MATIIGEN: A Model-Driven Framework for Automated DNA Variant Interpretation in Precision Medicine

Software engineering plays a key role in developing high-quality healthcare systems, particularly in Precision Medicine, where advanced systems are required to tailor clinical interventions based on individual genetic, environmental, and lifestyle factors. Therefore, it is necessary to rethink software engineering methods to address the significant challenges in healthcare systems, especially in system design, complex data analysis, traceability, and AI explainability. This paper presents the MATIIGEN project, which aims to address these challenges. MATIIGEN introduces an intelligent system for automated DNA variant interpretation. The project combines Model-Driven Software Engineering (MDSE) principles with Explainable Artificial Intelligence (XAI) to support the transition of genomic tools from laboratory validation environments (TRL4) to operational clinical settings (TRL6). MDSE provides the structural and methodological basis for building robust, traceable, and interoperable software systems, and XAI provides mechanisms to make the system’s outputs more transparent and understandable to clinicians. The applicability of MATIIGEN platform is demonstrated through a historically overlooked chronic disease: Lipedema. By focusing on a condition that is under-researched in clinical settings, we can demonstrate that the MATTIGEN platform can generate insights in areas of medicine where data is scarce and complex. Our work demonstrates that adopting MDSE principles provides a systematic methodology for transforming multifaceted clinical data into actionable medical insights and establishes a scalable architecture for high-quality, software-intensive systems in the healthcare domain.