Adverse drug reactions (ADRs) endanger patients' health and pose a challenge to drug development and medical care. Predicting ADRs still fails in many cases due to their idiosyncrasy and limited assay or cross-species translatability. Findings from diverse sources need to be contextualised with individual patient conditions, e.g., diseases, genotypes, or co-medications, to enable a systemic understanding and reliable predictions of ADRs. However, experiments mimicking realistic patient scenarios are often expensive, infeasible, and insufficient. Here, mechanistic in silico models have emerged...