– IBM has partnered with Boehringer Ingelheim to use AI foundation models for antibody research.
– Antibody treatments are effective against various diseases and have fewer side effects compared to traditional treatments.
– The aim is to develop a foundational AI model to make the production of lifesaving treatments more scalable and efficient.
– The use of generative AI can help in the discovery of new antibodies by examining molecules that haven’t been previously explored.
– Generative AI can also remove unconscious biases and expand the number of potential applications for each discovery.
– The collaboration between IBM and Boehringer Ingelheim aims to overcome the challenges of lab-based antibody research and speed up the rate of potential discoveries.
IBM has announced a new collaboration with global research company Boehringer Ingelheim to use its AI foundation models to aid in the discovery of new antibody treatments.
Antibody treatments are the dominant weapon in the fight against a wide range of serious diseases, and produce far less side effects when compared to more traditional treatments.
It is hoped that by developing a foundational AI model for antibody research, the production of lifesaving treatments can become scalable and more efficient.
Generative AI for antibody discovery
Speaking at the launch event in IBM’s Zurich research lab, Alessandro Curioni, IBM Fellow, Vice President Europe and Africa and Director IBM Research Zurich, highlighted the potential benefits of foundational models beyond AI and quantum, stating that, “Foundation models can be used to tackle problems and data that are outside the language domain.”
One of the most significant challenges hindering the development of new antibody treatments is the lab based nature of antibody research. The successful development of a new antibody treatment requires controlled repetition, meaning that new treatments cannot be produced quickly enough, slowing down the rate of potential discoveries.
Therefore, IBM and Boehringer Ingelheim hope to scale the development of new antibodies by using generative AI to produce molecules that haven’t previously been examined, removing non-viable candidates and allowing researchers to focus on those that are more promising, greatly enhancing efficiency.
Furthermore, generative AI can help remove unconscious biases in the development of new antibodies by applying each candidate to a wide range of potential applications outside of an individual’s area of expertise, greatly improving not only the number of discoveries, but also the number of use cases for each discovery.
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AI Eclipse TLDR:
IBM has announced a collaboration with Boehringer Ingelheim to use AI foundation models to aid in the discovery of new antibody treatments. Antibody treatments are effective in fighting various diseases with fewer side effects compared to traditional treatments. The goal is to develop a foundational AI model for antibody research to make the production of lifesaving treatments more scalable and efficient. By using generative AI, new antibodies can be developed and molecules that haven’t been examined before can be identified, eliminating non-viable candidates and improving efficiency. Additionally, generative AI can help remove unconscious biases in antibody development by applying candidates to a wide range of potential applications, increasing the number of discoveries and use cases.