Progress in research of pharmacokinetic models for intelligent target controlled infusion

doi:10.3877/cma.j.issn.1674-0785.2023.04.022

Abstract

Abstract:

Target controlled infusion (TCI) is a technique of infusing intravenous drugs to achieve a user-defined predicted (target) drug concentration in a specific body compartment or tissue of interest. TCI is becoming widely used with the advent of big data in medicine. In order to realize the intellectualization of modern anesthesia, more attention has been paid to the development and research of automatic drug delivery systems, while the optimization of TCI models emphasizes the individualization of anesthesia. This review intends to link TCI to modern medicine and thus to illustrate the multichannel closed-loop system and the optimization of pharmacokinetic models, which will characterize the future development of TCI.

Key words: Intellectualization, Target controlled infusion, Multichannel, Closed-loop, Model

Zhihao Lai, Yan Lu, Xincheng OuYang, Kexin Song. Progress in research of pharmacokinetic models for intelligent target controlled infusion[J]. Chinese Journal of Clinicians(Electronic Edition), 2023, 17(04): 491-495.

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References 44

1	Struys MM, De Smet T, Glen JI, et al. The history of target-controlled infusion [J]. Anesth Analg, 2016, 122(1): 56-69.
2	Zhang L, Wang H, Li Q, et al. Big data and medical research in China [J]. BMJ, 2018, 360: j5910.
3	Farag E, Westlake B, Dutton RP, et al. The ASA committee for neuroanesthesia and anesthesia quality institute: report for demographic patterns for neurosurgical anesthesia practice in the United States [J]. J Neurosurg Anesthesiol, 2018, 30(2): 189-191.
4	Leopold JA. Precision medicine based on personal phenotyping [J]. Trends Cardiovasc Med, 2023, 27: S1050-1738(23)00016-6.
5	Feehley T, O'Donnell CW, Mendlein J, et al. Drugging the epigenome in the age of precision medicine [J]. Clin Epigenetics, 2023, 15(1): 6.
6	Engbers FHM, Dahan A. Anomalies in target-controlled infusion: an analysis after 20 years of clinical use [J]. Anaesthesia, 2018, 73(5): 619-630.
7	Liu N, Le Guen M, Benabbes-Lambert F, et al. Feasibility of closed-loop titration of propofol and remifentanil guided by the spectral M-Entropy Monitor [J]. Anesthesiology, 2012, 116(2): 286-295.
8	Martín-Mateos I, Méndez Pérez JA, Reboso Morales JA, et al. Adaptive pharmacokinetic and pharmacodynamic modelling to predict propofol effect using BIS-guided anesthesia [J]. Comput Biol Med, 2016, 75: 173-180.
9	Fang M, Tao Y, Wang Y. An enriched simulation environment for evaluation of closed-loop anesthesia [J]. J Clin Monit Comput, 2014, 28(1): 13-26.
10	Hemmerling TM, Arbeid E, Wehbe M, et al. Evaluation of a novel closed-loop total intravenous anaesthesia drug delivery system: a randomized controlled trial [J]. Br J Anaesth, 2013, 110(6): 1031-1039.
11	杨宁, 杨明, 彭文平, 等. BIS指导下异丙酚闭环与开环靶控输注腹部手术麻醉效果的比较 [J]. 中南大学学报·医学版, 2020, 45(12): 1419-1424.
12	Kuizenga MH1, Vereecke HE, Struys MM. Model-based drug administration: current status of target-controlled infusion and closed-loop control [J]. Curr Opin Anaesthesiol, 2016, 29(4): 475-481.
13	Hemmerling TM, Charabati S, Salhab E, et al. The Analgoscore: a novel score to monitor intraoperative nociception and its use for closed-loop application of remifentanil [J]. J Comput, 2009, 4: 311-318.
14	Bibian S, Dumont GA, Black I. Closed-loop target-controlled infusion systems: stability and performance aspects [J]. Mil Med, 2015, 180(3 Suppl): 96-103.
15	吴奇伟, 岳云, 张忱. 腹部手术中闭环与开环靶控输注罗库溴铵的药效比较 [J/OL]. 中华临床医师杂志(电子版), 2012, 6(6): 1605-1606.
16	Dussaussoy C, Peres M, Jaoul V, et al. Automated titration of propofol and remifentanil decreases the anesthesiologist's workload during vascular or thoracic surgery: a randomized prospective study [J]. J Clin Monit Comput, 2014, 28(1): 35-40.
17	Guo Y, Wang D, Yang X, et al. Effects of different sufentanil target concentrations on the MAC_BAR of sevoflurane inpatients with carbon dioxide pneumoperitoneum stimulus [J]. BMC Anesthesiol, 2020, 20(1): 239.
18	赵艳, 王玉洁, 邱维吉, 等. 静吸复合全麻时靶控输注低浓度舒芬太尼的准确性评价 [J]. 中华麻醉学杂志, 2020, 40(8): 4.
19	韩灵, 庞磊, 连鑫等. 不同效应室靶浓度舒芬太尼对丙泊酚意识消失EC50的影响 [J/OL]. 中华临床医师杂志(电子版), 2011, 5(06): 1601-1605.
20	Chen L, Wang M, Xiang H, et al. Prediction of effect-site concentration of sufentanil by dose-response target controlled infusion of sufentanil and propofol for analgesic and sedation maintenance in burn dressing changes [J]. Burns, 2014, 40(3): 455-459.
21	李柳旬, 徐波, 吴宗泽, 等. NI指导下丙泊酚-瑞芬太尼程控性闭环靶控输注麻醉用于腹腔镜胆囊切除术的效果 [J]. 中华麻醉学杂志, 2016, 36(12): 1423-1427.
22	Mahr N, Bouhake Y, Chopard G, et al. Postoperative neurocognitive disorders after closed-loop versus manual target controlled-infusion of propofol and remifentanil in patients undergoing elective major noncardiac surgery: the randomized controlled postoperative cognitive dysfunction-electroencephalographic-guided anesthetic administration trial [J]. Anesth Analg, 2021, 133(4): 837-847.
23	Hüppe T, Maurer F, Sessler DI, et al. Retrospective comparison of Eleveld, Marsh, and Schnider propofol pharmacokinetic models in 50 patients [J]. Br J Anaesth, 2020, 124(2): e22-e24.
24	Schnider TW, Minto CF, Gambus PL, et al. The influence of method of administration and covariates on the pharmacokinetics of propofol in adult volunteers[J]. Anesthesiology, 1998, 88(5): 1170-1182.
25	Schüttler J, Ihmsen H. Population pharmacokinetics of propofol: a multicenter study [J]. Anesthesiology, 2000, 92(3): 727-738.
26	陈广民, 郭雷, 李恩有. 丙泊酚靶控输注准确性的研究进展 [J]. 中国现代应用药学, 2020, 37(19): 5.
27	Anderson BJ, Bagshaw O. Practicalities of total intravenous anesthesia and target-controlled infusion in children [J]. Anesthesiology, 2019, 131(1): 164-185.
28	Eleveld DJ, Colin P, Absalom AR, et al. Target-controlled-infusion models for remifentanil dosing consistent with approved recommendations [J]. Br J Anaesth, 2020, 125(4): 483-491.
29	Maitre PO, Ausems ME, Vozeh S, et al. Evaluating the accuracy of using population pharmacokinetic data to predict plasma concentrations of alfentanil [J]. Anesthesiology, 1988, 68: 59-67.
30	Scott JC, Stanski DR. Decreased fentanyl and alfentanil dose requirements with age. A simultaneous pharmacokinetic and pharmacodynamic evaluation [J]. J Pharmacol Exp Ther, 1987, 240: 159-166.
31	Wu W, Zhou Y, Zhu Y, et al. Sufentanil target controlled infusion (TCI) versus remifentanil TCI for monitored anaesthesia care for patients with severe tracheal stenosis undergoing fiberoptic bronchoscopy: protocol for a prospective, randomised, controlled study [J]. BMJ Open, 2022, 12(8): e058662.
32	Ingrande J, Lemmens HJ. Target-Controlled Infusion: not a one-sized-fits-all answer to drug administration [J]. Anesth Analg, 2018, 127(4): 813-814.
33	Glen JB, White M. A comparison of the predictive performance of three pharmacokinetic models for propofol using measured values obtained during target-controlled infusion [J]. Anaesthesia, 2014, 69(6): 550-557.
34	de la Fuente NF, Puga VA, Cortínez LI, et al. The effective effect-site propofol concentration for induction in morbidly obese patients using total body weight with a new pharmacokinetic model [J]. Anesth Analg, 2013, 117(1): 283-284.
35	Chidambaran V, Venkatasubramanian R, Sadhasivam S, et al. Population pharmacokinetic-pharmacodynamic modeling and dosing simulation of propofol maintenance anesthesia in severely obese adolescents [J]. Paediatr Anaesth, 2015, 25(9): 911-923.
36	Cortínez LI, De la Fuente N, Eleveld DJ, et al. Performance of propofol target-controlled infusion models in the obese: pharmacokinetic and pharmacodynamic analysis [J]. Anesth Analg, 2014, 119(2): 302-310.
37	Eleveld DJ. Target-controlled-infusion for special populations: How different is different enough? [J]. Acta Anaesthesiol Scand, 2019, 63(4): 422-423.
38	Short TG, Hannam JA, Laurent S, et al. Refining target-controlled infusion: an assessment of pharmacodynamic target-controlled infusion of propofol and remifentanil using a response surface model of their combined effects on bispectral index [J]. Anesth Analg, 2016, 122(1): 90-97.
39	陈杭. 麻醉靶控输注的控制策略及算法研究 [D]. 杭州: 浙江大学, 2007.
40	王乐, 夏彬彬, 陈世财. 生理药代动力学模型在临床合理用药中的应用 [J]. 中国临床药理学杂志, 2023, 39(01): 127-130.
41	Deepika D, Kumar V. The role of “physiologically based pharmacokinetic model (PBPK)” new approach methodology (NAM) in pharmaceuticals and environmental chemical risk assessment [J]. Int J Environ Res Public Health, 2023, 20(4): 3473.
42	Fairman K, Choi MK, Gonnabathula P, et al. An overview of physiologically-based pharmacokinetic models for forensic science [J]. Toxics, 2023, 11(2): 126.
43	Hartmanshenn C, Scherholz M, Androulakis IP. Physiologically-based pharmacokinetic models: approaches for enabling personalized medicine [J]. J Pharmacokinet Pharmacodyn, 2016, 43(5): 481-504.
44	姜晓峰. 医疗大数据在临床医学中的应用现状 [J/OL]. 中华临床医师杂志(电子版), 2018, 12(8): 427-431.

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