Understanding disease mechanisms is crucial for drug discovery, necessitating the integration of diverse and multi-modal data. Here, the authors develop iPANDDA, a network-based computational pipeline that integrates multi-modal data to predict drug targets for SOX2-dependent lung squamous cell carcinoma, identifying and validating key targets like AKT and mTOR complexes.

In this interview, Namshik Han explains the role quantum algorithms can play in drug discovery research and what makes a successful startup.