What We Do

At mAIbe, we specialize in developing monoclonal antibodies (mAbs) targeting endemic viruses, such as HIV and RSV, as well as pathogens with pandemic potential. The list of viruses capable of triggering the next pandemic has expanded significantly, now including pathogens such as influenza A virus, dengue virus, and monkeypox virus. Historically and currently, vaccines have proven essential in mitigating the spread and severity of many viral infections. However, the high variability of certain viruses and the clinical conditions in patients with compromised immune responses underscore the critical need for passive immunization strategies as part of a comprehensive anti-infective approach. Monoclonal antibodies offer attractive therapeutic and prophylactic options against viral infections due to their high specificity and ability to enhance immune responses. Additionally, advancements in antibody engineering have facilitated improvements in their effector functions and extended half-lives. Recent progress in structural biology has enabled the identification and targeting of vulnerable regions in viral proteins, resulting in the selection and optimization of potent neutralizing antibodies. These insights are not only pivotal for mAb development but can also guide improvements and redesign efforts for more effective vaccines.

WE at mAIbe focus on Monoclonal Antibodies against MDR bacteria Antimicrobials are a cornerstone of modern medicine that allow for tremendous increases in life expectancy and quality of humanity. However, resistance to antimicrobials is challenging this development and is becoming an ever-increasing problem that is estimated to surpass the combined deaths of cancer and heart disease by the year 2050, with an estimated 10 million deaths per year. Monoclonal Antibodies designed against MDR bacteria are becoming an important therapeutic tool. Indeed, MoAbs characteristics allow for the targeting of only the bacteria of interest, not affecting the commensal bacteria of the host, while the development of resistance is extremely unlikely. Moreover, MoAbs -based therapies have the advantage over vaccines of having an immediate response, allowing their use when the patient is already suffering from infection. The use of AI-driven MoAbs will allow accurate selection of MDR bacteria target sites, thus improving affinity and lowering required doses and cost.

We design smarter therapeutics by embedding key properties—such as potency, half-life, and developability—right from the start of the discovery process. Using innovative computational tools, we reduce the need for extensive lab testing, focusing only on the most promising drug candidates. This fail-fast approach helps eliminate unsuitable molecules early, making the development process faster, more efficient, and less wasteful. Fewer experiments mean less waste, lower costs, and a smaller environmental footprint. Additionally, by optimizing drug properties, we can achieve the same therapeutic effect with lower doses and less frequent administration, improving both accessibility and patient experience. Committed to the Refine, Reduce, Replace principles (3Rs), we also limit reliance on animal testing, ensuring a more ethical and sustainable approach to drug development.

Our innovative approach uses artificial intelligence to transform how we design monoclonal antibodies, powerful tools for treating infectious diseases. We quickly generate and test countless antibody variations, finding those best suited to precisely target specific disease markers. Using advanced AI methods, we predict and optimize how antibodies attach to their targets, significantly boosting their effectiveness. We also use AI-driven computer simulations to improve antibody strength and stability, ensuring they perform reliably in real-world conditions. This approach dramatically speeds up the discovery process, reduces reliance on expensive lab experiments, and makes development faster and more cost-effective. Our streamlined method combines the predictive power of AI with detailed biological insights to create antibodies that are not only highly effective but also safer and easier to produce.

mAIbe’s operative model

The Dynamic Developing Network (DDN) is a business model derived from the computer science context. It refers to a network of entities that evolves over time, where changes in its elements, including its vertices and edges, can be observed. The DDN operative model applied to the biopharmaceutical sector, brings significant cost and time benefits in drug discovery and development. mAIbe’s DDN is an interconnected network of entities working on shared projects under clear objectives, contracts and agendas. The network includes geographically dispersed SMEs, collaborating like departments of a multinational biopharmaceutical company. DDNs enhance efficiency, sustainability and competitiveness in the pharmaceutical sector by managing risks and speeding up technology and product development.