The seminar explores the integration of advanced AI and life sciences, from theory to real-world biomedical applications within multidisciplinary ecosystems. Key topics include generative and multimodal AI, focusing on challenges such as data fusion, generalisation, interpretability, and regulatory compliance. The session also covers medical AI pipelines, from biomedical data to clinical decision support, and the role of bioinformatics in enabling precision medicine through the analysis of complex genomic data. AI-driven innovation in drug development is addressed, highlighting applications in drug screening, repurposing, and advanced therapies. The seminar also introduces biologically inspired models based on in vitro neural networks, offering interpretable and energy-efficient alternatives to traditional AI. Finally, the importance of collaboration across academia, healthcare, and industry is emphasised, alongside the need for interoperable infrastructures and robust data governance. Overall, the seminar underlines the importance of integrated approaches to effectively translate AI into clinical and biotechnological practice.