way, often in Phase II or III clinical trials, when the cost of a single study already runs into tens of millions. The primary reason for these failures is not a lack of data, but the inability of current tools to predict how the human immune system will respond to a vaccine candidate before the first patient is enrolled.

Inferon Life Sciences is a spin-off of the Italian National Research Council (CNR) that addresses exactly this problem. Our computational platform simulates the human adaptive immune response in silico, providing pharmaceutical and biotech companies with structured, mechanistically grounded predictions of a vaccine candidate's immunogenicity before investing in in vitro, in vivo, or clinical trial studies.

What We Offer

Inferon's core service is the Vaccine Immunogenicity Predictor: a decision-support system for the pre-clinical phase, built around the C-IMMSIM software, one of the most scientifically validated and detailed agent-based models of the human immune response, developed by CNR researchers Filippo Castiglione and Massimo Bernaschi over more than two decades of research, and applied in European projects funded by IMI and Horizon Europe.

Clients can submit antigen sequences or vaccine candidates and receive structured predictive reports covering:

• Immunogenicity profiles: estimation of the expected immune response (humoral and cellular) to specific antigens or epitopes.

• Population coverage: simulation across virtual patient cohorts built from real-world epidemiological data, replicating the genetic and immunological heterogeneity of the target population, including HLA variability.

• Immunodominance and cross-reactivity: identification of dominant epitopes and assessment of unwanted cross-reactive responses.

• Dose, schedule, and adjuvant optimization: in silico comparison of different administration regimens to identify the optimal strategy before clinical studies.

A second product, Clinical Trial Candidates Ranking, is particularly relevant for companies already using AI tools for antigen selection that need a mechanistic validation layer to reduce the risk of failure at the most expensive stages of development.

• Clinical trial candidate ranking: comparative assessment of the probability of Phase II and III success for candidates identified by third-party AI pipelines.

Why Our Platform Is Different

Computational tools currently available on the market fall into two main categories: statistical and differential equation models (such as those offered by Certara) that fail to capture the dynamic complexity of the immune response, and AI tools that require enormous volumes of training data and do not provide insights in the biological mechanisms.

C-IMMSIM occupies a distinct space. It is a mechanistic agent-based model that simulates the cellular and molecular interactions of the adaptive immune system at the individual level, including T and B lymphocytes, dendritic cells, macrophages, cytokines, affinity maturation, and clonal selection. This architecture generates biologically interpretable predictions (not simple statistical correlations) and does so with significantly smaller volumes of experimental data than pure AI models require.

The platform also integrates AI-based immunoinformatics tools for epitope prediction and binding affinity scoring, and can incorporate single-cell RNA sequencing data to build personalised digital twins of individual patients, a relevant asset for companies working on personalised cancer immunotherapies or vaccines targeting specific populations.

Who We Work With

Inferon Lifesciences is looking to establish collaborations with mid-size pharmaceutical companies, late-stage biotechs, and AI companies in the life sciences sector seeking to integrate an immunological simulation layer into their development pipelines. We are also open to partnerships with CROs looking to expand their computational offering, and with academic or institutional consortia engaged in rare disease modelling or pandemic preparedness.

Our engagement model is flexible. We offer low-commitment pilot projects designed to validate the platform on a client-specific use case, as well as software licensing agreements and structured long-term collaborations for companies ready to integrate immune simulation into their pre-clinical development decisions.

The Team

Inferon Life Sciences is led by Emiliano Mancini (PhD in Computational Science with over a decade of entrepreneurial and IP valorisation experience across the Netherlands, Singapore, and Belgium), as well as by scientific founders Filippo Castiglione (CNR Research Director and a pioneer of agent-based modelling in biology) and Massimo Bernaschi (CNR Technology Director, four-time finalist for the Gordon Bell Prize in Supercomputing.