EpitopePredikt has been utilised in NorthTick EU project to improve the sensitivity and specificity of existing serological testing methods.read more
AiBIOLOGICS has developed an Artificial Intelligence software with deep learning algorithms that significantly expedites and refines antibody discovery, diagnostic development, vaccine design and immunogenicity mapping.
AiBIOLOGICS and VAL work in synergy. Immunological data generated by VAL are used to create new AI models by AiBIOLOGICS. In turn, AI algorithms created by AiBIOLOGICS are validated in VAL laboratories.
AiBIOLOGICS through its various artificial intelligence and deep learning algorithms has been created to accelerate biotherapeutic, diagnostic and vaccine discovery as well as to offer immunogenicity solutions.
The company was established in Dublin due to the rich biotech ecosystem present in Ireland from where it intends to develop partnerships to drive biological discovery platforms.
Marius Ionescu has 20 years’ experience in computer related technologies spanning from operating systems, telecommunication, to software engineering.
Florentina Mihaila, is a seasoned administrative director experienced in coordinating financial, legal, and HR teams in a number of international organisations over the past 20 years.
“Our unique technology uses artificial intelligence and deep learning models to provide breakthrough solutions that will revolutionise the fields of diagnostics, vaccine designs and therapeutics evaluation.”
Our EpitopePredikt technology is a game-changer for diagnostic, antibody and vaccine discovery providing higher performance capacity with adaptability, significant reduction in manufacturing cost and lead times.
EpitopePredikt’s deep learning will structure the algorithms in layers in order to create an “artificial neural network” that can provide intelligent solutions for biological design.
The combination of AiBIOLOGICS recombinant epitopes with our proprietary peptide display platform ensures highly sensitive and specific detection of antibodies from your sample. This discovery and display platform is adaptable to any disease, in any organism.
Deep Learning is a branch of machine learning, a subfield of Artificial Intelligence. It involves constructing and training very “deep” neural networks for problem solving, such as making predictions and revealing hidden patterns from very complex problems.
Deep learning is one major reason for the rise of AI over the last 10 years, and it has become a main driving force for AI to be recognised and applied to various problems.
Deep learning is suitable capturing very complex spatial and temporal patterns from a huge amount of data, but recently deep learning has also been applied to those problems in which only sparse data are available.
Evolutionary computation is a subfield of artificial intelligence and is inspired by evolution in biology. In an evolutionary algorithm, there is a population of potential solutions for a real-world problem, and the population will undergo several iterations, each of which involves the applications of evolutionary operators to each individual in the population, such as selection, mutation, and cross-over so that the individuals improve their fitness (i.e., the quality of the solution) over time. Eventually a satisfactory solution will be generated.
Evolutionary computation as a generic problem solver can be applied to a wide range of optimisation problems, from optimising the job schedules, logistics, to optimising the parameters of existing AI models.
Learn more about our current projects, company news and past use cases of our technology.
In 2020, AiBiologics joined forces with leading scientists and clinicians from the University of Aberdeen, NHS Grampian and it’s partner company Verte
Vertebrate Antibodies will utilise its proprietary AI and recombinant technologies to tackle Covid-19. Vertebrate Antibodies Ltd (VAL) is joining forc
EpitopePredikt has been utilised in NorthTick EU project to improve the sensitivity and specificity of existing serological testing methods. Borrelia