A Configurable Clinical Decision Support System for Model-Informed Precision Dosing: System Architecture and Operational Principles (Preprint)

BACKGROUND Therapeutic Drug Monitoring (TDM) supports individualized pharmacotherapy, yet its implementation in routine care remains limited by operational constraints, data quality issues, and the need for expert interpretation. Model-Informed Precision Dosing (MIPD) addresses several of these limitations through population pharmacokinetic modeling and Bayesian forecasting, but its effective deployment in clinical practice still requires human TDM experts. OBJECTIVE This paper presents Tucuxi‑CDSS, a configurable and open-source Clinical Decision Support System (CDSS) designed to enable safe, standardized, and automated MIPD-guided dose individualization, with a particular focus on safeguarding against pre-analytical and data-entry errors. METHODS We detail Tucuxi-CDSS system architecture, data validation workflow, decision logic, and configuration mechanisms, with a particular focus on safeguarding against pre-analytical and data-entry errors. The system is built around extensive configurability through XML-based drug files, language files, and reporting templates. Verification was performed through unit testing and system-level tests, while validation was conducted by comparing CDSS outputs against those of a human TDM expert in an in-silico study. RESULTS The resulting system supports end-to-end MIPD workflows, from data import and automated error detection through dosage adaptation and clinical report generation. A pilot deployment for rifampicin dosing optimization in routine tuberculosis care is currently underway in Tanzania, and an illustrative use case with imatinib demonstrates the system's covariate handling and reporting capabilities. We also briefly present the results of the validation test where we compare its effectiveness against a human TDM expert in an in-silico study. CONCLUSIONS Tucuxi‑CDSS provides a modular, extensible, and open-source platform capable of delivering expert-level TDM oversight in settings where trained pharmacologists are scarce. Its performance evaluation against a TDM expert is presented in a companion paper and supports future prospective studies on CDSS adoption in clinical practice.