Faggionato E, Guazzo A, Pegolo E, Carli R, Bruschetta M, Favero SD. An Adaptive Model Predictive Controller to Address the Biovariability in Blood Clotting Response During Therapy With Warfarin.
IEEE Trans Biomed Eng 2023;
70:2667-2678. [PMID:
37030797 DOI:
10.1109/tbme.2023.3261962]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Abstract
OBJECTIVE
Effective dosing of anticoagulants aims to prevent blood clot formation while avoiding hemorrhages. This complex task is challenged by several disturbing factors and drug-effect uncertainties, requesting frequent monitoring and adjustment. Biovariability in drug absorption and action further complicates titration and calls for individualized strategies. In this paper, we propose an adaptive closed-loop control algorithm to assist in warfarin therapy management.
METHODS
The controller was designed and tested in silico using an established pharmacometrics model of warfarin, which accounts for inter-subject variability. The control algorithm is an adaptive Model Predictive Control (a-MPC) that leverages a simplified patient model, whose parameters are updated with a Bayesian strategy. Performance was quantitatively evaluated in simulations performed on a population of virtual subjects against an algorithm reproducing medical guidelines (MG) and an MPC controller available in the literature (l-MPC).
RESULTS
The proposed a-MPC significantly (p 0.05) lowers rising time (2.8 vs. 4.4 and 11.2 days) and time out of range (3.3 vs. 7.2 and 12.9 days) with respect to both MG and l-MPC, respectively. Adaptivity grants a significantly (p 0.05) lower number of subjects reaching unsafe INR values compared to when this feature is not present (8.9% vs.15% of subjects presenting an overshoot outside the target range and 0.08% vs. 0.28% of subjects reaching dangerous INR values).
CONCLUSION
The a-MPC algorithm improve warfarin therapy compared to the benchmark therapies.
SIGNIFICANCE
This in-silico validation proves effectiveness of the a-MPC algorithm for anticoagulant administration, paving the way for clinical testing.
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