Abstract
Non-human animal studies outline precise mechanisms of central mu-opioid regulation of pain, stress, affiliation and reward processing. In humans, pharmacological blockade with non-selective opioid antagonists such as naloxone and naltrexone is typically used to assess involvement of the mu-opioid system in such processing. However, robust estimates of the opioid receptor blockade achieved by opioid antagonists are missing. Dose and timing schedules are highly variable and often based on single studies. Here, we provide a detailed analysis of central opioid receptor blockade after opioid antagonism based on existing positron emission tomography data. We also create models for estimating opioid receptor blockade with intravenous naloxone and oral naltrexone. We find that common doses of intravenous naloxone (0.10-0.15 mg/kg) and oral naltrexone (50 mg) are more than sufficient to produce full blockade of central MOR (>90% receptor occupancy) for the duration of a typical experimental session (∼60 minutes), presumably due to initial super saturation of receptors. Simulations indicate that these doses also produce high KOR blockade (78-100%) and some DOR blockade (10% with naltrexone and 48-74% with naloxone). Lower doses (e.g., 0.01 mg/kg intravenous naloxone) are estimated to produce less DOR and KOR blockade while still achieving a high level of MOR blockade over ∼30 minutes. The models and simulations form the basis of two novel web applications for detailed planning and evaluation of experiments with opioid antagonists. These tools and recommendations enable selection of appropriate antagonists, doses and assessment time points, and determination of the achieved receptor blockade in previous studies.
1. Introduction
A variety of psychological processes are thought to be modulated by the brain’s muopioid system, including reward [1], pain [2], stress [3], and social bonding [4,5]. In studies with human participants, researchers are probing the mu-opioid system through naturally occurring variation in the mu-opioid receptor gene [6] and functional imaging of mu-opioid receptor availability with positron emission tomography (PET; [7]). These methods are however very costly due to the need for large samples (e.g., candidate gene studies) or specialized radiolabeling setups (e.g., PET). A popular method to study the mu-opioid system in humans is the pharmacological blockade of opioid receptors with antagonistic drugs. Opioid receptor antagonists bind opioid receptors, but in contrast to agonists they do not generally produce a response by the cell (although some, e.g., naloxone, may act as inverse agonists under certain conditions [8]). Opioid antagonists such as naloxone and naltrexone have a high affinity to muopioid receptors (MOR) and thereby prevent other ligands (including endogenous ones) from binding to this receptor type. Therefore, when antagonism with these drugs blocks a behavior, the behavior is assumed to be mu-opioid-dependent [9]. Most opioid antagonists available for human use are non-selective for opioid receptor subtypes and also bind to kappa-opioid receptors (KOR) with high affinity and to delta-opioid receptors (DOR) with low affinity (Table 1). To enable causal inferences about mu-opioid receptor functions based on pharmacological blockade, it is optimal to select an antagonist, a dose, and an assessment time point that results in complete blockade of MOR while causing minimal interference with other receptor types.
Affinities of the opioid antagonists naloxone and naltrexone to cloned human opioid receptors expressed on Chinese hamster ovary (CHO) cells.
PET and dual-detector systems quantify in vivo receptor binding in the human brain and can be used to estimate opioid receptor blockade with non-selective opioid antagonists. Quantification of receptor binding with these techniques works by injecting a radiotracer; a ligand that binds to the target receptors in the brain and that has been labelled with a radioactive isotope. Receptor binding results in accumulation of the radiotracer in the brain. Positron emission from the radioactive isotope can then be recorded through detection of gamma rays produced by electron-positron annihilation [16–18]. Administration of an antagonist prevents the radiotracer from binding to the receptors, resulting in less accumulation of the radiotracer and fewer detected gamma rays.
Antagonist doses used in basic human research to block the mu-opioid system are often based on plasma concentration, estimates from single PET studies, or on conventions (e.g., 0.10-0.15 mg/kg intravenous naloxone and 50 mg oral naltrexone), and they vary considerably. For example, reported intravenous naloxone doses used in studies of endogenous mu-opioid function are as low as 0.006 mg/kg [19] and as high as 6 mg/kg [20]. Concurrent KOR and DOR blockade is seldom considered when selecting doses. Here we synthesize the available PET and dual-detector data and create models for estimating the amount and duration of central opioid receptor blockade with various doses of commonly used opioid antagonists. In line with previous interpretations of blockade estimates, we define full blockade as >90% receptor occupancy [21,22]. This overview will help determine the achieved MOR blockade in previous studies and evaluate the possibility of DOR and KOR blockade or carry-over effects affecting the results or complicating inferences. It will also enable selection of the appropriate antagonist drugs, doses, assessment time points and intersession intervals for future studies.2.
2. Methods
2.1. Procedure
We synthesized and further analyzed the available evidence from PET and dual-detector studies on opioid receptor blockade with naloxone and naltrexone. Studies containing blockade data were located using a semi-systematic approach, based on Web of Science searches (see Appendix) and examination of references in relevant papers. For naloxone, the shortest-acting antagonist with the widest variety of reported doses and test schedules, we first created a log-logistic dose-response curve to map intravenous doses to MOR blockade estimates. For this model, data from 45-65 minutes post-naloxone infusions were used. A dose-response curve for oral naltrexone based on data obtained within 8 hours of administration was available from Rabiner et al. [23].
In a second step, we modeled the MOR blockade-time profile of naloxone. First, we used the reported blockade half-life in the brain with naloxone to estimate the exponential decay of receptor occupancy over time and across doses. Next, we adjusted the model to reflect the initial absorption phase (i.e., distribution to the brain) indicated by data on the time-to-peak blockade with intravenous naloxone.
Finally, due to limited availability of PET and dual-detector data, we simulated dose-response curves for KOR and DOR blockade with naloxone and naltrexone. These simulations used MOR blockade data and relative opioid receptor affinities from studies of human opioid receptors expressed on Chinese hamster ovary (CHO) cells (see e.g., [24]). Simulation-based estimates were compared to the available PET and dual-detector data on DOR and KOR blockade with naloxone and naltrexone.
The available data on central opioid receptor blockade with nalmefene and GSK1521498 are summarized in the appendix.
3. Results
3.1. Naloxone
3.1.1. Mu-opioid receptor blockade with intravenous naloxone
Two PET [17,21] and two dual-detector studies [25,26] have quantified MOR blockade with intravenous naloxone. In these studies, a target dose of naloxone is first injected intravenously. Five minutes later, participants receive an intravenous injection of radiolabeled [11C]carfentanil, and positron emission from the brain is recorded for 60 minutes. The signal in the thalamus is used to calculate MOR blockade since this brain region has a very high density of mu-opioid receptors [27]. Blockade estimates in both types of studies are corrected for non-specific binding (i.e., non-receptor binding). PET studies use the radiotracer signal in the occipital lobe as a reference for non-specific binding when correcting the blockade estimates [21] due to the small number of MOR in this region [27]. In contrast, dual-detector studies use the thalamic radiotracer signal under 1.0 mg/kg intravenous naloxone as reference for non-specific binding because PET studies suggest that this dose is sufficient to block nearly all MOR in the thalamus [17,21].
Due to the highly standardized protocol used across these studies, the data are suitable for quantitative synthesis. Based on blockade estimates from PET and dual-detector studies with [11C]carfentanil and intravenous naloxone (Table 2), and additional timing information from a PET study with intranasal naloxone [28], we created a model for estimating the level and duration of MOR blockade in the human brain achieved with various doses of intravenous naloxone.
Overview of positron emission studies reporting estimates of mu-opioid receptor blockade with intravenous naloxone. Together with additional timing information (time-to-peak blockade and blockade half-life), these data form the basis of the model.
Model specification and fitting was performed in R [29] using the drc [30] and linpk [31] packages. Our model is an adaptation of the pkprofile function from the linpk package. The pkprofile function is a general pharmacokinetic model for calculating the concentration-time profile of a drug that can account for absorption, infusion duration, and administration of multiple doses [31]. It uses a V and Cl parameterization where V is the volume of distribution and Cl is the clearance. Cl can be expressed as k × V, with k being the elimination rate constant. By setting V to 1, Cl defaults to k and we can substitute the dose input in the pkprofile function with the estimated MOR blockade at the administration time point (tadmin), assuming no absorption phase. Absorption can instead be handled by the pkprofile function by specifying an absorption rate constant (ka).
3.1.1.1. Establishing a dose-blockade curve at ∼55 minutes
Blockade estimates in available PET and dual-detector studies (Table 2) are based on the mean signal recorded between 45-65 minutes after intravenous naloxone administration. Assuming a linear decrease in blockade within this 20-minute time window (see Appendix), the reported blockade estimates approximately correspond to the blockade observed halfway (i.e., 10 minutes) through this section of the recording, i.e., at 55 minutes after intravenous naloxone administration (tmeasure). Like Mayberg and Frost [21], we fitted a log-logistic model to the available data (Table 2) to describe the relationship between naloxone dose and central blockade at tmeasure. We specifically used a four-parameter model (Equation 1) with the lower limit constrained to 0, the upper limit constrained to 100, and the Hill slope constrained to 1. The parameter ED50 (i.e., effective dose 50) in this model indicates the estimated dose at which 50% of the receptors are blocked [23].
Figure 1 displays the relationship between dose and MOR blockade (in black) for intravenous naloxone ∼55 minutes after administration. For the log-logistic model, we obtained the parameter estimate ED50 (SE) = 0.0023 (0.0004).
The effect of intravenous (IV) naloxone dose on opioid receptor blockade ∼55 minutes after administration. The bottom x-axis displays untransformed doses while the top x-axis shows the corresponding log10-transformed doses. The dashed horizontal line indicates full (90%) receptor blockade. MOR blockade (solid black curve) is based on the data in Table 2 (black dots). DOR (dot-dashed red curve) and KOR blockade (long-dashed blue curve) were approximated from MOR blockade using the relative receptor affinities of naloxone (Table 1). Semitransparent bands indicate 95% confidence bands. The estimated ED50 for MOR, DOR and KOR blockade was 0.0023 (SE = 0.0004), 0.094 and 0.018 mg/kg, respectively.
3.1.1.2. Establishing blockade over time
To extrapolate the MOR blockade at the time of administration (tadmin), we followed Kim et al. [25] and used an exponential decay model (Equation 2) to first calculate the elimination rate constant k from naloxone’s central blockade half-life (see Appendix). The blockade half-life estimates for naloxone obtained in PET [28] and dual-detector studies [25] are 100 and 120 minutes respectively. Using an average blockade half-life of 110 minutes (SE = 10), we obtained k = 0.006. This elimination rate constant also substituted the clearance parameter Cl in the pkprofile function because we set the volume of distribution V to 1.
In the above model, t is the time in minutes after tmeasure (i.e., 55 minutes after naloxone administration) and d is the dose-dependent blockade at tmeasure, which can be substituted with Equation 1. By subtracting tmeasure from the time input t, we enable extrapolation of blockade between tadmin (i.e., 0 minutes after naloxone administration) and tmeasure (Equation 3).
In Equation 3, t indicates the time in minutes after tadmin. By specifying t = 0 in Equation 3, we get the below function (Equation 4) for calculating the blockade produced by a given dose at tadmin assuming no absorption phase.
Equation 5 shows the formula for converting an intravenous naloxone dose to MOR blockade at tadmin assuming no absorption phase. By setting the volume of distribution V to 1, we can substitute the dose input in the pkprofile function with the output of Equation 5 to enable estimation of time-blockade profiles.
To estimate the time-to-peak (tmax) blockade for intravenous naloxone, we used time series data from dual-detector studies with [11C]carfentanil [16,25,32]. In these studies, the maximum reduction in activity from the control condition (i.e., no naloxone) occurred 23-29 minutes after administration of intravenous naloxone (M = 24.74, SE = 1.24; see Appendix for details). These data suggest that it takes ∼25 minutes after tadmin for naloxone to be distributed to the brain and occupy a maximum amount of central MOR after a single intravenous bolus of naloxone. To obtain the absorption rate constant ka for the MOR blockade-time profile (see Appendix for details), we used the Lambert W function (W-1; implemented in the pracma package; [33]). This resulted in the absorption rate constant ka = 0.126, which could be used as an input for the pkprofile function.
The final result is a model that converts an intravenous naloxone dose to central MOR blockade and computes a blockade-time profile with an absorption phase (i.e., distribution to the brain) and an elimination phase. The model treats blockade as a truncated measure of the concentration of naloxone in the brain. While blockade has an upper limit of 100%, the central concentration of naloxone may exceed the level necessary to produce full blockade of mu-opioid receptors. We allowed model estimates to exceed 100% to reduce underestimation of the duration of full MOR blockade and facilitate detection of excessive concentration levels that contribute to high DOR and KOR blockade. Blockade-time profiles for various doses of intravenous naloxone based on the model are available in Figure 2.
Time-blockade curves for exemplified bolus doses of intravenous (IV) naloxone, accounting for distribution to the brain and truncated at 100% blockade. The dashed horizontal line indicates full (90%) receptor blockade. DOR (dot-dashed red curve) and KOR blockade (long-dashed blue curve) were approximated from MOR blockade (solid black curve) using the relative receptor affinities of naloxone (Table 1).
3.1.2. Delta- and kappa-opioid receptor blockade with intravenous naloxone
Naloxone is a non-selective opioid antagonists that also blocks DOR and KOR. Due to the limited data on DOR and KOR blockade with intravenous naloxone, we simulated blockade of these two receptors using data on MOR blockade and naloxone’s affinity to DOR and KOR relative to MOR.
First, we generated dose-blockade curves for DOR and KOR using the estimated ED50 for MOR blockade (0.0023 mg/kg) and the mean reported affinity of naloxone to the various human opioid receptors (Table 1). Specifically, using the relative mean affinity, we estimate that ED50 would be 41 times greater for DOR than MOR and 8 times greater for KOR than MOR. By multiplying ED50 for MOR blockade with naloxone’s affinity to MOR relative to DOR and KOR we obtain ED50 = 0.094 mg/kg for DOR blockade and ED50 = 0.018 mg/kg for KOR blockade. Approximated dose-blockade curves for DOR and KOR at ∼55 minutes after intravenous naloxone administration are available in Figure 1.
Next, we established blockade-time profiles for DOR and KOR. Assuming similar elimination rate for blockade of MOR, DOR and KOR, we can adjust Equation 5 to allow for approximation of DOR (Equation 6) and KOR (Equation 7) blockade at tadmin.
If we also assume similar absorption rate for blockade of DOR and KOR as for blockade of MOR, we can use the pkprofile function to compute blockade-time profiles for DOR and KOR blockade with intravenous naloxone that incorporate an absorption phase (see Figure 2).
To validate these models, we compared the simulation results to data on DOR and KOR blockade with naloxone in humans. The available data are limited to studies using the non-selective opioid agonist [11C]diprenorphine which has equal affinity to MOR, DOR and KOR.
These studies suggest that doses of 0.1-1.5 mg/kg intravenous naloxone can completely block all three major opioid receptors [26,34]. A lower dose of ∼0.01 mg/kg produced full MOR blockade, but only partial blockade of DOR/KOR [26,35]. KOR blockade would likely be greater compared to DOR blockade due to naloxone’s higher affinity to KOR (Table 1). Our simulations are largely consistent with the available data, showing full KOR and high DOR blockade with 0.10 mg/kg and partial DOR and KOR blockade with 0.01 mg/kg (Figure 2). However, PET studies with ligands selective to DOR and KOR are necessary to determine the differential blockade of these two receptors by intravenous naloxone.
3.2. Naltrexone
3.2.1. Mu-opioid receptor blockade with oral naltrexone
3.2.1.1. Single dose
Several studies have used PET and dual-detection systems to investigate MOR blockade with single doses of oral naltrexone. Approximately 2 hours after administration of 50 mg oral naltrexone, the [11C]carfentanil signal in the brain matched the signal recorded 35-65 minutes after intravenous administration of 1 mg/kg naloxone [32], suggesting almost complete blockade of mu-opioid receptors [21]. Consistent with this, Rabiner et al. [23] report that 50 mg oral naltrexone produced 95% mu-opioid receptor blockade within 8 hours after administration. The same dose maintained >90% blockade at ∼49 hours after administration in the study by Lee et al. [32]. The observed blockade in this study decreased to 80% at ∼73 hours, 46% at ∼121 hours, and 30% at ∼169 hours after administration of naltrexone. Based on these data, Lee et al. [32] estimated the blockade half-life of naltrexone in the brain to be 72 hours. Lower doses of oral naltrexone also produce substantial levels of blockade. Within 8 hours of administration, 2, 5 and 15 mg blocked 27, 49 and 61% of the receptors, respectively [23]. Bednarczyk et al. [36] administered 12.5, 50 and 100 mg oral naltrexone and measured blockade after 3, 24, 72 and 144 hours (see also [37]). The blockade estimates from this study are unfortunately unavailable.
3.2.1.2. Repeated administration
The effect of repeated naltrexone administration on mu-opioid receptor availability has been investigated with PET in abstinent alcohol dependent patients. Following four days of treatment with 50 mg oral naltrexone, 95% of mu-opioid receptors in the brain were blocked [22]. Similar levels of blockade have been observed after daily administration of 50 mg oral naltrexone for three days [38].
3.2.2. Delta- and kappa-opioid receptor blockade with oral naltrexone
More PET data is available on DOR and KOR blockade with naltrexone than with naloxone. Applying the same simulation approach we used for intravenous naloxone to oral naltrexone, we find that simulation-based estimates largely agree with results from existing PET studies. For example, studies using the selective KOR agonist [11C]GR103545 and the selective KOR antagonist [11C]LY2795050 report high KOR blockade (85-93%) in healthy participants and participants with cocaine dependence 2-3 hours after administration of 150 mg oral naltrexone [39–41]. High levels of KOR blockade (87-92%) have also been observed after a week of daily treatment with 100 mg oral naltrexone in participants with alcohol dependence [24,42]. According to simulations based on data from Rabiner et al. [23] and affinity values from studies on cloned human opioid receptors (Table 1), 50 mg oral naltrexone would block 82% of KOR (Figure 3).
The effect of oral (PO) naltrexone dose on opioid receptor blockade within 8 hours of administration. The bottom x-axis displays untransformed doses while the top x-axis shows the corresponding log10-transformed doses. The dashed horizontal line indicates full (90%) receptor blockade. MOR blockade (solid black curve) is based on data (black dots) from Rabiner et al. [23]. DOR (dot-dashed red curve) and KOR blockade (long-dashed blue curve) were approximated from MOR blockade using the relative receptor affinities of naltrexone (Table 1). Semitransparent bands indicate 95% confidence bands. The estimated ED50 for MOR, DOR and KOR blockade was 5.59 (SE = 0.80; see also [23], 441.83 and 11.19 mg, respectively.
Using the selective DOR antagonist N1’-([11C]methyl)naltrindole ([11C]MeNTI), Madar et al. [43] and Smith et al. [44] reported that a single dose of 50 and 100 mg oral naltrexone produced 38% and 40-95% DOR blockade (respectively) approximately 2 hours after administration in healthy volunteers. Following three and four days of treatment with 50 mg oral naltrexone, the DOR blockade in abstinent alcohol dependent patients was estimated to 31% [38] and 21% [22], respectively. Simulations indicate that 50 mg oral naltrexone would produce only 10% DOR blockade (Figure 3). This underestimation could result from differences in measurement time points between the Rabiner et al. study and the PET studies of DOR blockade, or from some of the latter studies using repeated administration instead of a single dose.
4. General recommendations and web applications
General recommendations for selecting optimal antagonist drugs, doses and timings in basic human research based on our models and simulations are outlined in Table 3. To simplify planning of future studies and evaluation of past studies with intravenous naloxone and oral naltrexone, we also designed two web applications using the R package Shiny [45] that incorporate the models presented here. The app for intravenous naloxone (available at https://martintrostheim.shinyapps.io/planoxone/) produces an estimated MOR blockade-time profile based on the administration time point, dose, and infusion duration of a single or multiple doses, as specified by the user. Moreover, it can calculate the average MOR blockade over a given time interval. If provided with an intersession interval, the app will compute the residual MOR blockade at the beginning of the next session. The app for oral naltrexone (available at https://martintrostheim.shinyapps.io/plantrexone/) allows users to estimate the expected MOR blockade within 8 hours of administration of a given dose. Both apps enable users to simulate DOR and KOR blockade. By specifying the number of participants and session, and the drug price, the apps will also compute the total amount of drug needed for the study and the cost of this amount. The source code for both web applications is available on GitHub (https://github.com/martintrostheim/opioid-antagonist-planner).
Summary and general recommendations.
5. Discussion
Pharmacological blockade of a receptor system is a common method for probing the function of that receptor system in the human brain. Positron emission techniques yield data on the achieved level of blockade, but for studies of mu-opioid receptors, existing practices vary widely with regards to doses and assessment timing [47]. Here, we have synthesized the available PET and dual-detector data, and created models and web applications for calculating central opioid receptor blockade with the commonly used opioid antagonists naloxone (https://martintrostheim.shinyapps.io/planoxone/) and naltrexone (https://martintrostheim.shinyapps.io/plantrexone/). Our models allow for estimation of blockade of mu-, kappa- and delta-opioid receptors over time and across relevant dosing options in human clinical and experimental research. This overview and accompanying tools can therefore facilitate selection of an appropriate antagonist drug, dose, assessment time point, and intersession interval for future studies (see Table 3 for general recommendations). Conveniently, the web applications also calculate the total amount of the antagonist drug needed for a planned study.
Pharmacokinetic modelling of opioid antagonists typically focuses on plasma levels. However, for psychopharmacological studies it is important to understand the kinetics of the antagonist in the brain. Available PET and plasma data indicate that the central receptor blockade half-life of intravenous naloxone (110 minutes) and oral naltrexone (72 hours) correspond relatively closely to the plasma half-life of these antagonists during the terminal phase (75 minutes for intravenous naloxone and 96 hours for oral naltrexone; [48,49]), but not during the distribution phase. This suggests that plasma level would be a poor proxy for receptor blockade during the distribution phase and that modelling the elimination from the brain, as approximated here, is needed inform psychopharmacological experiments in sufficient detail.
These novel analytical tools can also aid interpretation of reported effects in the literature, since the presented models yield several insights into how previously used doses affect opioid receptors at the time of assessment. This is especially useful when interpreting the literature using naloxone, which has a relatively short half-life in the brain. Bolus doses of intravenous naloxone used in basic human research are often as large as or larger than 0.10-0.15 mg/kg (e.g., [50–52]). The initial bolus is sometimes supplemented with continuous infusion or an additional bolus (e.g., [52–54]), indicating that many authors may have underestimated the duration of the full blockade with these doses (∼60 minutes). As our model shows, such supplements are only necessary if researchers want to assess the effect of full MOR blockade on outcomes measured more than an hour after the initial bolus (see Figure 3). Yet, testing typically occurs within 15-60 minutes after the initial bolus. Lower doses are probably sufficient to produce full MOR blockade, but for a shorter period of time. For example, our model estimates 0.01 mg/kg to maintain full MOR blockade for ∼30 minutes. Combining a low bolus dose with continuous infusion can greatly extend the duration of the full MOR blockade for only a fraction of the cost of a high bolus dose (Table 3). An added benefit of using lower doses is that lower doses typically yield weaker and/or fewer side effects.
Studies using naltrexone to probe the endogenous mu-opioid system often administer 50 mg orally and begin outcome assessment ∼60-120 minutes later (e.g., [55–58]). However, some studies use a higher dose of 100 mg (e.g., [59,60]). The available PET and dual-detector data indicate that 50 mg is more than sufficient to produce full MOR blockade. This dose likely produces central concentration of naltrexone in excess of the dose required to completely block mu-opioid receptors. Weerts et al. [22] observed high level of and low variability in MOR blockade with 50 mg oral naltrexone. However, this ceiling effect could also be a result of the repeated dosing schedule used in this study. The earliest available MOR blockade estimate with oral naltrexone was collected ∼2 hours after administration and indicates that waiting 2 hours is sufficient to reach full MOR blockade with 50 mg [32]. Considering that naltrexone plasma levels peak 1 hour after oral administration [49], it is possible that the central blockade peaks in less than 2 hours.
Exponential decay processes are considered to be complete after five to ten half-lives [61]. Assuming a blockade half-life of ∼110 minutes with naloxone, we estimate that a washout period of 9 hours should be sufficient to eliminate the MOR blockade. This allows researchers to arrange experimental sessions on consecutive days in within-subjects designs using naloxone. In contrast, naltrexone’s half-life is estimated to 72 hours. After 1 week, which is a common intersession interval for within-subjects designs with oral naltrexone (e.g., [55,56,62]), the MOR blockade with 50 mg is reported to remain at 30%. This long-lasting effect is thought to result in part from metabolites of naltrexone that also act as antagonists [63]. However, some animal and human data suggest that naltrexone’s main active metabolite 6β-Naltrexol has limited ability to pass the blood-brain barrier and block central agonist effects [64]. Considering naltrexone’s long plasma terminal half-life (96 hours; [49]), it is possible that the prolonged blockade is facilitated by non-specific binding retention and/or slow release of naltrexone from central receptors. To ensure complete elimination of the blockade produced by oral naltrexone, a minimum intersession interval of 15 days would be necessary (i.e., five times the 72-hour blockade half-life; [61]).
We have primarily discussed the usefulness of intravenous naloxone and oral naltrexone in basic human research on the brain’s opioid system. Intranasal formulations of naloxone are also marketed for human use. These are noninvasive and easy to apply, and may therefore represent a viable alternative to intravenous naloxone and oral naltrexone. In a PET study by Johansson et al. [28], 4 mg of intranasal naloxone produced 85% MOR blockade and maintained this level of blockade for at least 20 minutes. However, there was large individual variability in peak MOR blockade, perhaps due to differences in nasal physiology and administration technique [65]. The observed time-to-peak MOR blockade was ∼40 minutes. Due to the slow absorption phase and risk of suboptimal administration, higher intranasal doses than 4 mg may be necessary to achieve full blockade more quickly and across all subjects. We therefore recommend using intravenous naloxone and oral naltrexone over intranasal naloxone to block the endogenous opioid system in basic human research. Compared to intranasal administration, intravenous administration requires smaller doses of naloxone to quickly produce high MOR blockade and is therefore less costly. Oral naltrexone likely results in less variable MOR blockade than intranasal naloxone due to the greater reliability of the oral administration method.
Because the opioid antagonists currently marketed for human use are non-selective, there is a concern that DOR and KOR blockade could complicate inferences about MOR functions. The available data and the simulations presented here indicate that naloxone and naltrexone can produce considerable KOR and DOR blockade depending on the dose. Our results need further validation against human PET data as we used receptor affinity data from CHO cells to simulate human DOR and KOR blockade from MOR blockade. While using a lower naloxone dose could reduce DOR and KOR blockade, this comes at the cost of a shorter duration of full MOR blockade from a bolus injection (see Figure 3). Applying a range of doses optimized for each receptor type can help disentangle the effects of MOR, DOR and KOR blockade on the outcome of interest. For researchers primarily interested in the mu-opioid system, more selective antagonists like GSK1521498 (see Appendix) could be a viable alternative to naloxone and naltrexone provided that detailed timing information becomes available.
Clinical effects of opioid antagonists can be observed without full MOR blockade. For example, the standard overdose reversal dose of intravenous naloxone (0.4 mg; [66]) starts reversing respiratory depression within 1-2 minutes, and this reversal lasts for ∼45-60 minutes [67]. Our model estimates that the MOR blockade throughout the majority of this time period is 70-80%. Regarding naltrexone, pretreatment with lower doses (estimated to produce ∼70% MOR blockade) attenuated subjective and physiological effects of medium to large doses of hydromorphone and morphine [68,69]. Subjective and physiological effects of opioid agonists like heroin and hydromorphone begin to reemerge within 48-72 hours after large doses of naltrexone [49,70,71], when central MOR blockade is estimated to ∼80%. Considered together, observable effects of agonist drugs on free MOR appear to emerge at 70-80% blockade. Any endogenous functions which could be fulfilled with 20-30% or smaller amounts of available MOR have yet to be determined.
The models and recommendations presented here should be considered in light of certain limitations. Here, we have used 90% receptor occupancy as the threshold for full blockade [21,22], but we cannot exclude that the up to 10% of unblocked receptors may fulfil some endogenous functions. Furthermore, only a limited number of studies have used positron emission techniques to quantify opioid receptor blockade with antagonist drugs. Many of these studies tested a small sample of participants, and some blockade estimates are based on a dose applied to a single participant. MOR blockade estimates for large doses of naloxone and naltrexone are likely accurate due to ceiling effects. However, estimates for lower doses and estimates from late in the elimination phase may be less accurate due to large individual variability in receptor binding (e.g., [22]). Despite limited data, the reported dose and timing information for intravenous naloxone was sufficient to create a tentative model of the relationship between dose, time and blockade for this antagonist. The model builds on blockade estimates from multiple studies rather than from a single study, and it can be validated and improved with data from future PET studies.
The majority of data informing this overview and models were collected from male participants. Men and women are pharmacokinetically and pharmacodynamically different [72], and these differences might affect the opioid receptor blockade produced by antagonist drugs. Many of the studies summarized here either present no analysis of gender effects [21,25,26,32,35,36,38,40,43], tested men only [23,34,39,73], or tested a single participant [16,17]. The few studies that report analyses of gender effects report no significant differences in receptor blockade between men and women [22,24,41,42]. Note that these studies used large doses (e.g., 50-150 mg oral naltrexone) that produce full MOR and KOR blockade in most participants. However, Weerts et al. [22] report no significant relationship between gender and the low DOR blockade produced by daily dosing of 50 mg oral naltrexone. More data is needed determine the generalizability of our models to men and women separately.
The purpose of this primer is to help researchers select antagonist doses that can block endogenous ligands from binding to central opioid receptors. While the information synthesized here may have implications for the choice of opioid antagonist doses in future clinical research, selection of doses for treatment purposes should be based on knowledge about the relationship between opioid antagonist dose and clinical outcomes rather than blockade of endogenous ligands. Naloxone and naltrexone are competitive antagonists, meaning that higher doses of agonist drugs may overcome the blockade produced by these antagonists. Larger doses or repeated administration of opioid antagonists may therefore be necessary in treatment settings to properly block the effects of agonist drugs.
6. Conclusion
Pharmacological blockade of the MOR system with an antagonist such as naloxone and naltrexone is a commonly used method of investigating the role of the human mu-opioid system in psychological processes. While more data on the opioid receptor blockade produced by these antagonists are needed, we hope that this overview and the accompanying tools can aid researchers in evaluating past antagonist studies and in selecting appropriate drugs, doses, assessment time points, and intersession intervals for future studies.
8. Conflict of interest
We declare no conflicts of interest.
7. Acknowledgements
This work was supported by grants from the European Research Council under the European Union’s Horizon 2020 research and innovation program (grant agreement No. 802885) to Siri Leknes and the South-Eastern Norway Regional Health Authority (project No. 2018035) to Marie Eikemo.
We thank Howard Fields at the University of California San Francisco, and Molly Carlyle at the University of Oslo and The University of Queensland for feedback on the manuscript. None of the above received financial compensation outside of salary.
Footnotes
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