Why Nigeria's Mobile Authentication System Failed: A Mixed-Methods Evaluation and AI-Based Framework for Securing the Pharmaceutical Supply Chain

Counterfeit medicines remain a significant public health challenge in Nigeria. The Mobile Authentication Service (MAS), introduced as a low-cost SMS-based verification tool, has not delivered the anticipated outcomes. This study adopts a mixed-methods design—combined empirical data from stakeholders and simulated quantitative data to evaluate MASs technical weaknesses and to propose an AI-driven alternative. Results indicate drawbacks in the existing system’s performance attributable to limited scalability, vulnerability to code duplication, and user distrust. Simulations show that an AI-enhanced MAS achieves higher accuracy, faster response times, and stronger detection rates. The paper contributes a computing-oriented evaluation of MAS and introduces a hybrid AI blockchain architecture to secure Nigeria’s pharmaceutical supply chain.