AI in Action: Almirall, Barcelona Supercomputing Center, and Nostrum Biodiscovery Seek New Dermatologic Therapies via AI

December 5, 2023

The partnership aims to improve the design of protein-protein modulators through Artificial Intelligence to identify new therapeutic approaches for the treatment of skin diseases.

Almirall S.A. (BME: ALM), Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC-CNS) and Nostrum Biodiscovery are joining forces to explore artificial intelligence (AI) and machine learning (ML) generative approaches to design new protein-protein modulators for dermatological diseases. 

The collaboration, named ARTIBAND, will extend over a three-year period. Initially, the technology will be developed and trained with data on the public domain. In a second phase, it will be further optimized and applied to the discovery of new protein-protein modulators. The project received funding from the Spanish Ministry of Science and Innovation as part of the EU-funded Recovery, Transformation and Resilience Plan. 

"Applying AI to protein-protein modulator design not only discovers new therapeutic approaches but also fundamentally reshapes how we tackle and solve dermatological challenges,” says Francesc Fernández, Almirall’s Data Science Director, in a news release. “This endeavor represents a bold step forward in our commitment to improving lives through groundbreaking research and innovation.”

Almirall and Barcelona Supercomputing Center (BSC) have been collaborating since 2018 in the research program SilicoDerm, a project focused on computational drug design applied to dermatological therapeutic targets. Silicoderm has been the starting point of AI-based tools for drug discovery. 

The application of generative artificial intelligence methods in the pharmaceutical sector is at an early stage but has great potential. One of the most promising areas of artificial intelligence and machine learning is generative chemical modelling. AI platforms are first trained with a huge amount of chemical data for an algorithm to "learn the chemical language." Once this is done, generative algorithms can propose new chemical materials based on the learned language model. In this way, the generative model proposes compounds that are different and could be complementary to those found in compound libraries and which are biased on demand.

In November 2023, Almirall announced its first collaboration in the field of AI-generated medicines

Facebook Comments


We’re glad to see you’re enjoying PracticalDermatology…
but how about a more personalized experience?

Register for free