Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modeling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing.

Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies.

Who is this event intended for?: Statisticians, Data Scientists, Researchers, Physicians, etc. interested in quantitative decision making.

What is the benefit of attending?: Information on AI driven approaches in different applications in research and pharmaceutical development.

Brief event overview: Initially a brief introduction to AI will be given, followed by a presentation of various applications in medicinal product lifecycle. Several aspects will be discussed incl. performance, theoretical and practical conditions and also regulatory guidelines.