The value of AI-driven Computational Modeling for BioTechs

Online
13:00 bis 14:00
Online
Digitization and Artificial Intelligence (AI) are increasingly finding their way into our everyday lives. The pharmaceutical industry is also using AI to optimize drug and therapy development. The possible uses and opportunities of AI extend across the entire value chain of the pharmaceutical industry: Starting with more precise prognoses in drug research, through lower development costs to more efficient processes in the laboratory and production.

 

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)

 

Registrationhttps://schrodinger.zoom.us/webinar/register/2016207468277/WN_NDGjWtHCRjGbBcQLyNdUAg