Mydecine Innovations Group announced they have completed a target-based model of the classic psychedelic serotonin receptor 5-HT2A for use in their AI-driven drug discovery program. The new model will allow them to expeditiously screen billions of structures to determine which novel compounds are most likely to increase binding affinity, enabling them to continue creating improved second and third generation psychedelic molecules for medical use. By centering their drug discovery efforts around artificial intelligence (AI) and machine learning (ML), Mydecine is positioned to discover drug enhancements more cost effectively and more efficiently than their competitors.

Using AI technology is relatively new in the drug development space and its applications are continuously expanding. The goal of this technology is to eliminate, or drastically reduce, the manual efforts companies typically undergo to identify possible drug improvements. By filtering the drug candidates with AI, the Company is inherently making their investments in later stage drug development more valuable by eliminating potential candidates that are likely to fail early on in the process.

Without AI and ML, based on their hypotheses, companies have to manually synthesize each molecule and individually test the likelihood of a successful binding agent. This process can consume enormous amounts of time and money; therefore, efficiently eliminating candidates likely to fail in preference for candidates that are more promising is extremely valuable.