Clinical trial NCT03143972: Pharmacodynamic Interaction of REMI and DMED
Official title: Pharmacodynamic Interactions Between Remifentanil and Dexmedetomidine (PIRAD)
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: PHASE4
Conditions: Anesthesia
Keywords: Dexmedetomidine
Remifentanil
Pharmacodynamics
Interaction
Lead sponsor: University Medical Center Groningen
Sponsor class: OTHER
First posted: 2017-05-08
Enrollment: 30
Sex: ALL
Minimum age (years): 18
Maximum age (years): 70
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NON_RANDOMIZED
Intervention model: CROSSOVER
Intervention model description: All volunteers will receive 2 standardized anesthesia sessions with a washout period of at least one week between sessions. During the first session volunteers will receive dexmedetomidine, during the second session they will first receive remifentanil and afterwards the combination of drugs will be administered. Anesthetic depth will be evaluated by MOAA/S scores (see table 2), testing of tolerance to electrical stimuli and laryngoscopy. Furthermore multichannel EEG-data will be collected to get insight in the drug dependent characteristics. Measured effects will be related to drug plasma concentrations.
Primary purpose: SUPPORTIVE_CARE

Brief summary: The objective is to map the pharmacokinetic / pharmacodynamic interaction between dexmedetomidine and remifentanil by observing changes in anesthetic depth. These changes will be related to drug concentrations using pharmacokinetic/pharmacodynamic (PKPD) modeling.

Detailed description: This study is designed to investigate whether the use of a combination of dexmedetomidine and remifentanil is clinically useful to provide anesthesia during surgical and diagnostic procedures and whether it could be used for anesthetic induction. Furthermore the aim is to gain better insights in the required dosing regimens, the inter-individual variability in response towards the combination and the associated side effects. Better characterization of this drug-drug interaction will presumably lead to more precise dosing regimens, which in turn, will lead to a reduction in the occurrence of oversedation, side effects and recovery times.

The objective is to map the pharmacokinetic / pharmacodynamic interaction between dexmedetomidine and remifentanil by observing changes in anesthetic depth, measured by hypnotic and analgesic endpoints such as modified observer's assessment of alertness and sedation scale (MOAA/S), response to electrical stimuli, response to laryngoscopy and electroencephalogram (EEG) derived indices. These effects will be related to drug concentrations using pharmacokinetic/pharmacodynamic (PKPD) modeling.

Eligibility criteria: Inclusion Criteria:

* American Society of Anesthesiologists (ASA) Physical Status 1
* No medical history of significance
* No chronic use of medication, drugs, tobacco or more than 20 gr alcohol daily (oral contraceptives excluded).
* Concerning the cognitive function: Volunteers are considered to have sufficient cognitive reserve if they are able to read and comprehend the patient information form, if they can adequately answer the anamnestic questions during the screening process and if they are allowed to provide legitimate written informed consent.
* No selection will be made regarding ethnic background
* No exclusion criterium is present

Exclusion Criteria:

* Known intolerance to dexmedetomidine or remifentanil
* Volunteer refusal
* Age \< 18 years or \>70 years
* Pregnancy, or currently nursing
* Hairstyle with dreadlocks (EEG-monitoring will not be possible)
* Body mass index (BMI) \<18 or \>30 kg/m2.
* Neurological disorder (epilepsy, the presence of a brain tumor, a history of brain surgery, hydrocephalic disorders, depression needing treatment with anti-depressive drugs, a history of brain trauma, a subarachnoidal bleeding, TIA or cerebral infarct, psychosis or dementia , schizophrenia, alcohol or drug abuse).
* Diseases involving the cardiovascular system (hypertension, coronary artery disease, prior acute myocardial infarction, any valvular and/or myocardial disease involving

Primary outcomes:
measure: Tolerance of Laryngoscopy (TOL)
timeFrame: 35 - 255 minutes
Secondary outcomes:
measure: Modified observer's assessment of alertness and sedation scale (MOAA/s)
timeFrame: During anesthesia sessions day 1 and day 2
measure: Electrical stimulus
timeFrame: During anesthesia sessions day 1 and day 2
measure: Electroencephalogram (EEG)
timeFrame: During anesthesia sessions day 1 and day 2
Other outcomes:
Locations:
city: Groningen
country: Netherlands
facility: University Medical Center Groningen
Study officials:
affiliation: University Medical Center Groningen
name: Michel MR Struys, Prof.Dr.
role: PRINCIPAL_INVESTIGATOR
References:
citation: Hannivoort LN, Eleveld DJ, Proost JH, Reyntjens KM, Absalom AR, Vereecke HE, Struys MM. Development of an Optimized Pharmacokinetic Model of Dexmedetomidine Using Target-controlled Infusion in Healthy Volunteers. Anesthesiology. 2015 Aug;123(2):357-67. doi: 10.1097/ALN.0000000000000740.
citation: Ramaswamy SM, Kuizenga MH, Weerink MAS, Vereecke HEM, Struys MMRF, Belur Nagaraj S. Frontal electroencephalogram based drug, sex, and age independent sedation level prediction using non-linear machine learning algorithms. J Clin Monit Comput. 2022 Feb;36(1):121-130. doi: 10.1007/s10877-020-00627-3. Epub 2020 Dec 14.
citation: Ramaswamy SM, Weerink MAS, Struys MMRF, Nagaraj SB. Dexmedetomidine-induced deep sedation mimics non-rapid eye movement stage 3 sleep: large-scale validation using machine learning. Sleep. 2021 Feb 12;44(2):zsaa167. doi: 10.1093/sleep/zsaa167.
citation: Belur Nagaraj S, Ramaswamy SM, Weerink MAS, Struys MMRF. Predicting Deep Hypnotic State From Sleep Brain Rhythms Using Deep Learning: A Data-Repurposing Approach. Anesth Analg. 2020 May;130(5):1211-1221. doi: 10.1213/ANE.0000000000004651.
citation: Ramaswamy SM, Kuizenga MH, Weerink MAS, Vereecke HEM, Struys MMRF, Nagaraj SB. Novel drug-independent sedation level estimation based on machine learning of quantitative frontal electroencephalogram features in healthy volunteers. Br J Anaesth. 2019 Oct;123(4):479-487. doi: 10.1016/j.bja.2019.06.004. Epub 2019 Jul 18.