Prediction of Drug-Drug Interactions Between Opioids and Overdosed Benzodiazepines Using Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation

Use of CYP2D6 substrates and inhibitors during pain management with analgesic opioids: Drug-drug interactions that lead to lack of analgesic effectiveness

BACKGROUND

Several opioids have pharmacogenetic and drug-drug interactions which may compromise their analgesic effectiveness, but are not routinely implemented into supportive pain management. We hypothesized that CYP2D6 phenotypes and concomitant use of CYP2D6 substrates or inhibitors would correlate with opioid analgesic outcomes.

MATERIALS AND METHODS

An observational cross-sectional study was conducted with 263 adult chronic non cancer pain (CNCP) patients from a real-world pain unit under long-term CYP2D6-related opioid treatment (tramadol, hydromorphone, tapentadol or oxycodone). Metabolizer phenotype (ultrarapid [UM], normal [NM], intermediate [IM] or poor [PM]) was determined by the CYP2D6 genotype. The socio-demographic (sex, age, employment status), clinical (pain intensity and relief, neuropathic component, quality of life, disability, anxiety and depression), pharmacological (opioid doses and concomitant pharmacotherapy) and safety (adverse events) variables were recorded.

RESULTS

The whole population (66 % female, 65 (14) years old, 70 % retired and 63 % attended for low back pain) were classified as PM (5 %), IM (32 %), NM (56 %) and UM (6 %). Multiple linear and logistic regressions showed higher pain intensity and neuropathic component at younger ages when using any CYP2D6 substrate (p = 0.022) or inhibitor (p = 0.030) drug, respectively, with poorer pain relief when CYP2D6 inhibitors (p=0.030) were present.

CONCLUSION

The concomitant use of CYP2D6 substrates or inhibitors during opioid therapy for CNCP may result in lack of analgesic effectiveness. This aspect could be relevant for pharmacological decision making during CNCP management.

Salivary Therapeutic Monitoring of Buprenorphine in Neonates After Maternal Sublingual Dosing Guided by Physiologically Based Pharmacokinetic Modeling

BACKGROUND

Opioid use disorder (OUD) during pregnancy is associated with high mortality rates and neonatal opioid withdrawal syndrome (NOWS). Buprenorphine, an opioid, is used to treat OUD and NOWS. Buprenorphine active metabolite (norbuprenorphine) can cross the placenta and cause neonatal respiratory depression (EC50 = 35 ng/mL) at high brain extracellular fluid (bECF) levels. Neonatal therapeutic drug monitoring using saliva decreases the likelihood of distress and infections associated with frequent blood sampling.

METHODS

An adult physiologically based pharmacokinetic model for buprenorphine and norbuprenorphine after intravenous and sublingual administration was constructed, vetted, and scaled to newborn and pregnant populations. The pregnancy model predicted that buprenorphine and norbuprenorphine doses would be transplacentally transferred to the newborns. The newborn physiologically based pharmacokinetic model was used to estimate the buprenorphine and norbuprenorphine levels in newborn plasma, bECF, and saliva after these doses.

RESULTS

After maternal sublingual administration of buprenorphine (4 mg/d), the estimated plasma concentrations of buprenorphine and norbuprenorphine in newborns exceeded the toxicity thresholds for 8 and 24 hours, respectively. However, the norbuprenorphine bECF levels were lower than the respiratory depression threshold. Furthermore, the salivary buprenorphine threshold levels in newborns for buprenorphine analgesia, norbuprenorphine analgesia, and norbuprenorphine hypoventilation were observed to be 22, 2, and 162 ng/mL.

CONCLUSIONS

Using neonatal saliva for buprenorphine therapeutic drug monitoring can facilitate newborn safety during the maternal treatment of OUD using sublingual buprenorphine. Nevertheless, the suitability of using adult values of respiratory depression EC50 for newborns must be confirmed.

Assessment of Drug-Drug Interaction Risk Between Intravenous Fentanyl and the Glecaprevir/Pibrentasvir Combination Regimen in Hepatitis C Patients Using Physiologically Based Pharmacokinetic Modeling and Simulations

INTRODUCTION

An unsafe injection practice is one of the major contributors to new hepatitis C virus (HCV) infections; thus, people who inject drugs are a key population to prioritize to achieve HCV elimination. The introduction of highly effective and well-tolerated pangenotypic direct-acting antivirals, including glecaprevir/pibrentasvir (GLE/PIB), has revolutionized the HCV treatment landscape. Glecaprevir is a weak cytochrome P450 3A4 (CYP3A4) inhibitor, so there is the potential for drug-drug interactions (DDIs) with some opioids metabolized by CYP3A4, such as fentanyl. This study estimated the impact of GLE/PIB on the pharmacokinetics of intravenous fentanyl by building a physiologically based pharmacokinetic (PBPK) model.

METHODS

A PBPK model was developed for intravenous fentanyl by incorporating published information on fentanyl metabolism, distribution, and elimination in healthy individuals. Three clinical DDI studies were used to verify DDIs within the fentanyl PBPK model. This model was integrated with a previously developed GLE/PIB PBPK model. After model validation, DDI simulations were conducted by coadministering GLE 300 mg + PIB 120 mg with a single dose of intravenous fentanyl (0.5 µg/kg).

RESULTS

The predicted maximum plasma concentration ratio between GLE/PIB + fentanyl and fentanyl alone was 1.00, and the predicted area under the curve ratio was 1.04, suggesting an increase of only 4% in fentanyl exposure.

CONCLUSION

The administration of a therapeutic dose of GLE/PIB has very little effect on the pharmacokinetics of intravenous fentanyl. This negligible increase would not be expected to increase the risk of fentanyl overdose beyond the inherent risks related to the amount and purity of the fentanyl received during recreational use.

Metabolic interactions of benzodiazepines with oxycodone ex vivo and toxicity depending on usage patterns in an animal model

BACKGROUND AND PURPOSE

Opioids and benzodiazepines are frequently combined in medical as well as in non-medical contexts. At high doses, such combinations often result in serious health complications attributed to pharmacodynamics interactions. Here, we investigate the contribution of the metabolic interactions between oxycodone, diazepam and diclazepam (a designer benzodiazepine) in abuse/overdose conditions through ex vivo, in vivo and in silico approaches.

EXPERIMENTAL APPROACH

A preparation of pooled human liver microsomes was used to study oxycodone metabolism in the presence or absence of diazepam or diclazepam. In mice, diazepam or diclazepam was concomitantly administered with oxycodone to mimic acute intoxication. Diclazepam was introduced on Day 10 in mice continuously infused with oxycodone for 15 days to mimic chronic intoxication. In silico modelling was used to study the molecular interactions of the three drugs with CYP3A4 and 2D6.

KEY RESULTS

In mice, in acute conditions, both diazepam and diclazepam inhibited the metabolism of oxycodone. In chronic conditions and at pharmacologically equivalent doses, diclazepam drastically enhanced the production of oxymorphone. In silico, the affinity of benzodiazepines was higher than oxycodone for CYP3A4, inhibiting oxycodone metabolism through CYP3A4. Oxycodone metabolism is likely to be diverted towards CYP2D6.

CONCLUSION AND IMPLICATIONS

Acute doses of diazepam or diclazepam result in the accumulation of oxycodone, whereas chronic administration induces the accumulation of oxymorphone, the toxic metabolite. This suggests that overdoses of opioids in the presence of benzodiazepines are partly due to metabolic interactions, which in turn explain the patterns of toxicity dependent on usage.

LINKED ARTICLES

This article is part of a themed issue on Advances in Opioid Pharmacology at the Time of the Opioid Epidemic. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v180.7/issuetoc.

Insights on benzodiazepines' potential in Alzheimer's disease

Alzheimer's disease (AD) is the most frequent type of dementia characterized by the deposition of amyloid beta (Aβ) plaque and tau-neurofibrillary tangles (TNTs) in the brain. AD is associated with the disturbances of various neurotransmitters including gamma-aminobutyric acid (GABA). Of note, GABA is reduced in AD, and restoration of GABA effect by benzodiazepines (BDZs) may improve AD outcomes. However, BDZs may adversely affect cognitive functions chiefly in elderly AD patients with sleep disorders. Besides, there is a controversy regarding the use of BDZs in AD. Consequently, the objective of the present review was to disclose the possible role of BDZs on the pathogenesis of AD that might be beneficial, neutral, or detrimental effects on AD. Prolonged use of intermediate-acting BDZ lorazepam exerts amnesic effects due to attenuation of synaptic plasticity and impairment of recognition memory. However, BDZs may have a protective effect against the development of AD by reducing tau phosphorylation, neuroinflammation, and progression of AD neuropathology. On the other side, other findings highlighted that extended use of BDZs was not associated with the development of AD. In conclusion, there are controversial points concerning the use of BDZs and the risk for the progression of AD. Thus, preclinical, and clinical studies are essential in this regard.

Benzodiazepines in Alzheimer's disease: beneficial or detrimental effects

Dementia is considered a clinical syndrome characterized by cognitive dysfunction and memory loss. Alzheimer's disease (AD) is the most common type of dementia. AD is linked with the turbulence of diverse neurotransmitters including gamma-aminobutyric acid (GABA). Notably, GABA in the brain and cerebrospinal fluid was reduced in AD. Thus, allosteric modulation of the GABA effect by benzodiazepines (BDZs) may improve the clinical outcomes of AD patients. Therefore, the objective of the present review was to reveal the possible role of BDZs on the pathogenesis and clinical outcomes in AD patients. Though BDZs may adversely affect cognitive functions mainly in elderly patients, herein it was postulated that BDZs may have beneficial, neutral, or detrimental effects in AD. Taken together, there is strong controversy regarding the use of BDZs and the risk for the development of AD. Therefore, experimental, preclinical and clinical studies are critical to determine the potential protective or detrimental effects of BDZs on AD neuropathology.

An Overview of Physiologically-Based Pharmacokinetic Models for Forensic Science

A physiologically-based pharmacokinetic (PBPK) model represents the structural components of the body with physiologically relevant compartments connected via blood flow rates described by mathematical equations to determine drug disposition. PBPK models are used in the pharmaceutical sector for drug development, precision medicine, and the chemical industry to predict safe levels of exposure during the registration of chemical substances. However, one area of application where PBPK models have been scarcely used is forensic science. In this review, we give an overview of PBPK models successfully developed for several illicit drugs and environmental chemicals that could be applied for forensic interpretation, highlighting the gaps, uncertainties, and limitations.

Midazolam for conscious sedation in transcatheter device closure of atrial septal defects guided solely by transthoracic echocardiography

OBJECTIVES

To investigate the safety and feasibility of midazolam for conscious sedation in transcatheter device closure of atrial septal defects guided solely by transthoracic echocardiography.

METHODS

A retrospective analysis was performed on 55 patients who underwent transcatheter device closure of atrial septal defects from October, 2019 to May, 2020. All patients received intravenous midazolam and local anesthesia with lidocaine to maintain sedation. A group of previous patients with unpublished data who underwent the same procedure with general anesthesia was set as the control group. The relevant clinical parameters, the Ramsay sedation scores, the numerical rating scale, and the post-operative satisfaction questionnaire were recorded and analyzed.

RESULTS

In the midazolam group, the success rate of atrial septal defect closure was 98.2%. Hemodynamic stability was observed during the procedure. None of the patients needed additional endotracheal intubation for general anesthesia. Compared with the control group, the midazolam group had no statistically significant differences in the Ramsay sedation score and numerical rating scale scores. Patients in the midazolam group experienced more post-operative satisfaction than those in the control group.

CONCLUSIONS

Conscious sedation using midazolam is a safe and effective anesthetic technique for transcatheter device closure of atrial septal defects guided solely by transthoracic echocardiography.

Oxycodone-Related Deaths: The Significance of Pharmacokinetic and Pharmacodynamic Drug Interactions

BACKGROUND AND OBJECTIVES

Oxycodone is frequently prescribed as well as detected in postmortem cases. Concurrent use of pharmacodynamically or pharmacokinetically interacting drugs can cause adverse effects or even fatal intoxication. The aims of this study were to investigate differences in prescriptions for and toxicological findings of pharmacodynamically and pharmacokinetically interacting drugs in fatal oxycodone-related intoxications and other causes of death. We also aimed to investigate the differences in prevalence of oxycodone prescriptions, and the detected postmortem oxycodone concentrations between fatal oxycodone-related intoxications and other causes of death.

METHODS

Forensic autopsy cases (2012-2018) where oxycodone was identified in femoral blood (n = 1236) were included. Medical history and prescription data were retrieved from national databases and linked to the forensic toxicology findings.

RESULTS

Oxycodone-related deaths were found to have higher blood concentrations of oxycodone (median 0.30 µg/g vs. 0.05 µg/g) and were less likely to have a prescription for oxycodone (OR 0.62) compared to nonintoxication deaths. Pharmacodynamically interacting drugs were prescribed in 79% and found in blood in 81% of the cases. Pharmacokinetically interacting drugs were rarely prescribed (1%). Oxycodone-related deaths were more likely to have prescriptions for a pharmacodynamically interacting drug (OR 1.7) and more often have co-findings of one or multiple pharmacodynamically interacting drugs (OR 5.6).

CONCLUSION

The results suggest that combined use of oxycodone and pharmacodynamically interacting drugs is associated with oxycodone-related death and that non-medical use of oxycodone is a potential risk factor for oxycodone-related intoxication.

A Physiologically Based Pharmacokinetic Model for Predicting Diazepam Pharmacokinetics after Intravenous, Oral, Intranasal, and Rectal Applications

Diazepam is one of the most prescribed anxiolytic and anticonvulsant that is administered through intravenous (IV), oral, intramuscular, intranasal, and rectal routes. To facilitate the clinical use of diazepam, there is a need to develop formulations that are convenient to administer in ambulatory settings. The present study aimed to develop and evaluate a physiologically based pharmacokinetic (PBPK) model for diazepam that is capable of predicting its pharmacokinetics (PK) after IV, oral, intranasal, and rectal applications using a whole-body population-based PBPK simulator, Simcyp^®. The model evaluation was carried out using visual predictive checks, observed/predicted ratios (R_obs/pred), and the average fold error (AFE) of PK parameters. The Diazepam PBPK model successfully predicted diazepam PK in an adult population after doses were administered through IV, oral, intranasal, and rectal routes, as the R_obs/pred of all PK parameters were within a two-fold error range. The developed model can be used for the development and optimization of novel diazepam dosage forms, and it can be extended to simulate drug response in situations where no clinical data are available (healthy and disease).

PBPK Analysis to Study the Impact of Genetic Polymorphism of NAT2 on Drug-Drug Interaction Potential of Isoniazid

PURPOSE

Isoniazid (INH) is prescribed both for the prophylaxis as well as the treatment of tuberculosis. It is primarily metabolized through acetylation by a highly polymorphic enzyme, N-acetyl transferase 2 (NAT2), owing to which significant variable systemic drug levels have been reported among slow and rapid acetylators. Furthermore, many drugs, like phenytoin, diazepam, triazolam, etc., are known to show toxic manifestation when co-administered with INH and it happens prominently among slow acetylators. Additionally, it is revealed in in vitro inhibition studies that INH carries noteworthy potential to inhibit CYP2C19 and CYP3A4 enzymes. However, CYP inhibitory effect of INH gets masked by opposite enzyme-inducing effect of rifampicin, when used in combination. Thus, distinct objective of this study was to fill the knowledge gaps related to gene-drug-drug interactions (DDI) potential of INH when given alone for prophylactic purpose.

METHODS

Whole body-PBPK models of INH were developed and verified for both slow and fast acetylators. The same were then utilized to carry out prospective DDI studies with CYP2C19 and CYP3A4 substrates in both acetylator types.

RESULTS

The results highlighted likelihood of significant higher blood levels of CYP2C19 and CYP3A4 substrate drugs in subjects receiving INH pre-treatment. It was also re-established that interaction was more likely in slow acetylators, as compared to rapid acetylators.

CONCLUSION

The novel outcome of the present study is the indication that prescribers should give careful consideration while advising CYP2C19 and CYP3A4 substrate drugs to subjects who are on prophylaxis INH therapy, and are slow to metabolic acetylation.

Drug-Drug Interaction Between Oxycodone and Diazepam by a Combined in Silico Pharmacokinetic and Pharmacodynamic Modeling Approach

Opioids and benzodiazepines have complex drug-drug interactions (DDIs), which serve as an important source of adverse drug effects. In this work, we predicted the DDI between oxycodone (OXY) and diazepam (DZP) in the human body by applying in silico pharmacokinetic (PK) and pharmacodynamic (PD) modeling and simulation. First, we studied the PK interaction between OXY and DZP with a physiologically based pharmacokinetic (PBPK) model. Second, we applied molecular modeling techniques including molecular docking, molecular dynamics (MD) simulation, and the molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) free energy method to predict the PD-DDI between these two drugs. The PK interaction between OXY and DZP predicted by the PBPK model was not obvious. No significant interaction was observed between the two drugs at normal doses, though very high doses of DZP demonstrated a non-negligible inhibitory effect on OXY metabolism. On the contrary, the molecular modeling study shows that DZP has potential to compete with OXY at the same binding pocket of the active μ-opioid receptor (MOR) and κ-opioid receptor (KOR). MD simulation and MM-PBSA calculation results demonstrated that there is likely a synergetic effect between OXY and DZP binding to opioid receptors, as OXY is likely to target the active MOR while DZP selectively binds to the active KOR. Thus, pharmacokinetics contributes slightly to the DDI between OXY and DZP although an overdose of DZP has been brought to attention. Pharmacodynamics is likely to play a more important role than pharmacokinetics in revealing the mechanism of DDI between OXY and DZP.

Development of a Virtual Chinese Pediatric Population Physiological Model Targeting Specific Metabolism and Kidney Elimination Pathways

Background: Physiologically based pharmacokinetic (PBPK) modeling and simulating may be a powerful tool in predicting drug behaviors in specific populations. It is a mathematical model that relates the pharmacokinetic (PK) profile of a compound with human anatomical characteristics, physiological characteristics, and biochemical parameters. Predictions using PBPK models offer a promising way to guide drug development and can be used to optimize clinical dosing regimens. However, PK data of new drugs in the pediatric population are too limited to guide clinical therapy, which may lead to frequent adverse events or insufficient efficacy for pediatric patients, particularly in neonates and infants.

Objective: The objective of this study was to establish a virtual Chinese pediatric population based on the physiological parameters of Chinese children that could be utilized in PBPK models.

Methods: A Chinese pediatric PBPK model was developed in Simcyp Simulator by collecting published Chinese pediatric physiological and anthropometric data to use as system parameters. This pediatric population model was then evaluated in the Chinese pediatric population by predicting the pharmacokinetic characteristics of four probe drugs: theophylline (major CYP1A2 substrate), fentanyl (major CYP3A4 substrate), vancomycin, and ceftazidime (renal-eliminated).

Results: The predicted maximum concentration (C_max), area under the curve of concentration-time (AUC), and clearance (CL) for theophylline (CYP1A2 metabolism pathway) and fentanyl (CYP3A4 metabolism pathway) were within two folds of the observed data. For drugs mainly eliminated by renal clearance (vancomycin and ceftazidime) in the Chinese pediatric population, the ratio of prediction to observation for major PK parameters was within a 2-fold error range.

Conclusion: The model is a supplement to the previous Chinese population PBPK model. We anticipate the model to be a better representative of the pediatric Chinese population for drugs PK, offering greater clinical precision for medication given to the pediatric population, ultimately advancing clinical development of pediatric drugs. We can refine this model further by collecting more physiological parameters of Chinese children.

Physiologically-Based Pharmacokinetic (PBPK) Modeling of Buprenorphine in Adults, Children and Preterm Neonates

Buprenorphine plays a crucial role in the therapeutic management of pain in adults, adolescents and pediatric subpopulations. However, only few pharmacokinetic studies of buprenorphine in children, particularly neonates, are available as conducting clinical trials in this population is especially challenging. Physiologically-based pharmacokinetic (PBPK) modeling allows the prediction of drug exposure in pediatrics based on age-related physiological differences. The aim of this study was to predict the pharmacokinetics of buprenorphine in pediatrics with PBPK modeling. Moreover, the drug-drug interaction (DDI) potential of buprenorphine with CYP3A4 and P-glycoprotein perpetrator drugs should be elucidated. A PBPK model of buprenorphine and norbuprenorphine in adults has been developed and scaled to children and preterm neonates, accounting for age-related changes. One-hundred-percent of the predicted AUC_last values in adults (geometric mean fold error (GMFE): 1.22), 90% of individual AUC_last predictions in children (GMFE: 1.54) and 75% in preterm neonates (GMFE: 1.57) met the 2-fold acceptance criterion. Moreover, the adult model was used to simulate DDI scenarios with clarithromycin, itraconazole and rifampicin. We demonstrate the applicability of scaling adult PBPK models to pediatrics for the prediction of individual plasma profiles. The novel PBPK models could be helpful to further investigate buprenorphine pharmacokinetics in various populations, particularly pediatric subgroups.