["Oxford Bulletin of Economics and Statistics, Volume 88, Issue 3, Page 553-567, June 2026. ", "\nABSTRACT\nAccurately estimating the correlations among clinical trial outcomes is crucial for managing the risk of biopharmaceutical investment portfolios. We propose a novel algorithm for estimating correlations in large clinical trial datasets using a generalised estimating equations (GEE) framework. Our algorithm outperforms existing methods in both convergence speed and computational efficiency. Empirical analysis of over 25,000 clinical trials reveals a correlation of approximately 10% for trials within therapeutic areas and up to 40% for trials sharing the same phase or mechanism hierarchy. Trials targeting the same disease show slightly negative correlations, suggesting a first‐mover advantage. Our approach offers a scalable method to estimate correlations within large clinical trial datasets.\n"]