Pharmacotherapy and Ventilatory Control Pieter Simons in Health and Disease
Pharmacotherapy and Ventilatory Control in Health and Disease Pieter Simons
The investigations described in chapters 2-5 of this thesis were performed in the Anesthesia & Pain Research Unit, Leiden University Medical Center, under the supervision of prof. dr. A. Dahan and dr. R. van der Schrier. Copyright ©2024 Pieter Simons. ISBN 978-94-6506-095-8 No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without prior permission of the author. Typeset by LATEX Cover design by Anneriek Simons Printed by Ridderprint, the Netherlands The printing of this thesis was financially supported by: ChipSoft and Trevena.
Pharmacotherapy and Ventilatory Control in Health and Disease PROEFSCHRIFT ter verkrijging van de graad van Doctor aan de Universiteit Leiden, op gezag van Rector Magnificus Prof. dr. ir. H. Bijl, hoogleraar in de Faculteit der Wiskunde en Natuurwetenschappen, volgens besluit van het College voor Promoties te verdedigen op 5 juni 2024 klokke 11:15 uur door Pieter Simons geboren te Enschede in 1991
Promotiecomissie Promotor: Prof. dr. A. Dahan Copromotores: Dr. M. Niesters Dr. M. van Velzen Commissie: Prof. dr. E.Y. Sarton Prof. dr. S. B. Karan (Rochester Medical Center) Prof. dr. dr. M.W. Hollmann (Amsterdam UMC) Prof. dr. H. Pijl Prof. dr. J. Swen
The marriage of breath and beat is critical for life. Ken D. O’Halloran - 2023
Contents 1 Introduction 1 2 S-ketamine oral thin film pharmacokinetics 13 3 S-ketamine oral thin film pharmacodynamics 41 4 Oliceridine respiratory effects 65 5 Diabetes, hyperinsulinemia, and the hypoxic ventilatory response 99 6 Summary, conclusions, and perspectives 121 7 Nederlandse samenvatting 131 Addenda 135
List of Figures 2.1 S-ketamine PK - Plasma concentrations . . . . . . . . . . . . . . 22 2.2 S-ketaminePK-FinalPKmodel. . . . . . . . . . . . . . . . . . 26 2.3 S-ketamine PK - Goodness of Fit (GOF) plots . . . . . . . . . . 30 2.4 S-ketaminePK-Simulations . . . . . . . . . . . . . . . . . . . . 31 2.5 S-ketaminePK-SimulationsHNK . . . . . . . . . . . . . . . . . 35 3.1 S-ketamine PD - Pharmacokinetic data . . . . . . . . . . . . . . 49 3.2 S-ketamine PD - Antinociceptive data . . . . . . . . . . . . . . . 49 3.3 S-ketamine PD - Goodness-of-Fit plots . . . . . . . . . . . . . . . 52 3.4 S-ketaminePD-Drughighdata . . . . . . . . . . . . . . . . . . 53 3.5 S-ketamine PD - Visual Predictive Checks . . . . . . . . . . . . . 54 3.6 S-ketamine PD - Steady-state concentration-effect relationships . 55 4.1 Oliceridine respiratory effects - ˙VE55 for four treatment arms . . 74 4.2 Oliceridine respiratory effects - Mean pharmacokinetic data . . . 76 4.3 Oliceridine respiratory effects - Goodness-of-Fit PK data . . . . . 77 4.4 Oliceridine respiratory effects - Population PK model outcome . 78 4.5 Oliceridine respiratory effects - Population PD model outcome . 81 4.6 Oliceridine respiratory effects - Goodness-of-Fit PD data . . . . . 82 4.7 Oliceridine respiratory effects - Simulation multiple dosing . . . . 85 4.8 Oliceridine respiratory effects - Queried adverse events . . . . . . 87 5.1 CBHypoxia-Strobediagram. . . . . . . . . . . . . . . . . . . . 105 5.2 CBHypoxia-HVR..........................108 5.3 CBHypoxia-Dejour.........................109 5.4 CBHypoxia-Hemodynamics . . . . . . . . . . . . . . . . . . . . 111
List of Tables 2.1 S-ketamine PK - Subject characteristics . . . . . . . . . . . . . . 20 2.2 S-ketamine PK - Pharmacokinetic parameters OTF . . . . . . . 23 2.3 S-ketaminePK-Adverseeffects . . . . . . . . . . . . . . . . . . 24 2.4 S-ketamine PK - OTF pharmacokinetics . . . . . . . . . . . . . . 27 3.1 S-ketamine PD - Pharmacodynamic parameter estimates . . . . 51 4.1 Oliceridine respiratory effects - PK parameter estimates . . . . . 79 4.2 Oliceridine respiratory effects - PD parameter estimates . . . . . 83 4.3 Oliceridine respiratory effects - Adverse effects . . . . . . . . . . 86 5.1 CB Hypoxia - Subject characteristics . . . . . . . . . . . . . . . . 106
1 Chapter 1 Introduction
Background Inherently dangerous, anesthesia has matured into an essentially safe practice due to major advancements in the field. Over the decades, even since the 1950s, the field of anesthetic and perioperative care has witnessed a continuous decline in mortality rates.1 These advancements can be attributed to the utilization of safer anesthetic agents, the development of advanced technical instruments and techniques, and comprehensive training programs, among other pivotal factors. Despite these remarkable progressions, challenges and gaps in our understanding persist. The evolution of drug use in anesthesiology is particularly noteworthy. Initially focused on facilitating surgical procedures and enhancing patient health outcomes, in the current landscape of 2023, anesthetics have expanded their applications well beyond the confines of the operating room. They are now integral in diverse medical contexts, including trauma care, resuscitation, sedation, intensive care, and the management of acute and chronic pain.2 Furthermore, the exploration of unconventional agents, such as psychedelics for pain, and the use of anesthetic agents in other disciplines, underscores the dynamic nature of modern medical practice and interdisciplinary research.3 For instance, consider ketamine, an N-methyl-D-aspartate receptor (NMDAR) blocker, introduced as an intravenous anesthetic in 1965. Since the 1990s its applications have extended to include the management of acute and chronic pain. More recently, since the early 2000s, nasal S-ketamine marketed as Spravato, has also found utility in psychiatry, offering an alternative treatment for therapy-resistant depression and post-traumatic stress disorder. This presents a potential replacement for traditional treatments like electroconvulsive therapy or antipsychotic therapy in specific cases.4,5 Studies on this fascinating drug can be advantageous for both the fields of psychiatry and anesthesiology. One persistent challenge of drugs in anesthesiology revolves around the efficacy and side-effect profile of contemporary analgesics. Both non-opioid and opioid analgesics, while indispensable in pain management, exhibit limitations in certain patient groups, particularly those suffering from chronic pain. Conversely, these drugs have adverse effects, including the potential for abuse, as observed with ketamine and opioids, as well as the life-threatening risk of opioid-induced respiratory depression. The combination of addiction and respiratory depression stands at the core of the current opioid epidemic in the United States, characterized by more than 100,000 deaths from opioid overdose in 2022.6 Both the efficacy and side-effect profile of these analgesics are intertwined with the critical role played by the patient’s phenotype.”One Size Fits All” is a thing of the past and research and guidelines are increasingly tailored to 2
1 Introduction individual factors due to the heterogeneity of clinical effects. Notably, a recent observational study involving over 1,300 patients highlighted that factors such as male sex, older age, opioid naivety, sleep-disordered breathing, and heart failure are associated with an increased risk of opioid-induced respiratory depression.7 Additional risk factors encompass the presence of comorbidities, concomitant use of systemic opioids and sedatives, and higher BMI.8,9 While clinical trials, typically conducted on young and healthy subjects, illuminate drug effects, questions are raised about the applicability of their findings. Therefore, we focus on studying a new opioid in a representative study sample comprising male and female volunteers of older age, including overweight participants. Of particular interest is the role of obesity as a risk factor for opioid-induced respiratory depression. Obesity’s global prevalence is staggering, and it directly heightens the risk of opioid-induced respiratory depression due to obesity-related changes in the respiratory system, alterations in respiratory drive, and breathing abnormalities during sleep.9,10 Furthermore, obesity increases the likelihood of developing insulin resistance and type 2 diabetes. Intriguingly, studies indicates that insulin resistance can modulate ventilatory drive, and type 2 diabetes can lead to the development of sleep-disordered breathing, independent of obesity.11,12,13 While speculative, these factors may contribute to an elevated risk of premature mortality among individuals with type 2 diabetes who use opioids over an extended period.14 In this thesis, I will present a series of studies conducted in our laboratory, focusing on the pharmacology of ketamine oral and buccal thin film, intravenous oliceridine and morphine, and type 2 diabetes. The studies encompass pharmacological aspects (ketamine, oliceridine, and morphine) and their effects on ventilatory control (morphine, oliceridine, and type 2 diabetes), spanning the important effects of these drugs in clinical practice. Thesis overview While ketamine has been used for nearly six decades, ongoing developments have led to new indications and new formulations are still being developed. As an analgesic, ketamine is employed in the prehospital setting, emergency ward, perioperatively, and for chronic pain syndromes.15,16,17,18 Substantial gaps persist in our understanding of its efficacy and safety when considering different routes of administration, varied durations, dosages, and distinct enantiomers in diverse clinical contexts. This thesis delves into the pharmacology of a novel S-ketamine oral and buccal thin film in Chapters 2 and 3, exploring its pharmacokinetics and pharmacodynamics, respectively. To achieve this, we employ a population pharmacokinetic/pharmacodynamic model, which integrates the changes in 3
concentration over time with the relationship between the concentration at the effect site and the intensity of the observed response, while considering multiple covariables.19 While the precise clinical indications for S-ketamine films remain undefined, our research primarily centers on evaluating its analgesic efficacy and its profile of side effects. It is conceivable that this thin film formulation may eventually find application as a potential treatment for therapy-resistant depression, akin to its intranasal counterpart. In Chapter 4, we compare the respiratory effects of oliceridine, a muopioid receptor agonist with biased characteristics, to morphine, a prototypical mu-opioid receptor agonist. The concept of biased agonism, or functional selectivity, underscores the origins of these distinctive characteristics.20 The respiratory effects of opioids are exerted via mu-opioid receptors in important brainstem respiratory centers. Upon binding to the mu-opioid receptor, opioids trigger the activation of distinct intracellular pathways. Earlier studies pointed towards the role of beta-arrestin recruitment in adverse effects of opioids, including respiratory depression.21 This understanding paved the way for the development of oliceridine, a mu-opioid receptor agonist exhibiting a pronounced bias in favor of G-protein signaling.22 The resultant net effect is an opioid that mitigates the extent of respiratory depression, offering a potential therapeutic advantage. Finally, in Chapter 5, we explore the effect of type 2 diabetes and hyperinsulinemia on ventilatory control. Only recently, a link between metabolic disorders and changes in ventilatory control has been established in animal and preclinical studies.23,24,25 These changes comprise changes in chemoreflex sensitivity, modifications in breathing patterns, and adjustments in carotid-body mediated sympathetic outflow.26,27,28 Given the increased incidence, morbidity, and mortality associated with SARS-COV-2 among individuals with type 2 diabetes, our particular interest was the ventilatory effect of hypoxia in this group of patients. The hypoxic ventilatory response is crucial in determining an individual’s predisposition to hypoxia-related pathologies. Therefore, this response was obtained in individuals with type 2 diabetes and compared to healthy controls, both during fasting conditions and under the influence of a hyperinsulinemic-euglycemic clamp. This study provides insight into the effects of metabolic dysregulation on ventilatory control. Given the large increase in patients with type 2 diabetes worldwide, this is an important study that may guide our approach to type 2 diabetics, particularly under conditions of changes in ventilatory control, such as those encountered perioperatively or following opioid administration. 4
1 Introduction Ventilatory control Two chapters in this thesis are dedicated to ventilatory control and the effect of drugs (morphine and oliceridine in Chapter 4) and type 2 diabetes (Chapter 5) on the ventilatory control system. In the field of anesthesiology, the study of ventilatory control has been of particular interest due to its implications for patient safety. Comprehending its underlying mechanisms is crucial, since disturbances in the normal respiratory rhythm generation may have severe cardiorespiratory consequences. The generation of respiratory rhythms occurs in specialized respiratory networks located in the pons and medulla. These networks receive afferent input from various sources, including the central and peripheral chemoreceptors, mechanoreceptors, and behavioral control from higher centers.29 The central chemoreceptors, dispersed in the hindbrain, sense minor changes in CO2/H+within the cerebrospinal fluid.30 The carotid bodies, the main peripheral chemoreceptors located in the fork of the carotid arteries, monitor hypoxia, hypercapnia as well as a variety of metabolic stimuli including arterial blood glucose concentrations.31 These chemoreceptors work together in an additive fashion. Upon metabolic acidosis, the input from the chemoreceptors activates the respiratory networks causing a hyperventilatory response, aimed a compensating the metabolic acidosis. A similar response is triggered by the exogenous administration of carbon dioxide, the hypercapnic ventilatory response or HCVR, and is used to determine the sensitivity of the ventilatory control system to CO2. The HCVR is particularly sensitive to the effects of opioids. In case of hypoxia, the carotid bodies are activated and a hyperventilatory response occurs that is biphasic.32 An initial acute response is followed by a slow decline, the hypoxic ventilatory decline. The secondary adaptation has a central origin, although its exact mechanism has yet to be elucidated. Apart from inducing a brisk hypoxia-induced hyperventilatory response, the carotid bodies induce an arousal response, as is observed in patients with obstructive sleep apnea. The obstruction and ensuring hypoxia stimulate the carotid bodies, causing an arousal response that clears the upper airways, followed by a short hyperventilatory response. InChapter 4, we obtain hypercapnic ventilatory responses induced by CO2 rebreathing according to the method developed by the Australian investigator D.J.C Read in the mid-1960s. Inhalation of 7% CO2 (in 93% O2) from a 46 liter rebreathing bag results in a linear increase in ventilation. We used the ventilation at an extrapolated end-tidal PCO2 of 55 mmHg as the main endpoint in our study. Recent studies from our laboratory indicate that this is the most sensitive parameter when determining the effect of drugs on ventilatory control.33 In Chapter 5, we use the more sophisticated dynamic end-tidal forcing 5
technique to obtain the ventilatory response to acute (5 min) hypoxia. This technique uses computer-controlled feedforward input to a series of mass flow controllers that allow manipulation of the inspired gas concentrations to induce a change in end-tidal gas concentration (and thus also arterial gas concentration) independent of the content of the venous return. 6
1 Introduction Study objectives The objectives of this thesis are: 1. To quantify the pharmacokinetics and pharmacodynamics (pain relief and psychomimetic adverse effects) of a novel S-ketamine oral thin film; 2. To quantify the pharmacokinetics and respiratory pharmacodynamics of the biased ligand oliceridine, in comparison to morphine; 3. Explore the effects of insulin on the hypoxic ventilatory response in type 2 diabetics compared to healthy controls. 7
1 References 1. Bainbridge D, Martin J, Arango M, Cheng D. Perioperative and anaesthetic-related mortality in developed and developing countries: a systematic review and meta-analysis. The Lancet. 2012; 380: 1075–1081 doi: 10.1016/s0140-6736(12)60990-8. 2. Nagrebetsky A, Gabriel RA, Dutton RP, Urman RD. Growth of Nonoperating Room Anesthesia Care in the United States: A Contemporary Trends Analysis. Anesthesia & Analgesia. 2017; 124: 1261–1267 doi: 10.1213/ane.0000000000001734. 3. Goel A, Rai Y, Sivadas S, Diep C, Clarke H, Shanthanna H, Ladha KS. Use of Psychedelics for Pain: A Scoping Review. Anesthesiology. 2023; 139: 523–536 doi: 10.1097/aln.0000000000004673. 4. Anand A et al. Ketamine versus ECT for Nonpsychotic Treatment-Resistant Major Depression. New England Journal of Medicine. 2023; 388: 2315–2325 doi: 10.1056/nejmoa2302399. 5. Reif A, Bitter I, Buyze J, Cebulla K, Frey R, Fu DJ, Ito T, Kambarov Y, Llorca PM, Oliveira-Maia AJ, Messer T, Mulhern-Haughey S, Rive B, Holt C von, Young AH, Godinov Y. Esketamine Nasal Spray versus Quetiapine for Treatment-Resistant Depression. New England Journal of Medicine. 2023; 389: 1298–1309 doi: 10.1056/nejmoa2304145. 6. Humphreys K, Shover CL, Andrews CM, Bohnert ASB, Brandeau ML, Caulkins JP, Chen JH, Cuellar MF, Hurd YL, Juurlink DN, Koh HK, Krebs EE, Lembke A, Mackey SC, Larrimore Ouellette L, Suffoletto B, Timko C. Responding to the opioid crisis in North America and beyond: recommendations of the Stanford-Lancet Commission. The Lancet. 2022; 399: 555–604 doi: 10.1016/S0140-6736(21)02252-2. 9
References 7. Khanna AK et al. Prediction of Opioid-Induced Respiratory Depression on Inpatient Wards Using Continuous Capnography and Oximetry: An International Prospective, Observational Trial. Anesthesia & Analgesia. 2020; 131: 1012–1024 doi: 10.1213/ane.0000000000004788. 8. Overdyk FJ, Dowling O, Marino J, Qiu J, Chien HL, Erslon M, Morrison N, Harrison B, Dahan A, Gan TJ. Association of Opioids and Sedatives with Increased Risk of In-Hospital Cardiopulmonary Arrest from an Administrative Database. PLOS ONE. 2016; 11: e0150214 doi: 10.1371/journal.pone.0150214. 9. Dahan A, Aarts L, Smith TW. Incidence, Reversal, and Prevention of Opioid-induced Respiratory Depression. Anesthesiology. 2010; 112: 226– 238 doi: 10.1097/ALN.0b013e3181c38c25. 10. Piper AJ, Grunstein RR. Big breathing: the complex interaction of obesity, hypoventilation, weight loss, and respiratory function. Journal of Applied Physiology. 2010; 108: 199–205 doi: 10.1152/japplphysiol.00713.2009. 11. Ramadan W, Dewasmes G, Petitjean M, Wiernsperger N, Delanaud S, Geloen A, Libert JP. Sleep Apnea Is Induced by a High-fat Diet and Reversed and Prevented by Metformin in Non-obese Rats∗. Obesity. 2007; 15: 1409–1418 doi: 10.1038/oby.2007.169. 12. Lecube A, Sim´o R, Pallayova M, Punjabi NM, L´opez-Cano C, Turino C, Hern´andez C, Barb´e F. Pulmonary Function and Sleep Breathing: Two New Targets for Type 2 Diabetes Care. Endocrine Reviews. 2017; 38: 550–573 doi: 10.1210/er.2017-00173. 13. S´anchez E, Sapin˜a-Beltr´an E, Gavald`a R, Barb´e F, Torres G, Sauret A, Dalmases M, L´opez-Cano C, Guti´errez-Carrasquilla L, Bermu´dez-L´opez M, Fern´andez E, Purroy F, Castro-Boqu´e E, Farr`as-Sall´es C, Pamplona R, Mauricio D, Hern´andez C, Sim´o R, and AL. Prediabetes Is Associated with Increased Prevalence of Sleep-Disordered Breathing. Journal of Clinical Medicine. 2022; 11: 1413 doi: 10.3390/jcm11051413. 14. Nalini M, Khoshnia M, Kamangar F, Sharafkhah M, Poustchi H, Pourshams A, Roshandel G, Gharavi S, Zahedi M, Norouzi A, Sotoudeh M, Nikmanesh A, Brennan P, Boffetta P, Dawsey SM, Abnet CC, Malekzadeh R, Etemadi A. Joint effect of diabetes and opiate use on all-cause and causespecific mortality: the Golestan cohort study. International Journal of Epidemiology. 2020; 50: 314–324 doi: 10.1093/ije/dyaa126. 10
1 References 15. Niesters M, Dahan A, Swartjes M, Noppers I, Fillingim RB, Aarts L, al. et. Effect of ketamine on endogenous pain modulation in healthy volunteers. Pain. 2011; 152: 656–663 doi: 10.1016/j.pain.2010.12.015. 16. Jonkman K, Dahan A, Donk T van de, Aarts L, Niesters M, Velzen M van. Ketamine for pain. F1000Research. 2017; doi: 10.12688/f1000research.11372.1. 17. Brinck E, Tiippana E, Heesen M, Bell RF, Straube S, Moore RA, Kontinen V. Perioperative intravenous ketamine for acute postoperative pain in adults. Cochrane Database of Systematic Reviews. 2018; doi: 10.1002/14651858.cd012033.pub4. 18. Bansal A, Miller M, Ferguson I, Burns B. Ketamine as a Prehospital Analgesic: A Systematic Review. Prehospital and Disaster Medicine. 2020; 35: 314–321 doi: 10.1017/s1049023x20000448. 19. Olofsen E, Dahan A. Population pharmacokinetics/pharmacodynamics of anesthetics. The APPS Journal. 2005; 7: E383–9 doi: 10.1208/aapsj070239. 20. Smith JS, Lefkowitz RJ, Rajagopal S. Biased signalling: from simple switches to allosteric microprocessors. Nature Reviews Drug Discovery. 2018; 17: 243–260 doi: 10.1038/nrd.2017.229. 21. Raehal KM, Walker JKL, Bohn LM. Morphine side effects in -arrestin 2 knockout mice. J Pharmacol Ther. 2005; 314: 1195–2001 doi: 10.1124/jpet.105.087254. 22. Stahl EL, Bohn LM. Low intrinsic efficacy alone cannot explain the improved side effect profiles of new opioid agonists. Biochem. 2021; doi: 10.1021/acs.biochem.1c00466. 23. Ribeiro MJ, Sacramento JF, Gonzalez C, Guarino MP, Monteiro EC, Conde SV. Carotid body denervation prevents the development of insulin resistance and hypertension induced by hypercaloric diets. Diabetes. 2013; 62: 2905– 16 doi: 10.2337/db12-1463. 24. Cunha-Guimaraes JP, Guarino MP, Timoteo AT, Caires I, Sacramento JF, Ribeiro MJ, Selas M, Santiago JCP, Mota-Carmo M, Conde SV. Carotid body chemosensitivity: early biomarker of dysmetabolism in humans. European Journal of Endocrinology. 2020; 182: 549–557 doi: 10.1530/EJE-19-0976. 11
References 25. Sacramento JF, Chew DJ, Melo BF, Donega M, Dopson W, Guarino MP, Robinson A, Prieto-Lloret J, Patel S, Holinski BJ, Ramnarain N, Pikov V, Famm K, Conde SV. Bioelectronic modulation of carotid sinus nerve activity in the rat: a potential therapeutic approach for type 2 diabetes. Diabetologia. 2018; 61: 700–710 doi: 10.1007/s00125-017-4533-7. 26. Lecube A, Sampol G, Hern´andez C, Romero O, Ciudin A, Sim´o R. Characterization of Sleep Breathing Pattern in Patients with Type 2 Diabetes: Sweet Sleep Study. PLOS ONE. 2015; 10: e0119073 doi: 10.1371/journal.pone.0119073. 27. Guti´errez-Carrasquilla L, L´opez-Cano C, S´anchez E, Barb´e F, Dalmases M, Hern´andez M, Campos A, Gaeta AM, Carmona P, Hern´andez C, Sim´o R, Lecube A. Effect of Glucose Improvement on Nocturnal Sleep Breathing Parameters in Patients with Type 2 Diabetes: The Candy Dreams Study. Journal of Clinical Medicine. 2020; 9: 1022 doi: 10.3390/jcm9041022. 28. Sacramento JF, Andrzejewski K, Melo BF, Ribeiro MJ, Obeso A, Conde SV. Exploring the Mediators that Promote Carotid Body Dysfunction in Type 2 Diabetes and Obesity Related Syndromes. International Journal of Molecular Sciences. 2020; 21: doi: 10.3390/ijms21155545. 29. Feldman JL, Mitchell GS, Nattie EE. Breathing: rhythmicity, plasticity, chemosensitivity. Annual Review of Neuroscience. 2003; 26: 239–66 doi: 10.1146/annurev.neuro.26.041002.131103. 30. Nattie E, Li A. Central chemoreceptors: locations and functions. Comprehensive Physiology. 2012; 2: 221–54 doi: 10.1002/cphy.c100083. 31. Lopez-Barneo J. Neurobiology of the carotid body. Handbook of Clinical Neurology. 2022; 188: 73–102 doi: 10.1016/B978-0-323-91534-2.00010-2. 32. Pamenter ME, Powell FL. Time Domains of the Hypoxic Ventilatory Response and Their Molecular Basis. Comprehensive Physiology. 2016; 6: 1345–1385 doi: 10.1002/cphy.c150026. 33. Hellinga M, Algera MH, Schrier R van der, Sarton E, Velzen M van, Dahan A, Olofsen E, Niesters M. A Biomarker of Opioid-induced Respiratory Toxicity in Experimental Studies. iScience. 2023; 24: 106520 doi: 10.1016/j.isci.2023.106520. 12
2 Chapter 2 S-ketamine oral thin film – Part I: population pharmacokinetics of S-ketamine, S-norketamine and S-hydroxynorketamine Pieter Simons1, Erik Olofsen1, Monique van Velzen1, Maarten van Lemmen1, Ren´e Mooren1, Tom van Dasselaar1, Patrick Mohr2, Florian Hammes2, Rutger van der Schrier1, Marieke Niesters1, Albert Dahan13 Front Pain Res (Lausanne) 2022; 3:946486 1. Department of Anesthesiology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands 2. LTS Lohmann Therapie-Systeme AG, Andernach, D-56626 Germany 3. PainLess Foundation, Leiden, the Netherlands 13
Introduction Over the last decade, low-dose ketamine has gained in popularity for treatment of chronic pain and therapy-resistant depression.1 Since its discovery in the early 1960s, ketamine has been administered mostly via the parenteral route for the induction of anesthesia and procedural sedation. With a broader range of indications and pre-hospital and out-of-hospital use of ketamine, the need for skilled venipunctures is a hurdle for chronic and repeated ketamine administrations. To overcome this problem, different routes of ketamine administration have been studied extensively, including inhaled, oral, sublingual, nasal, subcutaneous, intramuscular and rectal administrations. All of these routes have advantages, such as simplicity of administration, and drawbacks. For example, oral dosing results in slow absorption and is largely subject to intestinal and first-pass metabolism, with unpredictable bioavailability (7-25%). Others, such as the subcutaneous or intramuscular administration routes, are invasive and also result in a relatively slow absorption.2,3 Here we study the pharmacokinetics (and in part 2 of this study,4 the pharmacodynamics) of sublingual and buccal fast-dissolving oral-thin-films (OTFs) that contain 50 mg of S-ketamine, one of the stereoisomers of ketamine. In this report, we present the results of a pharmacokinetic analysis of the concentration-time curves following sublingual or buccal administration of 50 mg or 100 mg S-ketamine OTF in healthy volunteers. Apart from the simplicity of application, the use of an S-ketamine OTF may, depending on its bioavailability and first-pass effect, be advantageous in the treatment of pain and depression. An acceptable level of S-ketamine bioavailability will make it suitable for pain treatment in an acute setting,2,5 while a large first-pass effect with high concentrations of hydroxynorketamine will make the S-ketamine OTF an interesting alternative for the management of therapy-resistant depression as there is evidence that this metabolite is a potent antidepressant.6,7 We performed a population pharmacokinetic analysis of the S-ketamine OTF in healthy volunteers, and considered the parent compound and its metabolites, S-norketamine and S-hydroxynorketamine in the analysis. 14
2 S-ketamine oral thin film pharmacokinetics Methods Ethics and Subjects The protocol was approved by the Central Committee on Research Involving Human Subjects (Competent authority: Centrale Commissie Mensgebonden Onderzoek (CCMO), The Hague, the Netherlands; registration number NL75727.058.20) and the Medical Research Ethics Committee at Leiden University Medical Center (Medische Ethische Toetsingscommissie LeidenDen Haag-Delft, the Netherlands; identification number P20.111). The study was registered at the trial register of the Dutch Cochrane Center (www.onderzoekmetmensen.nl) under identifier NL9267 and at the European Union Drug Regulating Authorities Clinical Trials (EudraCT) database under number 2020-005185-33. All procedures were performed in compliance with the latest version of the Declaration of Helsinki and followed Good Clinical Practice guidelines. Healthy male and female volunteers, aged 18-45 years and with a body mass index ≥19 kg/m2 and ≤30 kg/m2, were recruited. After recruitment, all subjects gave written and oral informed consent, after which they were screened. Additional inclusion criteria were the ability to communicate with the research staff, non-smoking for at least 3 months prior to screening, and deemed suitable by the investigators. Exclusion criteria included: presence or history of any medical or psychiatric disorder (including a history of substance abuse, anxiety, or a chronic pain syndrome), use of medication in the three months prior to screening (including vitamins and herbs, excluding oral contraceptives), use of more than 21 units of alcohol per week, use of illicit substances (including cannabis) in the 4 weeks prior to the study, a positive urine drug test or an alcohol breath test at screening or on the morning of test drug dosing, pregnancy, lactating or a positive pregnancy test at screening or on the morning of dosing, participation in another (drug) trial in the 60 days prior to dosing. Eating, drinking, tooth brushing or gum chewing was not allowed on the morning of oral thin film application to avoid changes/variabilities in saliva pH, which could potentially affect the mucosal permeability and S-ketamine uptake. Study Design S-Ketamine Oral Thin Film Placement – Randomization – Intravenous S-ketamine Infusion This phase 1 study had an open-label randomized crossover design. The subjects were randomized to receive one oral thin film on one occasion (50 mg S-ketamine) and two on another visit (100 mg S-ketamine) with at least 7 days between visits. The thin film is a rectangular 4.5 cm2 orodispersible 15
film containing 57.7 mg S-ketamine hydrochloride (S-ketamine HCL). The Sketamine HCL is dispersed within a matrix to produce a film corresponding to 50 mg S-ketamine free base. The film(s) was/were placed either under the tongue or buccally on the mucosa. After placement of the films, the subject was not allowed to swallow for 10 min. The randomization sequence was determined by the randomization option in the Electronic Data Capture system CASTOR (www.castoredc.com). The oral thin films were provided by LTS Lohmann Therapie-Systeme AG (Andernach, Germany) and were dispensed by the hospital trial pharmacy on the morning of dosing. To calculate the bioavailability of the OTF, six hours after placement of the oral thin film, all subjects received an intravenous S-ketamine (Ketanest-S, Pfizer, the Netherland) infusion of 20 mg over 20 min. The intravenous dose of 20 mg given was based on a previous study on the pharmacokinetics of inhaled Sketamine in which a 20 mg intravenous dose was administered over 20 min. This dose was well accepted by the volunteers.8 We waited 6 h before giving the intravenous dose to ensure that most of the pharmacodynamic effects (i.e. the topic of our accompanying paper)4 had dissipated. Blood Sampling and S-Ketamine Measurement Blood samples were obtained at t = 0 (= oral thin film placement) 5, 10, 20, 40, 60, 90, 120, 180, 240, 300, 360 min, and at the following time periods following the start of the intravenous administration: 2, 4, 10, 15, 20, 30, 40, 60, 75, 90 and 120 min. 3-mL samples were obtained from a 22G arterial line placed in the radial artery of the non-dominant arm and collected in lithium heparin tubes. All heparin samples were centrifuged at 1,500 g for 10 min, within 15 min after withdrawal and plasma was separated and stored in two aliquots at -80 oCuntil analysis. For analysis the samples were thawed and 200 µL was transferred into glass tubes and 10 µL internal standard was added. After mixing, 250 µL buffer was added. After again mixing, 4 mL methyl-tertiair-butylether followed by 15 min and 15 min centrifugation. The upper organic layer was pipetted into another tube that contained 0.6 mL of 0.4 mol/L hydrochloric acid in methanol, and dried under a gentle stream of nitrogen at 35 oC. The residue was re-dissolved in 100 µL mobile phase (6.8 % methanol in water with 0.1 % formic acid) by vortexing and ultrasonication for 3 min and 5 µL sample was injected on the chromatographic system with a C18 column. All reference standards (ketamine and norketamine) and internal standards ketamine-D4 (K-D4), norketamine-D4 (NK-D4) were HCl salts and purchased from LGC Standards GmbH (Germany); cis-6-hydroxynorketamine (6-HNK) was purchased from Syncom BV (the Netherlands); and the internal standard hydroxy- norketamine-13C6 (HNK-13C6) was purchased from Alsachim SAS (France). 16
2 S-ketamine oral thin film pharmacokinetics S-ketamine and its metabolites, S-norketamine and S-hydroxynorketamine, were measured at the Department of Pharmacy and Toxicology using liquid chromatography coupled to QTOF-MS (hybrid quadrupole time-of-flight mass spectrometry) as detection technique (i.e. LC-QTOF- MS/MS). The LCQTOF-MS/MS system consisted of a Thermo Scientific double pump 3000 gradient system gradient with Bruker IL-2 QTOF.A column (Xterra MS C18 3.5µm x 2.1 mm x 100 mm) and precolumn (Xterra MS C18 Vanguard cartridge 3.5 µm x 2.1 mm) and was purchased from Waters Chromatography Europe BV (the Netherlands). For separation the mobile phase was methanol/water with 0.1 % formic acid with a gradient from 6.8-96 % methanol from 1 until 8.5 min. The total separation time was 15 min with a flow rate of 0.3 ml/min. The eluent was directed to the QTOF-MS from 1.2 until 7 min while the other part was directed to waste by a valve to avoid contamination of the QTOF. The system was controlled by Chromeleon Chromatography Data System software (Thermo Fisher Scientific, the Netherlands) for the LC part and Hystar (Bruker Nederland BV, the Netherlands) for the QTOF/MS part. In the positive ionization mode, the masses of the M+H ions were respectively 224.084, 228.109, 238.0993, 242, 124, 240.0786 and 246.099 Da for norketamine, norketamine-D4, ketamine, ketamine-D4, Cis-6-hydroxynorketamine and hydroxynorketamine13C6. Quant Analysis (Bruker Nederland BV, the Netherlands) was used for quantification of all analytes with a weighed (1/X*X) calibration line. The lower limits of quantitation were 6 ng/ml (0.025 nmol/mL), 6 ng/ml (0.026 nmol/mL) and 4 ng/ml (0.01 nmol/mL), for S-ketamine, S-norketamine and S-hydroxynorketamine, respectively. The upper limits of quantitation were, respectively, 500 ng/ml (2.1 nmol/ml), 1,000 (4.4 nmol/ml) and 200 ng/mL (0.72 nmol/ml) for S-ketamine, S-norketamine and S-hydroxynorketamine. Adverse Events Reported adverse events related to treatment were collected and were split up into events related to the 50 or 100 mg oral thin film or to the intravenous administration of S-ketamine. Additionally, the subjects were queried for dissociative side effects using the Bowdle questionnaire.9 TheBowdle questionnaire allows derivation of three factors of psychedelic ketamine effects: drug high and changes in internal and external perception. All three were measured on a visual analog score from 0 (no effect) to 10 cm (maximum effect). The questionnaire was first published in 1998 as a hallucinogen rating scale to quantify ketamine-induced psychedelic symptoms in volunteers and has been used in multiple studies on the effect of various psychedelics on dissociative symptoms. Blood pressure was obtained from the arterial-line using the FloTrac and Hemosphere system (Edwards Lifesciences, Irvine USA). 17
Population Pharmacokinetic Analysis Data analysis was performed using NONMEM version 7.5.0 (ICON Development Solutions, Hanover, MD, USA). To account for the differences in molecular weight between S-ketamine and the metabolites, concentration data were converted from ng/ml to nmol/ml. Data were analyzed in a stepwise fashion. First, S-ketamine data were analyzed, followed by the addition of S-norketamine and subsequently S-hydroxynorketamine. The routing of S-ketamine consists of two parts: one direct pathway from the OTF into plasma, and one indirect pathway in which some S-ketamine is stored in saliva which is ingested and absorbed via the gastrointestinal tract. Since S-norketamine was not administered, theoretically, the volume of the central S-norketamine compartment (VN1) was not identifiable. However, since we assumed that 80% of S-ketamine was metabolized VN1 is identifiable.2 The same applies for S-hydroxynorketamine: since we assumed that 70% of Snorketamine is transformed into S-hydroxynorketamine,10 the volume of the central S-hydroxynorketamine compartment is identifiable. The number of Sketamine, S-norketamine and S-hydroxy-norketamine compartments as well as the intermediary metabolism compartments was determined by goodness-of-fit criteria, i.e., a significant decrease in objective function value (OFV) calculated as -2 log likelihood (χ2 test), visual inspection of the data fits and goodness-offit plots (normalized prediction distribution error vs time plots, normalized prediction distribution error vs predicted plots, and predicted vs measured plots). Moreover, prediction-variance-corrected visual predictive checks (VPCs) were performed by simulating 1,000 data sets based on the model parameters and comparing the simulated quantiles with those of the true data. P <0.01 were considered significant. FOCE-I (first-order conditional estimation with interaction) was used to estimate model parameters. To account for inter-individual and inter-occasion variability (IOV), random effects were included in the model with an exponential relation: θi=θ×exp(ηi+ηiov), where θi is the parameter for individual i, θ is the population parameter, ηi is the random difference between the population and individual parameter, and ηiov is the difference between θi and θ as a result of IOV. In addition, proportional and additive errors were evaluated for each separate analyte to account for residual variability. The proportional and combined proportional and additive error models were described by Yij =Pij × (1+ϵij) and Yij =Pij×(1+ϵ1ij )+ϵ2ij , respectively, where Yij is the jth observed plasma concentration for individual i, Pij is the corresponding model prediction, and ϵij is the residual error. Inter-occasion variability was determined for the S-ketamine and S-norketamine absorption parameters, while it was determined for all S-hydroxynorketamine model parameters. 18
2 S-ketamine oral thin film pharmacokinetics Simulations In-silico simulations were performed to determine the effect of changes in the duration that the 50 mg S-ketamine oral thin film stayed sublingually (before the subjects was allowed to swallow) on plasma concentrations of S-ketamine and its metabolites. To that end, factor D1 was either increased or decreased by a factor (F) of 2, F1 was adjusted assuming it converges to 1 exponentially with D1 (i.e. F1 approaches 1 in case the OTF remains sublingually and is not swallowed), F2 was adjusted so that total bioavailability remains constant, and changes in D2 followed changes in D1 assuming D2 is the sum of D1 and gastrointestinal lag times. D1 is the duration of absorption, D2 is the duration of absorption from the gastrointestinal tract. F1 and F2 are the S-ketamine bioavailability from the oral mucosa and gastrointestinal tract, respectively. 19
Results Twenty-three subjects were screened, of which three subjects were excluded from participation because of psychological issues (n = 2) or earlier alcohol abuse (n = 1). Twenty subjects were dosed at least once (see Table 2.1 for their demographic characteristics), 19 subjects were dosed twice (once OTF with 50 mg S-ketamine, once with 100 mg S-ketamine). Table 2.1: Subject characteristics Characteristic Total population Sublingual OTF Buccal OTF n =20 n = 15 n = 5 Age (yr) ±SD 24 ±3 24 ±3 25 ±5 (range) (19-32) (21-30) (19-32) Sex (M/F n) 10/10 8/7 2/3 Mean weight (kg) ±SD 73 ±12 72 ±13 74 ±8 (range) (53-93) (53-93) (64-85) Mean height (cm) ±SD 179 ±10 179 ±12 177 ±6 (range) (161-197) (161-197) (170-183) Mean BMI (kg/m2) ±SD 23 ±2 22 ±2 24 ±3 (range) (19-27) (19-27) (21-27) BMI = body mass index 20
2 S-ketamine oral thin film pharmacokinetics One subject declined further participation after completing the first session, receiving 100 mg S-ketamine OTF sublingually, due to psychotomimetic side effects that occurred during the intravenous S-ketamine infusion. The mean and individual S-ketamine, S-norketamine and S-hydroxynorketamine data for both the sublingual and buccal OTF and intravenous infusion are given in Figure 2.1 on page 22. Since no differences were observed in plasma concentrations for the sublingual (n = 15) or buccal (n =5) locations of the OTF (individual data in Figure 2.1 panels D-I with in red buccal administration and in black sublingual administration) and in the subject characteristics (Table 2.1), we merged the two subgroups in the pharmacokinetic model analyses. Peak concentration (CMAX), time of peak concentration (TMAX) and area-under-the-concentrationtime curves (AUC) of S-ketamine and its metabolites are given in Table 2.2 on page 23. These data indicate that increasing the S-ketamine OTF dose produces dose a dependent increase in CMAXfor S-ketamine and its metabolites, with a delay in CMAX for the downstream metabolites. Comparing these data to the values observed after the intravenous S-ketamine in Figure 1, panels A-C, administration indicate the greater metabolism of the S-ketamine from the OTF compared to the 20 mg intravenous S-ketamine. Peak S-ketamine concentrations after the intravenous infusion were 273 (259-287) ng/mL (mean (95% confidence interval)) after treatment with the 50 mg S-ketamine OTF and 260 (251-269) ng/mL after treatment with the 100 mg S-ketamine OTF (Figure 2.1). 21
Figure 2.1: Mean measured plasma concentrations following application of the 50 and 100 mg S-ketamine oral thin film (OTF): (A) S-ketamine, (B) S-norketamine and (C) S-hydroxynorketamine. Individual concentrations are given in panels D-F for the 50 mg oral thin film, and G-I for the 100 mg oral thin film. In black the results of placement below the tongue, in red buccal placement. The OTF was administered at t = 0 min for 10 min (green bars); at t = 360 min, an intravenous dose of 20 mg S-ketamine was administered over 20 min (light orange bars). 22
2 S-ketamine oral thin film pharmacokinetics Table 2.2: Peak concentration (CMAX), time of CMAX (TMAX), and areaunder-the time-concentration curve (AUC) of S-ketamine, S-norketamine and Shydroxynorketamine following 50 and 100 mg S-ketamine oral thin film (OTF). 50mg S-ketamine OTF 100mg S-ketamine OTF S-ketamine CMAX (ng/ml) 96 (81 – 111) 144 (127 – 161) CMAX (nM) 420 (360 – 480) 600 (500 – 700) TMAX (min) 18.8 (16.6 – 21.2) 19.1 (17.1 – 21.2) AUC (0-6 h) (ng/ml.min) 8,363 (7,263 – 9,464) 13,347 (11,933 – 14,760) S-norketamine CMAX (ng/ml) 276 (243-308) 426 (362-489) CMAX (nM) 1,130 (970 – 1300) 1,475 (1,122 – 2,237) TMAX (min) 61 (53-68) 78 (66-91) AUC (0-6 h) (ng/ml.min) 38,497 (34,131 – 42,863) 67,959 (60,045 – 75,872) S-hydroxynorketamine CMAX (ng/ml) 101 (89 – 115) 189 (160 – 218) CMAX (nM) 340 (293 – 387) 619 (594 – 644) TMAX (min) 81 (69-92) 109 (89 – 130) AUC (0-6 h) (ng/ml.min) 24,087 (20,694 – 27,480) 44,972 (38,563 – 51,382) Values are mean (±95% confidence interval). Adverse Events Eighteen subjects reported at least one adverse event. In total, there were 97 adverse events. None were serious adverse events. See for the prevalence of events Table 2.3 on page 24. We relate one adverse event (numbness of the tongue) directly to the application of the oral thin film, the remaining events were drug-associated. All subjects experienced dissociative side effects (drug high, changes in internal and external perception) as derived from the Bowdle questionnaire. The accompanying paper on the OTF pharmacodynamic effects presents these data in detail.4 During the first hour after application of the OTF, blood pressure increased with mean arterial pressure 92 ±11 mmHg (mean ± SD), 97 ±7 mmHg and 104 ±6 mmHg at baseline (prior to application) and 10 and 60 min after the application of the 50 mg S-ketamine OTF, respectively, and 95 ±15 mmHg, 97 ±11 mmHg and 108 ±10 mmHg at baseline and 10 and 60 min after the application of the 100 mg S-ketamine OTF. 23
Table 2.3: Adverse effects 50mg S-ketamine OTF 100mg S-ketamine OTF 20mg S-ketamine Intravenous Blurred vision 1 Feeling drunk 2 Bradykinesia 1 1 Whistling sound in the ears 1 Vertigo/dizziness 1 3 4 Drowsiness 3 Nausea 1 1 2 Headache 1 2 3 Numbness of the tongue 2 Hypertension (SBP>180mmHg) 2 Perspiration 1 Dry eyes 1 Dissociative effects* 20 20 20 Total 27 29 37 * Dissociative effects included drug high and changes in internal and external perception. 24
2 S-ketamine oral thin film pharmacokinetics Population Pharmacokinetic Analysis The schematic diagram of the final pharmacokinetic model of the absorption of S-ketamine from the OTF and disposition of S-ketamine, with three compartments, and its metabolites S-norketamine and S-hydroxynorketamine, with each 2 compartments, is given in Figure 2.2 on page 26. Model parameter estimates are given in Table 2.4 on page 27; S-ketamine and S-norketamine distribution- and clearance-related parameters are in close correspondence with earlier data derived from a pooled-analysis of data from the literature.11 Gastrointestinal absorption of S-ketamine and the metabolism of S-ketamine andS-norketamine were best described by two delay or metabolism compartments. The model parameters given in Table 2.4 are explained in Figure 2.2. All pharmacokinetic data fits are presented in Supplementary Figure 1 online; the goodness-of-fit plots (individual predicted concentration vs. measured concentration; individual weighted residuals over time; normalized prediction discrepancy errors) are given in Figure 2.3 on page 30. Inspection of these plots together with the individual data fits indicate that the final model adequately described the plasma concentration-time data of S-ketamine and its two measured metabolites. The bioavailability of S-ketamine from the OTF was 26.3 ± 1.0%, with a duration of absorption (D1) of 13 min and an absorption rate constant of 0.04 min-1 (KA1), with one outlier (subject #4) who had a KA1 value of 0.012 min-1. The bioavailability for the 50 mg and 100 mg OTF differed by about 20% (F1 50 mg = 29%, F1 100 mg = 23%), but this did not reach the level of significance (p ≈0.01). The S-ketamine that was not absorbed in the mouth was ingested and was absorbed in the remainder of the gastrointestinal system into the portal vein. This process was modeled by two delay compartments defined by an absorption rate constant KA2 and a mean transit time (MTTG, Figure 2.4. The gastrointestinal absorption (F2) took 30 min. Around 75% of the initial amount of S-ketamine was directly metabolized into S-norketamine without participating in the distribution of S-ketamine in the systemic circulation. Metabolism into S-norketamine was modeled by two delay compartments with the delay defined by two mean transit times (MTT K →NK, Table 2.2 and Figure 2.2), which has a population value of around 20 min (again with outlier subject #4 who had a value of 9 min). Twenty percent of S-ketamine was not metabolized into S-norketamine but was either metabolized into other metabolites (e.g. hydroxyketamine) or was lost in the gut. S-norketamine was metabolized into S-hydroxynorketamine via two metabolism compartments with the delay defined by two mean transit times (NK→HNK, Table 2.2 and Figure 2.2), which had a population value of around 1 min. Thirty percent of S-norketamine was not metabolized into S-hydroxynorketamine but was metabolized to other metabolites such as S-dehydronorketamine. 25
Figure 2.2: Final pharmacokinetic model. K = S-ketamine, N = S-norketamine and H=S-hydroxynorketamine. KA1 and KA2 are S-ketamine rate constants. G.I. tract = gastrointestinal tract. Cp = plasma concentration. K1, N1 and H1 are the central compartments for S-ketamine, S-norketamine and S-hydroxynorketamine, respectively. VN1 and VK1 are the volumes of the central compartments of S-ketamine and S-norketamine, respectively. Kx, Nx and Hx are the peripheral compartments for S-ketamine, S-norketamine and S-hydroxynorketamine, respectively, with x = compartment 2 or 3. CL = clearance with CLK1 and CLN1 S-ketamine and S-norketamine clearances from the central compartment towards the metabolism compartment, respectively and CLK2, CLK3, CLN2 and CLH2 intercompartmental clearances. CLH1 is the terminal S-hydroxynorketamine clearance. MTT = mean transit (or delay) time with MTTG the mean transit time from the gut to the liver. 26
2 S-ketamine oral thin film pharmacokinetics Table 2.4: S-ketamine OTF pharmacokinetics Parameter Estimate SEE Inter-subject variability (ω2) SEE Inter-occasion variability (ν2) SEE S-ketamine mucosal absorption from OTF F1 (bioavailability) % 26.3 1.2 0.060 0.019 D1 (duration of absorption) min 13.1 1.0 0.154 0.033 Absorption rate constant; KA1 (min-1) 0.04 0.002 0.062 0.014 Outlier (id = 4, occ = 2) for KA1 (min-1) 0.012 0.0004 Volume of S-ketamine compartment 1; VK1 (L @ 70 kg) 11.6 0.9 0.057 0.019 Volume of S-ketamine compartment 2; VK2 (L @ 70 kg) 39.0 2.9 Volume of S-ketamine compartment 3; VK3 (L @ 70 kg) 174 11 Clearance from VK1 towards metabolism compartment MK; CLK1 (L/min @ 70 kg) 1.48 0.06 0.029 0.012 Clearance from VK1 to VK2; CLK2 (L/min @ 70 kg) 2.43 0.24 Clearance from VK1 to VK3; CLK3 (L/min @ 70 kg) 1.21 0.08 0.026 0.014 sRelative (relative within subject variability) 0.012 0.0004 S-ketamine absorption from the gastrointestinal tract F2 (bioavailability) % 116 6 0.057 0.031 D2 (duration of infusion) min 29.9 3.5 0.611 0.120 Absorption rate constant; KA2 (min-1) 0.049 0.007 0.376 0.150 Mean transit time GUT (min) 10.7 1.7 0.937 0.312 27
Table 2.4 continued from previous page Parameter Estimate SEE Inter-subject variability (ω2) SEE Inter-occasion variability (ν2) SEE S-norketamine Volume of S-norketamine compartment 1; VN1 11.6 0.9 0.057 0.019 11.6 Volume of S-norketamine compartment 2; VN2 (L @ 70 kg) 221 13 Clearance of S-norketamine compartment 1; CLN1 (L/min @ 70 kg) 1.00 0.04 0.050 0.012 Clearance of S-norketamine compartment 2; CLN2 (L/min @ 70 kg) 2.63 0.15 Mean transit time K®NK (min) 20.1 1.0 0.021 0.122 Outlier mean transit time (id = 4) (min) 8.72 0.19 sRelative (relative within-subject variability) 0.102 0.007 sAdditive (additive within-subject variability) 0.058 0.018 0.751 0.349 S-hydroxynorketamine Volume of S-hydroxynorketamine compartment 1; VH1 (L @ 70 kg) 4.4 2.0 1.22 0.91 Volume of S-hydroxynorketamine compartment 2; VH2 (L @ 70 kg) 87.5 6.5 0.152 0.031 Clearance of S-hydroxynorketamine compartment 1; CLH1 (L/min @ 70 kg) 0.933 0.068 0.103 0.042 0.008 0.004 Clearance of S-hydroxynorketamine compartment 2; CLH2 (L/min @ 70 kg) 1.70 0.25 0.287 0.124 28
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