Multimodal data means combining different types of information—such as molecular structures, omics data, clinical trial designs and scientific texts—into a single analytical model. For non‑specialists, it is important to understand that mixing modalities can improve predictions but also complicates data quality, integration and interpretability, which directly affects trust in AI‑assisted trial or discovery tools.