doseoptimization

Dose optimization is the process of selecting and adjusting dosage regimens to maximize therapeutic benefit while minimizing adverse effects. It applies to pharmacologic therapies and to imaging procedures that involve radiation exposure, with the goal of tailoring treatment to individual patients.

In medicine, dose optimization relies on pharmacokinetic and pharmacodynamic modeling, therapeutic drug monitoring, and dose titration. Population PK/PD models estimate typical responses and variability to predict individual dosing, often using Bayesian forecasting. Clinicians use loading doses, maintenance dosing, and dose adjustments for organ impairment, drug interactions, age, or weight, aiming to stay within a therapeutic window.

In radiology and nuclear medicine, dose optimization means reducing radiation dose while maintaining sufficient image quality for diagnosis, following ALARA principles. Techniques include protocol selection, automatic exposure control, dose tracking, iterative reconstruction, and newer imaging technologies.

Implementation involves data collection, model development, simulation, decision support, and monitoring outcomes such as efficacy, toxicity, and diagnostic accuracy. Integration with electronic health records and clinical guidelines supports consistency and auditing.

Challenges include interpatient variability, incomplete data, adherence, cost, and balancing benefit-risk, especially in pediatrics, geriatrics, and patients with comorbidities. Ethical and regulatory considerations guide safety and documentation.

Ongoing research emphasizes individualized therapy, real-time monitoring, and optimization algorithms to improve safety and effectiveness across therapies and imaging.