Aug 21, 2024
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6
min read
The race for the first AI-discovered medication to successfully reach patients is on!
With new and improved Generative AI models for drug discovery and development emerging in the past six months, the race is becoming far more competitive.
Currently, eleven AI-discovered drugs are in phase 2 clinical trials worldwide. It will be interesting to see who will be the first company to reach phase 3.
Powerful LLMs trained on biochemical data released in the past six months are now changing this landscape by allowing the whole biotech community to enter the race.
So why is Generative AI more powerful in drug discovery and development compared to previous AI models? There are four main reasons:
𝟏. 𝐆𝐞𝐧𝐀𝐈 𝐰𝐨𝐫𝐤𝐬 𝐰𝐞𝐥𝐥 𝐞𝐯𝐞𝐧 𝐨𝐧 𝐬𝐦𝐚𝐥𝐥 𝐝𝐚𝐭𝐚𝐬𝐞𝐭𝐬. Because it is pre-trained on vast amounts of data, it doesn't need a lot of data to fine-tune a model for a specific task.
𝟐. 𝐆𝐞𝐧𝐀𝐈 𝐢𝐬 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 (𝐎𝐛𝐯𝐢𝐨𝐮𝐬𝐥𝐲?!). These models are trained generatively and can be used to generate de-novo biochemical data, resulting in better-performing biological products.
𝟑. 𝐆𝐞𝐧𝐀𝐈 𝐨𝐮𝐭𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐬 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧𝐬 in most cases compared to previous AI paradigms used on biochemical data.
𝟒. 𝐆𝐞𝐧𝐀𝐈 𝐢𝐬 𝐄𝐱𝐩𝐥𝐚𝐢𝐧𝐚𝐛𝐥𝐞. Unlike previous AI models for biochemical data, which were black boxes, GenAI can be explained using the built-in attention mechanism.
For these reasons, using Generative AI allows companies to generate better-performing medications and to reduce the time to market in their discovery pipeline dramatically.
I predict that companies that will be early adopters of GenAI in their R&D pipelines will create a significant competitive advantage in the drug discovery race.
At Converge Bio, we create the computational platform allowing biotech and pharmaceutical companies to best integrate this revolutionary technology in every part of their R&D pipeline. Please feel free to contact me for more details.
