European Epidemiological Forum

The life science industry is discovering the power of artificial intelligence (AI) and has started leveraging it in various aspects of research and development.

Different techniques and machine learning (ML) algorithms, including natural language processing, have emerged and are helping in gathering, analysing and even interpreting the huge data arising out of RWE databases. Similarly, Predictive analytics are a new reality and can change the way we discover and market new drugs.

Indeed, up to a recent past, observational research tools were, in the great majority, simple palliatives to the ones used in randomized clinical trials, trying to accommodate the lack of rigor and the many biases of observational data. For the first time in history, newly developed observational research techniques and tools are unique to big data and do not necessarily overlap with the traditional statistical approaches used in pivotal registrations trials.

The objective of this online conference is to familiarize the audience with the new capabilities that are being made available in the field of artificial intelligence and machine learning in relation to its application to real world data.
Beyond the hype, EPI Forum will address the benefits and limitations of this new approach and discuss how it can complement traditional approach to observational studies.
Understanding the scope and depth of AI and machine learning is important in the current environment. Speakers with experience in AI/ML will share insights and illustrate the subject with examples and demonstrations.

The EPI Forum Scientific Board

Christian Agboton - Sr Global Brand Medical Director at Takeda
Maurille Feudjo Tepie - Observational Research Director at Amgen

is inviting you to this unique event, where you will be able to understand how AI/ML can complement or in some cases increase the value of current approaches using real world data.

Who should attend?
The conference is addressed to professionals with an interest in drug development, healthcare decision making, academia and healthcare research, belonging to department such as: Medical Affairs, R&D, HTA/Market access, Medical Informatics, Clinical Operations, Regulatory Affairs, Pharmacovigilance, Biostatistics and Data Management from Pharmaceutical, Biotechnology and Medical Device companies, CROs, Universities/Hospitals, Academic Research, Patient Associations and Healthcare Organizations.