FDA launches full-scale rollout of AI tools after successful pilot
Food and Drug Administration (FDA) - 08-May-2025Generative AI will be deployed across all FDA centres by mid-2025 to streamline scientific reviews
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Artificial intelligence (AI) is revolutionising healthcare and drug discovery, bringing unprecedented advancements to both fields.
In healthcare, AI is transforming medical imaging and diagnostics. By analysing X-rays, MRIs, and other scans, AI can detect conditions like tumours and fractures more quickly and accurately than ever before. This technology also extends to pathology, where AI can identify cancerous cells in tissue samples with remarkable precision.
Though the data scientists need to make sure they feed in the right data. For example, in a study designed to detect hip fractures, it turned out the AI was using the patient's age and particularly the imaging device model to make its prediction. This worked because portable scanners are only used then the patient is too immobile to get to a hospital - and this limitation turned out to be a bigger indicator than any details on the image itself.
In drug discovery, AI accelerates the process by predicting the structure and properties of new molecules, identifying potential drug candidates faster than traditional methods. AI helps repurpose existing drugs for new uses, reducing the time and cost of bringing new treatments to market. By predicting drug interactions and side effects, AI ensures safer medications for patients. In genomics and proteomics, AI analyses vast amounts of data to uncover new drug targets and understand disease mechanisms, paving the way for innovative treatments.
Additionally, AI plays a crucial role in biomarker discovery, which is essential for diagnosing diseases and monitoring treatment responses. Clinical trials also benefit from AI through better patient selection and real-time monitoring, making trials more efficient. And finally, AI is pivotal in predictive analytics, monitoring patients' data from wearable devices and electronic health records to predict and prevent health issues before they become critical.
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