Digital twin technology is increasingly used across pharmaceutical science, pharmaceutical manufacturing, precision medicine, and regulatory science. However, the same term is now applied to systems with very different simulated objects, including drug products, manufacturing processes, patients, and regulatory workflows. This semantic expansion has created a need for clearer conceptual organisation. The central problem addressed in this article is that pharmaceutical digital twin research has developed faster than its classification language. A tablet dissolution model, a continuous manufacturing simulator, a virtual patient population, and a compliance-monitoring model may all be described as digital twins, even though they support different decisions and require different validation logics. Without classification, comparison across studies becomes imprecise. This article proposes a four-category taxonomy of pharmaceutical digital twin systems. The categories are Product Twins, Process Twins, Patient Twins, and Regulatory Twins. The classification is grounded in the primary object of simulation and the principal decision function supported by the twin. The proposed taxonomy shows that digital twins should not be treated as a single technological class. Product Twins primarily simulate drug-product behaviour, Process Twins simulate manufacturing operations, Patient Twins simulate therapeutic response in individuals or populations, and Regulatory Twins simulate or support regulatory evaluation and oversight. Distinguishing these categories is a necessary step toward mature pharmaceutical digital twin science.
Eurasian Academy of Medicine and Dentistry