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 is an Irish company and sister company of Vertebrate Antibodies Ltd (VAL), an emerging biotech company established and incubated by the University of Aberdeen.

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.


Dr Ayham Alnabulsi

Chief Executive Officer, Director, Co-founder

Strategic visionary and entrepreneur with extensive knowledge in medical genetics, immunology and mathematics.

Dr Abdo Alnabulsi

Chief Operating Officer

Abdo Alnabulsi brings a unique combination of scientific expertise in immunoassays development and validations, cancer pathology and programming.

Dr Tiehui Wang

Chief Data Scientist

Dr Tiehui Wang is a leading immunologist with a research focus on the regulation mechanisms of the immune system.

Loredana Jerdea

Chief Financial Officer

Oliver Meister

Legal Director

Oliver is a UK qualified solicitor who represents the main shareholder in AI Biologics and assists the company in legal and regulatory matters.

Catherine Bedford

Office Manager

Marius Ionescu

AI and Software Engineering

Marius Ionescu has 20 years’ experience in computer related technologies spanning from operating systems, telecommunication, to software engineering.

Florentina Mihaila


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.

Dr Wei Pang

Dr Wei Pang (Associate Professor, Heriot-Watt University) is a computer scientist who is specialised in Bio-inspired Computing, Machine Learning, and Explainable AI.


Prof Graeme Murray

Professor Murray is Regius Professor of Pathology and academic clinical speciality lead for Pathology at the University of Aberdeen.

Prof Chris Secombes

Professor Secombes (Emeritus Regius Chair of Natural History) is a renowned immunologist with a wealth of expertise on veterinary immunology and immunopathology.

Breakthrough Solutions

Diagnostic Solutions

AiBIOLOGICS offers in silico modelling to accelerate discovery and development of serology-based assays that will transform the sector, improving assay performance, reducing cost and lead production time.

Through identification of immunodominant sequences, expression on our peptide display technology and leveraging of AI technologies, we can create breakthrough solutions for diagnostic discovery.

Vaccine Candidates

AiBIOLOGICS software will accelerate the development of vaccines (e.g. subunit & peptide vaccines) subsequently offering significant safety advantages.

The software can also identify immune components that will support mucosal vaccines design and reduce allergy associated effects.

Immunogenicity Mapping

EpitopePredikt provides in silico screening for potential immunogenic signatures of biological drug candidates for clinical evaluations.

We can identify immunogenic profiles for the lead candidates to carry forward from preclinical and clinical trials, thus reducing the risk of failure due to immunogenicity issues and improving overall safety.

“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.”

Do you have a vaccine, diagnostic or antibody discovery project or are seeking immunogenicity solutions ? Please contact us for details.


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.

Learn more about the technology

Deep Learning algorithms

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 techniques

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.

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