Anaesthesia Infusion Control

About

Machine-controlled drug infusion uses a target-controlled mechanism, whereby pharmacokinetic models are used to calculate the concentration of anaesthetic in the brain based on blood plasma values. If the calculated concentration goes outside set parameters, more anaesthetic is delivered until the concentration returns to the pre-set target. However, such systems use general pharmacokinetic models and calculations that don’t allow for metabolic and physiological variation in patients. There is no feedback of the patient’s actual dose. Thus, there is a risk of under dosing and patient consciousness during the procedure or excess dosing with increased recovery times and cost.  We have developed a learning closed loop system that assess the patient’s hypnotic state as a feedback mechanism but which is also capable of learning how to regulate the dose based on the previous results. This patented reinforcement learning algorithm allow the system to adapt to a patient’s responses after employing a factory-set general protocol. In tests performed, use of these algorithms resulted in a reduction of anaesthesia use by 9.4%, narrower deviations from targets, and patients’ anaesthetic state remaining in clinically acceptable ranges 93.9% of the time. The system has under gone in vivo testing and is available for license. Please press “Connect” and we will send you 6 supporting Powerpoint slides on this technology. When contacting us, please use our internal reference code: 6828