Physiologically-Based Pharmacokinetic Modeling for Predicting Drug Interactions of a Combination of Olanzapine and Samidorphan

Application of physiologically based pharmacokinetic modeling of novel drugs approved by the U.S. food and drug administration

Physiologically based pharmacokinetic (PBPK) models which can leverage preclinical data to predict the pharmacokinetic properties of drugs rapidly became an essential tool to improve the efficiency and quality of novel drug development. In this review, by searching the Application Review Files in Drugs@FDA, we analyzed the current application of PBPK models in novel drugs approved by the U.S. Food and Drug Administration (FDA) in the past five years. According to the results, 243 novel drugs were approved by the FDA from 2019 to 2023. During this period, 74 Application Review Files of novel drugs approved by the FDA that used PBPK models. PBPK models were used in various areas, including drug-drug interactions (DDI), organ impairment (OI) patients, pediatrics, drug-gene interaction (DGI), disease impact, and food effects. DDI was the most widely used area of PBPK models for novel drugs, accounting for 74.2 % of the total. Software platforms with graphical user interfaces (GUI) have reduced the difficulty of PBPK modeling, and Simcyp was the most popular software platform among applicants, with a usage rate of 80.5 %. Despite its challenges, PBPK has demonstrated its potential in novel drug development, and a growing number of successful cases provide experience learned for researchers in the industry.

Physiologically-based pharmacokinetic modeling of prominent oral contraceptive agents and applications in drug-drug interactions

Considerable interest remains across the pharmaceutical industry and regulatory landscape in capabilities to model oral contraceptives (OCs), whether combined (COCs) with ethinyl estradiol (EE) or progestin-only pill. Acceptance of COC drug-drug interaction (DDI) assessment using physiologically-based pharmacokinetic (PBPK) is often limited to the estrogen component (EE), requiring further verification, with extrapolation from EE to progestins discouraged. There is a paucity of published progestin component PBPK models to support the regulatory DDI guidance for industry to evaluate a new chemical entity's (NCE's) DDI potential with COCs. Guidance recommends a clinical interaction study to be considered if an investigational drug is a weak or moderate inducer, or a moderate/strong inhibitor, of CYP3A4. Therefore, availability of validated OC PBPK models within one software platform, will be useful in predicting the DDI potential with NCEs earlier in the clinical development. Thus, this work was focused on developing and validating PBPK models for progestins, DNG, DRSP, LNG, and NET, within Simcyp, and assessing the DDI potential with known CYP3A4 inhibitors (e.g., ketoconazole) and inducers (e.g., rifampicin) with published clinical data. In addition, this work demonstrated confidence in the Simcyp EE model for regulatory and clinical applications by extensive verification in 70+ clinical PK and CYP3A4 interaction studies. The results provide greater capability to prospectively model clinical CYP3A4 DDI with COCs using Simcyp PBPK to interrogate the regulatory decision-tree to contextualize the potential interaction by known perpetrators and NCEs, enabling model-informed decision making, clinical study designs, and delivering potential alternative COC options for women of childbearing potential.

Combining samidorphan with olanzapine to mitigate weight gain as a side effect in schizophrenia treatment

Purpose

This article analyzes clinical trials that provide evidence for the positive effects of using samidorphan to mitigate undesirable weight gain in patients diagnosed with schizophrenia who are undergoing treatment with olanzapine.

Views

Weight gain is a prevalent and problematic side effect of antipsychotic drug therapy, particularly in patients with schizophrenia. To address this issue, extensive research is being conducted to explore new drug therapies that can effectively counteract psychotic symptoms while minimizing the occurrence of unwanted side effects. One promising approach involves the addition of weight-loss substances to existing medications. Studies have indicated that opioid receptor antagonists, such as samidorphan, have the potential to facilitate weight loss. Consequently, a novel therapy combining samidorphan and olanzapine has been developed and is discussed in detail in this article.

Conclusions

The combination of samidorphan and olanzapine has demonstrated its ability to effectively reduce weight gain in patients with schizophrenia, without compromising the drug's primary function of alleviating psychotic symptoms. Moreover, the inclusion of samidorphan in the treatment regimen may contribute to a lower risk of cardiovascular events, though it is worth noting that it could also lead to an increase in digestive side effects. Despite this potential drawback, the introduction of this innovative therapy represents a significant advancement in the management of obesity among individuals with schizophrenia.

Delineating gene-environment effects using virtual twins of patients treated with clozapine

Studies that focus on individual covariates, while ignoring their interactions, may not be adequate for model-informed precision dosing (MIPD) in any given patient. Genetic variations that influence protein synthesis should be studied in conjunction with environmental covariates, such as cigarette smoking. The aim of this study was to build virtual twins (VTs) of real patients receiving clozapine with interacting covariates related to genetics and environment and to delineate the impact of interacting covariates on predicted clozapine plasma concentrations. Clozapine-treated patients with schizophrenia (N = 42) with observed clozapine plasma concentrations, demographic, environmental, and genotype data were used to construct VTs in Simcyp. The effect of increased covariate virtualization was assessed by performing simulations under three conditions: "low" (demographic), "medium" (demographic and environmental interaction), and "high" (demographic and environmental/genotype interaction) covariate virtualization. Increasing covariate virtualization with interaction improved the coefficient of variation (R² ) from 0.07 in the low model to 0.391 and 0.368 in the medium and high models, respectively. Whereas R² was similar between the medium and high models, the high covariate virtualization model had improved accuracy, with systematic bias of predicted clozapine plasma concentration improving from -138.48 ng/ml to -74.65 ng/ml. A high level of covariate virtualization (demographic, environmental, and genotype) may be required for MIPD using VTs.

Olanzapine/Samidorphan: A New Option for the Treatment of Adults With Schizophrenia or Bipolar I Disorder

Objective

To review the pharmacology, pharmacokinetics, and efficacy and safety data of a combination of olanzapine and samidorphan (OLZ/SAM) for the treatment of schizophrenia and bipolar I disorder, which mitigates the possible unwanted side effects of weight gain associated with olanzapine (OLZ).

Data Sources

The review was done with a bibliographic survey of studies using MEDLINE/PubMed (January 1999-May 2021) database using the keywords olanzapine and samidorphan. Abstracts, scientific posters, and information from the manufacturer's product labeling were evaluated for inclusion. Inclusion criteria: phase 2, phase 3, and open-labeled studies that evaluated the use of OLZ/SAM for the treatment of schizophrenia and bipolar I disorder.

Data Synthesis

We have included one phase 2 dose-ranging exploratory study, two phase 3 efficacy and safety studies, and several open-label extension studies without a comparator. For the treatment of schizophrenia, OLZ/SAM and OLZ alone were analyzed in 2 randomized, double-blind comparison studies of approximately 960 patients. Analysis indicated that OLZ (5-20 mg)/SAM (10 mg) significantly mitigated the side effect of weight gain compared with OLZ alone (control) while maintaining antipsychotic efficacy. For bipolar I disorder, OLZ/SAM was approved as an acute treatment for manic or mixed episodes, as well as an adjunct to valproate or lithium for manic/mixed episodes based on bridging strategy allowed by the Food and Drug Administration.

Relevance to Patient Care and Clinical Practice

The combination of olanzapine and samidorphan demonstrated efficacy for the treatment of schizophrenia with a dosage range of 5 to 20 mg OLZ to a 10-mg fixed dose of samidorphan. Advantages of this drug combination include once-daily dosing, favorable tolerability, and most importantly, mitigation of weight gain, which may encourage adherence, when compared with OLZ alone.

Conclusion

The new combination treatment of OLZ/SAM is a unique antipsychotic formulation to provide the recognized efficacious treatment of OLZ, while mitigating the weight gain and possibly the weight-related adverse effects secondary to OLZ monotherapy.

Olanzapine/Samidorphan: A New Combination Treatment for Schizophrenia and Bipolar I Disorder Intended to Reduce Weight Gain

Olanzapine is a second-generation antipsychotic with established efficacy in several psychiatric disease states, but its use is limited because of weight gain and metabolic side effects. Samidorphan is a novel opioid antagonist that binds to mu-opioid, kappa-opioid, and delta-opioid receptors and is hypothesized to reduce cravings for high-calorie foods thus attenuating antipsychotic-induced weight gain. The combination product olanzapine/samidorphan was approved by the US Food and Drug Administration in June 2021 for the treatment of schizophrenia and bipolar I disorder; this article reviews the pharmacological properties of oral olanzapine/samidorphan and its clinical efficacy and tolerability with a focus on mitigation of olanzapine-induced weight gain in these patient populations. In clinical trials, the combination of olanzapine/samidorphan was associated with significantly less weight gain and smaller increases in waist circumference as compared with olanzapine monotherapy. Olanzapine/samidorphan demonstrated similar efficacy as olanzapine monotherapy and was well tolerated. Weight gain and metabolic side effects associated with olanzapine monotherapy can result in tolerability issues and potentially medication nonadherence. Olanzapine/samidorphan is an effective treatment for schizophrenia and bipolar I disorder with less weight gain than olanzapine monotherapy.

Endogenous opiates and behavior: 2020

This paper is the forty-third consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2020 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

Physiologically Based Pharmacokinetic Modeling in Pregnant Women Suggests Minor Decrease in Maternal Exposure to Olanzapine

Pregnancy is accompanied by significant physiological changes that might affect the in vivo drug disposition. Olanzapine is prescribed to pregnant women with schizophrenia, while its pharmacokinetics during pregnancy remains unclear. This study aimed to develop a physiologically based pharmacokinetic (PBPK) model of olanzapine in the pregnant population. With the contributions of each clearance pathway determined beforehand, a full PBPK model was developed and validated in the non-pregnant population. This model was then extrapolated to predict steady-state pharmacokinetics in the three trimesters of pregnancy by introducing gestation-related alterations. The model adequately simulated the reported time-concentration curves. The geometric mean fold error of Cmax and AUC was 1.14 and 1.09, respectively. The model predicted that under 10 mg daily dose, the systematic exposure of olanzapine had minor changes (less than 28%) throughout pregnancy. We proposed that the reduction in cytochrome P4501A2 activity is counteracted by the induction of other enzymes, especially glucuronyltransferase1A4. In conclusion, the PBPK model simulations suggest that, at least at the tested stages of pregnancy, dose adjustment of olanzapine can hardly be recommended for pregnant women if effective treatment was achieved before the onset of pregnancy and if fetal toxicity can be ruled out.

Assembling the P450 puzzle: on the sources of nonadditivity in drug metabolism

There is an increasing number of indications of an oversimplification in the premise that the cumulative properties of the human drug-metabolizing ensemble represent a simple aggregate of the properties of the constituting enzymes. Recent studies of the functional effects of hetero-association of multiple cytochrome P450 species and their interactions with metabolically related enzymes revealed a tight integration in the drug-metabolizing ensemble. In our opinion, the sources of interindividual variability in drug metabolism can be elucidated only when considering this ensemble as a multienzyme system, the functional parameters of which are determined by interactions between its constituents. In this article, we present a conceptual model providing a mechanistic explanation for the functional effects of the interactions between multiple P450 species and propose a clue to understanding the nonadditive behavior of the drug-metabolizing ensemble.

Using physiologically-based pharmacokinetic modeling for predicting the effects of hepatic impairment on the pharmacokinetics of olanzapine and samidorphan given as a combination tablet

A combination of olanzapine and samidorphan (OLZ/SAM) was recently approved by the US Food and Drug Administration for treatment of patients with schizophrenia or bipolar I disorder. The effects of moderate hepatic impairment on the pharmacokinetics (PKs) of olanzapine and samidorphan after a single dose of OLZ/SAM were characterized in a clinical study. Physiologically-based pharmacokinetic (PBPK) modeling was used to extend the clinical findings to predict the effects of varying degrees of hepatic impairment on the PKs of olanzapine and samidorphan. A previously developed PBPK model for OLZ/SAM was refined to recover the observed pharmacokinetic differences between individuals with moderate hepatic impairment and healthy controls. The optimized model was applied to predict changes in olanzapine and samidorphan PKs after multiple once-daily doses of OLZ/SAM in subjects with mild, moderate, and severe hepatic impairment relative to healthy controls. Modifications to model parameters, including absorption rate constant and fraction unbound to plasma protein, were made to recover the observed change in the PKs of olanzapine and samidorphan in individuals with moderate hepatic impairment. In applying the optimized model, mild, moderate, and severe hepatic impairment were predicted to increase steady-state total systemic exposures by 1.1-, 1.5-, and 1.6-fold, respectively, for olanzapine, and by 1.2-, 1.9-, and 2.3-fold, respectively, for samidorphan. PBPK modeling allowed for prediction of untested clinical scenarios of varying degrees of hepatic impairment in lieu of additional clinical studies.

Quantifying the Impact of Phenoconversion on Medications With Actionable Pharmacogenomic Guideline Recommendations in an Acute Aged Persons Mental Health Setting

Introduction: Polypharmacy and genetic variants that strongly influence medication response (pharmacogenomics, PGx) are two well-described risk factors for adverse drug reactions. Complexities arise in interpreting PGx results in the presence of co-administered medications that can cause cytochrome P450 enzyme phenoconversion. Aim: To quantify phenoconversion in a cohort of acute aged persons mental health patients and evaluate its impact on the reporting of medications with actionable PGx guideline recommendations (APRs). Methods: Acute aged persons mental health patients (N = 137) with PGx and medication data at admission and discharge were selected to describe phenoconversion frequencies for CYP2D6, CYP2C19 and CYP2C9 enzymes. The expected impact of phenoconversion was then assessed on the reporting of medications with APRs. Results: Post-phenoconversion, the predicted frequency at admission and discharge increased for CYP2D6 intermediate metabolisers (IMs) by 11.7 and 16.1%, respectively. Similarly, for CYP2C19 IMs, the predicted frequency at admission and discharge increased by 13.1 and 11.7%, respectively. Nineteen medications with APRs were prescribed 120 times at admission, of which 50 (42%) had APRs pre-phenoconversion, increasing to 60 prescriptions (50%) post-phenoconversion. At discharge, 18 medications with APRs were prescribed 122 times, of which 48 (39%) had APRs pre-phenoconversion, increasing to 57 prescriptions (47%) post-phenoconversion. Discussion: Aged persons mental health patients are commonly prescribed medications with APRs, but interpretation of these recommendations must consider the effects of phenoconversion. Adopting a collaborative care model between prescribers and clinical pharmacists should be considered to address phenoconversion and ensure the potential benefits of PGx are maximised.

Application of Physiologically Based Pharmacokinetic Modeling to Predict the Effect of Renal Impairment on the Pharmacokinetics of Olanzapine and Samidorphan Given in Combination

BACKGROUND

A combination of the antipsychotic olanzapine and opioid receptor antagonist samidorphan (OLZ/SAM) is in development for the treatment of patients with schizophrenia or bipolar I disorder. The effect of severe renal impairment on the pharmacokinetics of olanzapine and samidorphan after a single oral dose of OLZ/SAM was evaluated in a clinical study. Complementary to the clinical findings, physiologically based pharmacokinetic modeling was used to assess the effects of varying degrees of renal impairment on the pharmacokinetics of olanzapine and samidorphan.

METHODS

A physiologically based pharmacokinetic model for OLZ/SAM was developed and validated by comparing model-simulated data with observed clinical data. The model was applied to predict changes in olanzapine and samidorphan pharmacokinetics after administration of OLZ/SAM in subjects with mild, moderate, and severe renal impairment relative to age-matched controls with normal renal function.

RESULTS

The model predicted 1.5- and 2.2-fold increases in olanzapine and samidorphan area under the plasma concentration-time curve (AUC), respectively, after a single dose of OLZ/SAM in subjects with severe renal impairment vs controls, which was consistent with results from the clinical study. Application of the model prediction indicated increases in steady-state olanzapine AUC of 1.2-, 1.5-, and 1.6-fold, and samidorphan AUC of 1.4-, 1.8-, and 2.2-fold, in subjects with mild, moderate, and severe renal impairment, respectively, relative to healthy controls.

CONCLUSIONS

Physiologically based pharmacokinetic modeling extended the findings from a clinical study in severe renal impairment to other untested clinical scenarios; these data could be of interest to clinicians treating patients with renal impairment.