Methods to improve anesthetic drug management

Modern day anesthesia involves the use of multiple drugs simultaneously to maintain insensitivity to pain or analgesia, lack of awareness of the surgical procedure and suppression of autonomic responses. The sedative component of anesthesia is primarily provided by using a hypnotic drug (volatile or intravenously administered) and the analgesic component is provided by an opioid (primarily intravenously administered). The level of anesthetic effect produced by these drugs is assessed by the use of a multitude of physiologic responses such as heart rate, blood pressure, movement etc. The response dynamics of these indicators are typically non linear and change with the combination of anesthetics being used. The potency of drugs also vary among patients and across age groups. These factors make the accurate titration of anesthetic drugs challenging. Accurate titration of anesthetic drug such that the effect is just enough to cause unconsciousness and immobility in the patient helps to avoid adverse effects such as delayed emergence, awareness during the procedure, hyper variable cardiovascular state and memory loss that is thought to be associated with under or overdose.; This work aims to improve anesthetic drug management through efficient drug delivery and real time monitoring. The first goal is to improve drug delivery and clinical outcomes for the average patient by identifying combinations of sedative and analgesic drugs that ensure fast recovery from anesthesia. Although the combinations are suitable to be applied in clinical practice they may not be effective when applied to individual patients that are outliers (such as those who use chronic pain medication). The drug dose in such patients can be titrated by assessing the depth of anesthesia in real time. The second goal is to test the ability of emerging depth of anesthesia monitoring technologies to assess each patient's anesthetic state. Real time monitors of anesthetic effect can help the clinicians refine their dosing strategy and predict adverse events such as intraoperative awareness or patient responses to pain.