Operational Experiences with Secure Multiparty Computation in Clinical Research

Abstract

International medical research increasingly depends on collaborative analysis of sensitive patient data. Legal and ethical restrictions, however, limit the direct sharing of raw datasets across institutions and national borders. This paper examines the deployment of secure multiparty computation (MPC) protocols in a multinational clinical research consortium involving hospitals in four countries. Privacy-preserving statistical models were used to compute disease progression indicators without revealing individual records. Operational experience indicates that computation latency and protocol complexity remain major barriers to routine use. Nevertheless, participating institutions reported improved willingness to engage in data-driven collaboration under cryptographic protection. The study suggests that privacy-preserving computation technologies may gradually reshape international medical data governance practices.