Target-controlled infusion devices: are we missing much?

Donati, François; Miller, Donald R.; Fiset, Pierre

doi:10.1007/s12630-011-9454-1

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…It has been argued that benefits of some interventions are self-evident without formal evidence, as has been highlighted in a light-hearted meta-analysis of parachutes (54). The difficulties in defining costs and benefits for software-based devices are further illustrated by Target Controlled Infusion pumps for the intravenous anesthetic propofol which, while not approved for commercial use in the USA, have been widely adopted elsewhere (55). Despite challenges, research and commercialization of dashboards is ongoing motivated by the belief that current dose strategies for many therapeutics can be improved, benefitting patients.…”

Section: Discussionmentioning

confidence: 99%

Dashboard Systems: Implementing Pharmacometrics from Bench to Bedside

Mould

Upton

Wojciechowski

2014

AAPS J

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Abstract. In recent years, there has been increasing interest in the development of medical decisionsupport tools, including dashboard systems. Dashboard systems are software packages that integrate information and calculations about therapeutics from multiple components into a single interface for use in the clinical environment. Given the high cost of medical care, and the increasing need to demonstrate positive clinical outcomes for reimbursement, dashboard systems may become an important tool for improving patient outcome, improving clinical efficiency and containing healthcare costs. Similarly the costs associated with drug development are also rising. The use of model-based drug development (MBDD) has been proposed as a tool to streamline this process, facilitating the selection of appropriate doses and making informed go/no-go decisions. However, complete implementation of MBDD has not always been successful owing to a variety of factors, including the resources required to provide timely modeling and simulation updates. The application of dashboard systems in drug development reduces the resource requirement and may expedite updating models as new data are collected, allowing modeling results to be available in a timely fashion. In this paper, we present some background information on dashboard systems and propose the use of these systems both in the clinic and during drug development.

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Section: Discussionmentioning

confidence: 99%

Dashboard Systems: Implementing Pharmacometrics from Bench to Bedside

Mould

Upton

Wojciechowski

2014

AAPS J

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“…They display estimated (not measured) plasma and effect-site concentrations, which may differ from the actual concentrations, especially in patients who display extreme anthropomorphic features or in patients with different racial characteristics. [ 7 8 ]…”

Section: Robots In Anesthesiamentioning

confidence: 99%

Artificial intelligence and anesthesia

Singh

Nath²

2022

Saudi Journal of Anaesthesia

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Rapid advances in Artificial Intelligence (AI) have led to diagnostic, therapeutic, and intervention-based applications in the field of medicine. Today, there is a deep chasm between AI-based research articles and their translation to clinical anesthesia, which needs to be addressed. Machine learning (ML), the most widely applied arm of AI in medicine, confers the ability to analyze large volumes of data, find associations, and predict outcomes with ongoing learning by the computer. It involves algorithm creation, testing and analyses with the ability to perform cognitive functions including association between variables, pattern recognition, and prediction of outcomes. AI-supported closed loops have been designed for pharmacological maintenance of anesthesia and hemodynamic management. Mechanical robots can perform dexterity and skill-based tasks such as intubation and regional blocks with precision, whereas clinical-decision support systems in crisis situations may augment the role of the clinician. The possibilities are boundless, yet widespread adoption of AI is still far from the ground reality. Patient-related “Big Data” collection, validation, transfer, and testing are under ethical scrutiny. For this narrative review, we conducted a PubMed search in 2020-21 and retrieved articles related to AI and anesthesia. After careful consideration of the content, we prepared the review to highlight the growing importance of AI in anesthesia. Awareness and understanding of the basics of AI are the first steps to be undertaken by clinicians. In this narrative review, we have discussed salient features of ongoing AI research related to anesthesia and perioperative care.

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“…Subsequently, pharmacokinetic models have been incorporated into computerized systems as exemplified by the development and routine use (although not in the USA) of target controlled infusion pumps for intravenous anesthetics (21). These devices employ pharmacokinetic – pharmacodynamic link models and BET (‘Bolus-Elimination-Transfer’) functions to approximate square-wave stepping of plasma drug concentration (22–25).…”

Section: Computer-guided Dosingmentioning

confidence: 99%

Personalized Drug Dosage – Closing the Loop

Tucker

2016

Pharm Res

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A brief account is given of various approaches to the individualization of drug dosage, including the use of pharmacodynamic markers, therapeutic monitoring of plasma drug concentrations, genotyping, computer-guided dosage using ‘dashboards’, and automatic closed-loop control of pharmacological action. The potential for linking the real patient to his or her ‘virtual twin’ through the application of physiologically-based pharmacokinetic modeling is also discussed.

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Target-controlled infusion devices: are we missing much?

Cited by 4 publications

References 11 publications

Dashboard Systems: Implementing Pharmacometrics from Bench to Bedside

Dashboard Systems: Implementing Pharmacometrics from Bench to Bedside

Artificial intelligence and anesthesia

Personalized Drug Dosage – Closing the Loop

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