The results support further study of the combinations of bupivacaine, fentanyl, and clonidine mentioned above for postoperative analgesia after knee and hip surgery. This novel optimization method may be useful in clinical research.

Monitored anesthesia care (MAC) is increasingly used to provide patient comfort for diagnostic and minor surgical procedures. The drugs used in this setting can cause profound respiratory depression even in the therapeutic concentration range. Titration to effect suffers from the difficulty to predict adequate analgesia prior to application of a stimulus, making titration to a continuously measurable side effect an attractive alternative. Exploiting the fact that respiratory depression and analgesia occur at similar drug concentrations, we suggest to administer opioids and propofol during MAC using a feedback control system with transcutaneously measured partial pressures of CO (P tcCO ) as the controlled variable. To investigate this dosing paradigm, we developed a comprehensive model of human metabolism and cardiorespiratory regulation, including a compartmental pharmacokinetic and a pharmacodynamic model for the fast acting opioid remifentanil. Model simulations are in good agreement with ventilatory experimental data, both in presence and absence of drug. Closed-loop simulations show that the controller maintains a predefined CO target in the face of surgical stimulation and variable patient sensitivity. It prevents dangerous hypoventilation and delivers concentrations associated with analgosedation. The proposed control system for MAC could improve clinical practice titrating drug administration to a surrogate endpoint and actively limiting the occurrence of hypercapnia/hypoxia. Note to Practitioners-We describe a system minimizing the risks associated with the delivery of respiratory depressants to spontaneously breathing patients during medical procedures. In this setting, several factors can contribute to the occurrence of patient injuries: overdosing leading to profound respiratory depression, especially in the nonsteady state (bolus administration); inadequate monitoring of physiological parameters; delayed or inadequate resuscitation. We propose to monitor the respiratory gases (O CO ) as effective indicators of the patient's ventilatory state and to automatically titrate drug delivery based on this information. We tested the performance of the control system in a software environment with a comprehensive mathematical model of human metabolism and cardiorespiratory regulation. Using a P tcCO setpoint of 50 mmHg, the system delivered drug concentrations in the accepted therapeutic range for analgesia and prevented the occurrence of severe (transient and steady-state) respiratory depression, coping with interindividual variability. Since the drugs and the hardware necessary for the proposed system are commercially available, developing a medical device for the automatic delivery of sedatives/analgesics would be relatively inexpensive. In our opinion, the safety of monitored anesthesia care, especially when performed by non-anesthesiologists, would be profoundly enhanced. Future research will be directed towards the design of an algorithm for robust detection of sensor malfunction and the clinical evaluat...

The model is consistent with clinical knowledge and supports previously published experimental results on optimal drug combinations. This new framework improves understanding of the characteristics of drug combinations used in clinical practice and can be used in clinical research to identify optimal drug dosing.

Drugs are routinely combined in anesthesia and pain management to obtain an enhancement of the desired effects. However, a parallel enhancement of the undesired effects might take place as well, resulting in a limited therapeutic usefulness. Therefore, when addressing the question of optimal drug combinations, side effects must be taken into account. We propose a new method to study drug interactions considering also their side effects and to identify optimal drug dosing. The model is consistent with clinical knowledge and can explain previously published experimental results, improving our understanding of the characteristics of drug combinations used in clinical practice.

In conscious sedation (CS) procedures, the patient is sedated but retains the ability to breathe spontaneously. Drug-induced ventilatory depression represents a dangerous side effect of CS, possibly leading to hypoventilation and subsequent hypoxia. In this work, we propose a new pharmacodynamic model for drug-induced ventilatory depression. The model presents a parsimonious structure and shows good agreement with experimental data for different drugs. In addition, we explore the innovative idea of regulating drug infusion during CS by means of a feedback control system based on measurements of transcutaneous partial pressure of CO(2). In simulations, the controller proves able to maintain a predefined target of CO(2) despite pain, external disturbances and inter-patient variability in the sensibility to the drug. The implementation of the controller during CS procedures would improve clinical practice minimizing the occurrence of drug-induced ventilatory depression by tailoring drug infusion to patient's needs.