<ul><li>AI-driven predictions in Long COVID drug development utilize data integration capabilities to map symptom trajectories and identify potential drugs for trials.</li><li>AI has accelerated timelines in vaccine development and drug discovery, reducing traditional processes from years to months through epitope prediction and virtual screening.</li><li>Limitations and risks include data quality issues, algorithmic bias, regulatory gaps, and overstated efficacy claims, highlighting the need for high-quality datasets and validation.</li><li>AI applications have shown promising impacts in virtual drug screening, predictive phenotyping, and clinical trials optimization, but reliability concerns exist due to limited wet-lab validation and small training cohorts.</li><li>Collaborative efforts and adherence to FAIR data principles are crucial to enhancing the reliability of AI-driven predictions in Long COVID drug development.</li></ul>

Reliability of AI-driven predictions in guiding long COVID drug development

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