Artificial intelligence in pharmaceuticals is no longer a pipe dream. AI-designed treatments for conditions such as lymph cancer, inflammatory diseases, and motor neurone disease are now in human trials, thanks to advances in technology. AI has the potential to shorten the time it takes to develop new medicines and more efficiently identify new drug molecules. This will allow drugmakers to pocket billions of dollars while also providing patients with more new, innovative drugs at a faster rate than ever before. However, there is one significant barrier to overcome: data availability. AI systems will not produce the most accurate results unless they have access to high-quality, extensive data. This is a significant barrier for smaller businesses. Despite the promising results, there is a lingering fear that AI will fall short of expectations. At the moment, all eyes are on whether AI-designed medicines will be safe for people, have the desired effect on disease, and meet the rigorous regulatory standards required to be approved for human use. A better understanding of which data is predictive and meaningful in which disease context is required to help move the industry forward, and the technology must be capable of designing drugs at scale.

Source: ZDNet (link)
Images: MidJourney, Prompts by Lewis Farrell

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