Project ALPHA (Analytics for Life-sciences Professionals and Healthcare Advocates) is an initiative of the MIT Laboratory for Financial Engineering with the main objective of providing more timely and accurate estimates of the risks of clinical trials and related metrics (see “Related Research” below). By providing greater transparency to drug developers, investors, policymakers, and patients regarding the risks of biomedical R&D, we hope to allow all stakeholders to manage their resources more efficiently, leading to fewer failures, faster drug approval times, a lower cost of capital, and more funding for developing new therapies.
Visit https://projectalpha.mit.edu for more information.
- Machine learning with statistical imputation for predicting drug approvals (2019), Andrew W. Lo, Kien Wei Siah, and Chi Heem Wong, Harvard Data Science Review, https://doi.org/10.1162/99608f92.5c5f0525.
- What are the chances of getting a cancer drug approved? (2019), Chi Heem Wong, Kien Wei Siah, and Andrew W. Lo, DIA Global Forum.
- Estimation of clinical trial success rates and related parameters (2019), Chi Heem Wong, Kien Wei Siah, and Andrew W. Lo, Biostatistics 20, 273-286.