The value of AI-driven Computational Modeling for BioTechsOnline
In this webinar we will focus on useful computational applications for BioTech companies in the development of new large and small molecule therapies. Showcasing a comparison of powerful physics-based methods vs. wet lab techniques as well as on advantageous employments of machine/deep learning for molecular designs. The presentation will also highlight the significance of digitization and how it can transform the recent drug discovery working environment.
Furthermore, we will give an outlook on computational modeling becoming a main methodology in the drug discovery process and where we imagine it to be in the next decade.
In this webinar you will:
- Learn about physics-based methods for large as well as small molecule workflows (wet lab vs dry lab)
- Understand how computational methods are becoming more powerful and the role of AI in Drug Discovery
- See the impact of digitalization on an international and interdisciplinary workplace
Info Speaker: Dr. David Siebert and Dr. Dan Cannon
Target Audience: BioTech companies working on the development of small and large molecules (Proteins, antibodies and enzymes)