Author: Chin-Lin Chen, Ph.D / Data Scientist at Vizuro Key Takeaway Drug discovery has entered the era of big data. Every year, thousands of disease and normal samples are profiled — yet one critical bottleneck remains: identifying clinically meaningful target–marker gene pairs for new drug development . The core value of Apotek Path is for this purpose: Identify disease-relevant targets → Causal modeling reveals mechanistic gene interactions tailored to your disease contex

Why causal AI is becoming pharma’s next strategic differentiator — from target validation to clinical trials and real-world evidence. Visualizing the Ladder of Causation in Pharma: from seeing correlations, to doing interventions, to imagining counterfactuals — the foundation of causal AI in drug discovery. Introduction: The Limits of Correlation in Drug Discovery Drug discovery today generates unprecedented volumes of data. Omics, imaging, electronic health records, and real

Empowering Clinicians and General Populations with Actionable Insights Diabetes is one of the world’s fastest-growing health crises,...