Digital twins in precision pharmacotherapy: emerging applications, challenges, and future directions

Digital twin technology, defined as dynamic digital models that represent individual patients, is emerging as a promising paradigm in precision pharmacotherapy. The integration of pharmacokinetic and pharmacodynamic (PK/PD) modeling, clinical data, genomic information, and real-time patient monitoring enables digital twins to shift drug therapy away from population-based averages toward individualized, adaptive decisions. This narrative review explores conceptual frameworks, emerging applications, methodological approaches, clinical value, limitations, and future directions of digital twins in pharmacotherapy, with particular emphasis on the role of clinical pharmacists. Unlike broader digital twin reviews that primarily emphasize technical architectures, disease-specific applications, or pharmaceutical research and development, this review focuses on the clinical-pharmacy translation layer: how digital twin outputs can be interpreted, validated, communicated, and converted into actionable medication decisions at the bedside and across ambulatory care settings. Key applications include precision dosing, polypharmacy management, antimicrobial stewardship, and the optimization of complex therapies, alongside important ethical, regulatory, and implementation challenges.