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Towards Advanced Therapeutic Drug Monitoring: A Safety and Performance Evaluation of a Clinical Decision Support System for Imatinib
Yuan James Pétermann;
Roberto Rigamonti;
Paul Thoueille;
Junrui Chen;
Lavinia Alberi;
Alexandra Simon;
François Veuve;
Eva Choong;
Bruno Da Rocha Carvalho;
Sandro Carrara;
François R Girardin;
Thierry Buclin;
Chantal Csajka;
Yann Thoma;
Monia Guidi
ABSTRACT
Background:
Therapeutic Drug Monitoring (TDM) aims to optimize clinical outcomes but is hindered by logistical delays and susceptibility to data errors. Integrating Model-Informed Precision Dosing (MIPD) with Point-of-Care testing, fortified by rule-based validation and alerts, forms a transformative Clinical Decision Support System (CDSS) essential for securing this complex workflow.
Methods:
This in silico study rigorously evaluated a rule-based CDSS for imatinib against a human TDM expert. We simulated a set of 60 virtual patients using a previously developed population pharmacokinetic model, and deliberately enriched with data quality errors (e.g., timing inaccuracies, reporting errors) to stress-test system resilience. We compared CDSS and TDM expert performances based on error detection capabilities and clinical impact on therapeutic target attainment and safety.
Results:
The CDSS and the expert demonstrated comparable error detection capabilities. Although the CDSS showed numerically higher sensitivity (53% CI95% [35–70] vs 45% CI95% [30–61]) and lower specificity (83% CI95 [63–95] vs 100% CI95 [81–100]). Clinically, the CDSS significantly outperformed the expert in target attainment (55% vs 37%; p=0.046). However, while the expert generated no detrimental interventions, the CDSS resulted in four detrimental outcomes, where patients initially within the target range were shifted outside it.
Conclusion: The CDSS demonstrated superior efficacy in optimizing imatinib exposure while serving as a robust digital gatekeeper. While active optimization drives higher efficacy, a few observed detrimental cases highlight that algorithmic safety remains contingent on data integrity. This proof-of-concept study validates the CDSS architecture as a prerequisite for future prospective clinical trials.
Citation
Please cite as:
Pétermann YJ, Rigamonti R, Thoueille P, Chen J, Alberi L, Simon A, Veuve F, Choong E, Da Rocha Carvalho B, Carrara S, Girardin FR, Buclin T, Csajka C, Thoma Y, Guidi M
Safety and Performance Evaluation of a Clinical Decision Support System for Imatinib Therapeutic Drug Monitoring: In Silico Study