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...