<p>This review examines the mathematical modeling of pharmacodynamic effects on bone tissue. It focuses on integrating biological knowledge with computational approaches to improve our understanding of drug-influenced bone remodeling. Bone is a highly dynamic organ undergoing continuous renewal through tightly regulated cellular processes. Mathematical models provide a quantitative framework for analyzing key physiological mechanisms, including bone density regulation, fracture healing, and tumor progression in response to pharmacological interventions. We systematically classify and assess commonly used models that simulate cellular dynamics in bone-related diseases under pharmacological intervention. Each model is evaluated in terms of its applicability, predictive capability, and inherent limitations. While existing models have effectively captured fundamental aspects of healthy bone reconstruction, recent discoveries in osteoblast activity and systemic bone physiology emphasize the need for more advanced mathematical representations of drug effects. These developments call for models that better capture the complexities of drug actions at multiple biological scales. The integration of biomechanics, systems biology, and artificial intelligence has facilitated the creation of predictive models capable of optimizing pharmacological strategies and supporting personalized treatment approaches. Moving forward, interdisciplinary collaboration will be crucial to refining these models, improving their translational value, and advancing pharmacological research in bone health and disease.</p>