Digital pathology and AI: enhancing molecular diagnostics in low- and middle-income countries

Abstract

Introduction: Molecular diagnostics in Low- and Middle-Income Countries (LMICs) face significant barriers: limited expertise, geographical access, and infrastructure. These impede effective disease management and public health. Traditional workflows lack scalability and objectivity. Areas covered: This review explores how Digital Pathology (DP) and Artificial Intelligence (AI) can enhance LMIC molecular diagnostics. DP, via whole slide imaging, enables remote expert consultation and quality control. AI integration automates quantitative analysis (e.g. cell counting, biomarker scoring), facilitating rapid interpretation and extending specialized diagnostic reach. We discuss successful telepathology pilots and their cost-effectiveness. The manuscript highlights DP/AI’s capacity to bolster molecular screening and accelerate research, while addressing implementation barriers: infrastructure, cost, training, and regulation. Expert Opinion: Strategic integration of Digital Pathology (DP) and Artificial Intelligence (AI) offers an unparalleled opportunity to transform molecular diagnostics in LMICs. By providing scalable, objective, and accessible capabilities, these technologies can significantly improve public health outcomes and medical research. However, successful adoption demands targeted investment in digital infrastructure, capacity building, robust ethics, and public-private partnerships. Prioritizing direct clinical utility and molecular diagnostic applications is key to sustainable implementation and equitable access to advanced diagnostics.