Background: Opioids are potent painkillers but come with serious adverse effects ranging from addiction to potentially lethal respiratory depression. A variety of drugs with separate mechanisms of action are available to prevent or reverse opioid-induced respiratory depression (OIRD). Methods: The authors reviewed human studies on reversal of OIRD using models that describe and predict the time course of pharmacokinetics (PK) and pharmacodynamics (PD) of opioids and reversal agents and link PK to PD. Results: The PKPD models differ in their basic structure to capture the specific pharmacological mechanisms by which reversal agents interact with opioid effects on breathing. The effect of naloxone, a competitive opioid receptor antagonist, is described by the combined effect-compartment receptor-binding model to quantify rate limitation at the level of drug distribution and receptor kinetics. The effects of reversal agents that act through non-opioidergic pathways, such as ketamine and the experimental drug GAL021, are described by physiological models, in which stimulants act at CO 2 chemosensitivity, CO 2 -independent ventilation, or both. The PKPD analyses show that although all reversal strategies may be effective under certain circumstances, there are conditions at which reversal is less efficacious and sometimes even impossible. Conclusions: Model-based drug development is needed to design an 'ideal' reversal agentdthat is, one that is not influenced by opioid receptor kinetics, does not interfere with opioid analgesia, has a rapid onset of action with longlasting effects, and is devoid of adverse effects.

Chronic opioid consumption is associated with addiction, physical dependence, and tolerance. Tolerance results in dose escalation to maintain the desired opioid effect. Intake of high-dose or potent opioids may cause life-threatening respiratory depression, an effect that may be reduced by tolerance. We performed a pharmacokineticpharmacodynamic analysis of the respiratory effects of fentanyl in chronic opioid users and opioid-naïve subjects to quantify tolerance to respiratory depression. Fourteen opioid-naïve individuals and eight chronic opioid users received escalating doses of intravenous fentanyl (opioid-naïve subjects: 75-350 µg/70 kg; chronic users: 250-700 µg/70 kg). Isohypercapnic ventilation was measured and the fentanyl plasma concentration-ventilation data were analyzed using nonlinear mixed-effects modeling. Apneic events occurred in opioid-naïve subjects after a cumulative fentanyl dose (per 70 kg) of 225 (n = 3) and 475 µg (n = 6), and in 7 chronic opioid users after a cumulative dose of 600 (n = 2), 1,100 (n = 2), and 1,800 µg (n = 3). The time course of fentanyl's respiratory depressant effect was characterized using a biophase equilibration model in combination with an inhibitory maximum effect (E max) model. Differences in tolerance between populations were successfully modeled. The effect-site concentration causing 50% ventilatory depression, was 0.42 ± 0.07 ng/mL in opioid-naïve subjects and 1.82 ± 0.39 ng/mL in chronic opioid users, indicative of a 4.3-fold sensitivity difference. Despite higher tolerance to fentanyl-induced respiratory depression, apnea still occurred in the opioid-tolerant population indicative of the potential danger of high-dose opioids in causing life-threatening respiratory depression in all individuals, opioid-naïve and opioid-tolerant.

The funder provided support in the form of salaries for RLD and CLM. The funder of the study and affiliated authors participated in designing the study, data analysis, and interpretation of the data. All authors had full access to all the data and agreed to submit the manuscript for publication. RLD and CLM are paid employees of Indivior Inc. AD received consultancy and/or speaker fees from Enalare Therapeutics Inc. (USA), Grünenthal BV (Netherlands), Trevena Inc. (USA), MSD Nederland BV, and grants/ awards from ZonMW (The Hague, Netherlands) in the framework of the NWA-ORC Call (NWA.1160.18.300) and the US FDA.

Background Opioid-induced respiratory depression driven by ligand binding to mu-opioid receptors is a leading cause of opioid-related fatalities. Buprenorphine, a partial agonist, binds with high affinity to mu-opioid receptors but displays partial respiratory depression effects. The authors examined whether sustained buprenorphine plasma concentrations similar to those achieved with some extended-release injections used to treat opioid use disorder could reduce the frequency and magnitude of fentanyl-induced respiratory depression. Methods In this two-period crossover, single-centre study, 14 healthy volunteers (single-blind, randomized) and eight opioid-tolerant patients taking daily opioid doses ≥90 mg oral morphine equivalents (open-label) received continuous intravenous buprenorphine or placebo for 360 minutes, targeting buprenorphine plasma concentrations of 0.2 or 0.5 ng/mL in healthy volunteers and 1.0, 2.0 or 5.0 ng/mL in opioid-tolerant patients. Upon reaching target concentrations, participants received up to four escalating intravenous doses of fentanyl. The primary endpoint was change in isohypercapnic minute ventilation (VE). Additionally, occurrence of apnea was recorded. Results Fentanyl-induced changes in VE were smaller at higher buprenorphine plasma concentrations. In healthy volunteers, at target buprenorphine concentration of 0.5 ng/mL, the first and second fentanyl boluses reduced VE by [LSmean (95% CI)] 26% (13–40%) and 47% (37–59%) compared to 51% (38–64%) and 79% (69–89%) during placebo infusion (p = 0.001 and < .001, respectively). Discontinuations for apnea limited treatment comparisons beyond the second fentanyl injection. In opioid-tolerant patients, fentanyl reduced VE up to 49% (21–76%) during buprenorphine infusion (all concentration groups combined) versus up to 100% (68–132%) during placebo infusion (p = 0.006). In opioid-tolerant patients, the risk of experiencing apnea requiring verbal stimulation following fentanyl boluses was lower with buprenorphine than with placebo (odds ratio: 0.07; 95% CI: 0.0 to 0.3; p = 0.001). Interpretation Results from this proof-of-principle study provide the first clinical evidence that high sustained plasma concentrations of buprenorphine may protect against respiratory depression induced by potent opioids like fentanyl.

Opioids are complex drugs that produce profit (most importantly analgesia) as well as a myriad of adverse effects including gastrointestinal motility disturbances, abuse and addiction, sedation and potentially lethal respiratory depression (RD). Consequently, opioid treatment requires careful evaluation in terms of benefit on the one hand and harm on the other. Considering benefit and harm from an economic perspective, opioid treatment should lead to profit maximization with decision theory defining utility as (profit − loss).We here focus on the most devastating opioid adverse effect, RD and define opioid utility U = P(benefit) − P(harm), where P(benefit) is the probability of opioid-induced analgesia and P(harm) the probability of opioid-induced RD. Other utility functions are also discussed including the utility U = P(benefit AND NOT harm), the most wanted opioid effect, i.e., analgesia without RD, and utility surfaces, which depict the continuum of probabilities of presence or absence of analgesia in combination with the presence or absence of RD. Utility functions are constructed from pharmacokinetic and pharmacodynamic data sets, although pragmatic utility functions may be constructed when pharmacokinetic data are not available. We here discuss utilities of several opioids including the partial mu-opioid-receptor agonist buprenorphine, the full opioid receptor agonists fentanyl and alfentanil, and the bifunctional opioid cebranopadol, which acts at mu-opioid and nociception/orphanin FQ-receptors. We argue that utility functions give clinicians the opportunity to make an informed decision when opioid analgesics are needed for pain relief, in which opioids with a positive utility function are preferred over opioids with negative functions. Furthermore, utility functions of subpopulations will give an extra insight as a utility functions measured in one subgroup (e.g., patients with postoperative pain, good opioid responders) may not be mirrored in other patient subgroups (e.g., neuropathic pain patients, poor opioid responders).