The use of a PID controller to model vecuronium pharmacokinetics and pharmacodynamics during liver transplantation

Abstract

A four-phase proportional-integral-derivative (PID) controller was evaluated under the extremely unstable conditions of liver transplantation. Vecuronium was delivered to achieve 80%-90% neuromuscular blockade as measured by electromyogram (EMG). The first two controller phases delivered boluses and a constant infusion calculated to rapidly achieve setpoint, followed by a proportional-derivative (PD) phase at 35% from setpoint, and PID within 10% of the setpoint. During liver transplantation, the sources of system instability included large blood losses, temperature changes, and loss of hepatic drug metabolism during removal and replacement. During prolonged surgery, and when blood losses were not severe, the EMG remained within 10% of setpoint. Controller performance was more variable during system instability. Plasma sampling and two-compartment modelling of the infusion and response with a weighting factor for blood loss allowed estimation of the sources and degree of instability for improved design of future controllers.

Muscle Relaxation Controlled by Automated Administration of Cisatracurium

“…Compared with previous researchers' results, the mean of the mean T1% and error in automatic control is 9.52 and 0.48, respectively. Except Derene's [8], the other results of mean of mean T1% error are between 0.19 to 1.3 after taking absolute calculation. The best results were presented by Shieh et al [3] who used rocuronium with hierarchical rule-based FLC.…”

“…shows a comparison of published human clinical results obtained with different drugs with an EMG monitor. General speaking, these studies [3][4][5][6][7][8][9][10][11][12] can be clustered into different types of anesthetic medicines, such as atracurium, rocuronium, vecuronium, and pacuronium. Regarding control by rocuronium, Shieh et al [3] presented the controlling combination of rocuronium with hierarchical rule-based FLC.…”

“…But there are great variations in the human body and its responses to drugs, and if the patient model was imprecise or not general, their GPC would not work in a clinical setting. Regarding control by vecuronium, O'Hara et al [8] presented the controlling combination of vecuronium with PID control. However, their control performance was highly variable during system instability because the control output of PID changed rapidly.…”

Model-Based Closed-Loop Control of Thalamic Deep Brain Stimulation

“…We use a biophysically-reasonable simulation study including models of DBS, Vim, motor cortex, motor neurons in the spinal cord, and muscle fibers to generate muscle activities (represented by EMG). To link Vim-DBS to EMG signals in our model-based control framework, model-predicted EMG signals, generated by our simulation study, are used to calculate the feedback biomarker by a polynomial fit, which is processed and implemented in a proportional-integral-derivative (PID) controller [34][35][36] that automatically updates the appropriate DBS frequency. Our model-predicted EMG can replicate the essential tremor symptoms during DBS-OFF, and is consistent with clinical observations of tremor during different frequencies of Vim-DBS.…”

Closed-loop drug infusion using neural networks

“…Recent developments in the field of closed-loop drug delivey either employ the classical PID (proportionalintegral-differential) controller [OHD+97], use a modelbased (pharmacodynamic/pharmacokinetic model, PKPD) [OSA9 1 J or a rule-based approach (fuzzy logic) [MLER97].…”