Population Pharmacokinetic and Exposure-Response Analyses for Efficacy and Safety of Risankizumab in Patients With Active Crohn's Disease.

The population pharmacokinetics (PK) of risankizumab and exposure-response relationships for efficacy and safety in patients with Crohn's disease (CD) were characterized using data from phase II and III studies to support dosing regimen selection. A two-compartment model with first-order absorption and first-order elimination adequately described risankizumab PK. Covariates including sex, baseline fecal calprotectin, corticosteroid use, baseline creatinine clearance, body weight, and baseline albumin were statistically correlated with risankizumab clearance, but their impact on exposure was not clinically relevant for efficacy or safety. Exposure-response analyses showed that exposures associated with the 600 mg intravenous (i.v.) induction dose at Weeks 0, 4, and 8 achieved a near maximal response for all efficacy end points evaluated, with negligible added benefit from the 1,200 mg i.v. regimen. By Week 52 of the maintenance treatment, trends of higher responses were observed for the exposure range associated with the 360 mg subcutaneous (s.c.) every-8-weeks (Q8W) regimen for most of the evaluated efficacy end points, particularly for the more stringent end points, such as endoscopic remission and ulcer-free endoscopy. Exposure-response analyses for safety did not identify any apparent relationship between exposure and safety. These results supported the final dose recommendation of 600 mg i.v. at Weeks 0, 4, and 8, followed by 360 mg s.c. at Week 12 and Q8W thereafter in patients with CD.

A Population Pharmacokinetic Model of (R)- and (S-) Oxybutynin and Its Active Metabolites After Oral and Intravesical Administration to Healthy Volunteers.

Oxybutynin is a racemic anticholinergic drug used for the symptomatic treatment of detrusor overactivity. The formation of active metabolites related to tolerability problems depends on the route of administration. The objective of this evaluation was to develop a pharmacokinetic model for oral/intravesical administration as the basis for simulations with different dosages. Data from a published changeover clinical study with 18 healthy adults receiving a single oral dose of 5 mg immediate-release oxybutynin and single and multiple intravesical doses of 10 mg oxybutynin solution was evaluated. Enantioselective plasma concentrations of oxybutynin and N-desethyloxybutynin (NDO) were used to establish a population pharmacokinetic model using nonlinear mixed-effects modeling with NONMEM 7.4.1. For both enantiomers, the data were described well by a 2-compartment model for oxybutynin with an additional compartment for NDO. Oxybutynin absorption was modeled by transit compartments for oral and first-order absorption for intravesical application. Bioavailability of the more active (R)-enantiomer was 7% for oral and 10%-22% for intravesical administration. In simulations, intravesical doses of 5 to 15 mg (R)-oxybutynin administered 2 to 3 times daily decreased peak-trough fluctuations of NDO to 8% compared with 24% after oral administration. The NDO/oxybutynin ratio was reduced from 17 after oral administration to unity. Chronic intravesical versus oral administration of (R)-oxybutynin generates distinctly lower and less variable concentrations of (R)-NDO. Pharmacokinetic simulations suggest that exposure for 12.5 mg (R)-oxybutynin administered twice daily might not compromise efficacy and tolerability compared with exposure for standard thrice-daily administrations. This assumption needs to be assessed in clinical studies.

Population Pharmacokinetics of Glecaprevir/Pibrentasvir in HCV-infected Japanese Subjects in Phase 3 CERTAIN-1 and CERTAIN-2 Trials.

Glecaprevir (GLE)/pibrentasvir (PIB) 300 mg/120 mg once daily (Mavyret/Maviret) is an all-oral, pangenotypic, interferon- and ribavirin-free combination regimen approved for the treatment of chronic hepatitis C virus (HCV) infection. The objective of the current analyses was to characterize the pharmacokinetics (PK) of GLE/PIB in HCV-infected Japanese patients. Data from 332 subjects enrolled in 2 Japan phase 3 trials, CERTAIN-1 and CERTAIN-2, were used in the analyses. Pharmacokinetics of GLE/PIB were characterized using a nonlinear mixed-effects modeling. The analyses evaluated the impact of covariates (concomitant medications and demographic and clinical covariates such as renal impairment, effect of cirrhotic status) on GLE/PIB PK. GLE and PIB PK were described by 1- and 2-compartment models, respectively. Presence of cirrhosis, age, and body weight were identified as significant covariates on GLE/PIB PK. A trend toward higher GLE and PIB exposures in older patients and higher PIB exposures in heavier patients was observed; however, these increases were not considered clinically meaningful. GLE and PIB exposures were higher in HCV-infected subjects with cirrhosis (Child-Pugh A; GLE area under the plasma concentration-time curve was 160% higher, and PIB area under the plasma concentration-time curve was 21% higher) compared to subjects without cirrhosis. Renal function (including subjects with end-stage renal disease with dialysis) had no impact on GLE or PIB exposures. The GLE/PIB dose was well tolerated in the Japanese population, and no dose adjustment is needed for the evaluated intrinsic and extrinsic factors.

Population pharmacokinetic and pharmacodynamic modeling of epinephrine administered using a mobile inhaler.

Inhaled epinephrine is a potential alternative to self-administered intramuscular epinephrine in imminent anaphylactic reactions. The objective was to develop a pharmacokinetic-pharmacodynamic model describing exposure and effects on heart rate of inhaled epinephrine. Data from a 4-phase cross-over clinical trial in 9 healthy volunteers including 0.3 mg intramuscular epinephrine, two doses of inhaled epinephrine (4 mg/mL solution administered during [mean] 18 and 25 min, respectively) using a mobile pocket inhaler, and an inhaled placebo were analyzed using mixed-effects modeling. Inhaled epinephrine was available almost immediately and more rapidly than via the intramuscular route (absorption half-live 29 min). Epinephrine plasma concentrations declined rapidly after terminating inhalation (elimination half-life 4.1 min) offering the option to stop exposure in case of adverse events. While the expected maximum concentration was higher for inhaled epinephrine, this was not associated with safety concerns due to only moderate additional hemodynamic effects compared to intramuscular administration. Bioavailability after inhalation (4.7%) was subject to high interindividual and interoccasional variability highlighting that training of inhalation would be essential for patients. The proposed model suggests that the use of a highly concentrated epinephrine solution via inhalation may offer an effective treatment option in anaphylaxis, while efficacy in patients remains to be shown.

A Modeling and Simulation Framework for Adverse Events in Erlotinib-Treated Non-Small-Cell Lung Cancer Patients.

Treatment with erlotinib, an epidermal growth factor receptor tyrosine kinase inhibitor used for treating non-small-cell lung cancer (NSCLC) and other cancers, is frequently associated with adverse events (AE). We present a modeling and simulation framework for the most common erlotinib-induced AE, rash, and diarrhea, providing insights into erlotinib toxicity. We used the framework to investigate the safety of high-dose erlotinib pulses proposed to limit acquired resistance while treating NSCLC. Continuous-time Markov models were developed using rash and diarrhea AE data from 39 NSCLC patients treated with erlotinib (150 mg/day). Exposure and different covariates were investigated as predictors of variability. Rash was also tested as a survival predictor. Models developed were used in a simulation analysis to compare the toxicities of different regimens, including the previously mentioned pulsed strategy. Probabilities of experiencing rash or diarrhea were found to be highest early during treatment. Rash, but not diarrhea, was positively correlated with erlotinib exposure. In contrast with some common understandings, radiotherapy decreased transitioning to higher rash grades by 81% (p < 0.01), and experiencing rash was not correlated with positive survival outcomes. Model simulations predicted that the proposed pulsed regimen (1600 mg/week + 50 mg/day remaining week days) results in a maximum of 20% of the patients suffering from severe rash throughout the treatment course in comparison to 12% when treated with standard dosing (150 mg/day). In conclusion, the framework demonstrated that radiotherapy attenuates erlotinib-induced rash, providing an opportunity to use radiotherapy and erlotinib together, and demonstrated the tolerability of high-dose pulses intended to address acquired resistance to erlotinib.

Modeling tumor dynamics and overall survival in advanced non-small-cell lung cancer treated with erlotinib.

INTRODUCTION: Pharmacostatistical models can quantify different relationships and improve decision making in personalized medicine and drug development. Our objectives were to develop models describing non-small-cell lung cancer (NSCLC) dynamics during first-line treatment with erlotinib, and survival of the cohort. METHODS: Data from patients with advanced NSCLC (n = 39) treated first-line with erlotinib (150 mg/day) were analyzed using nonlinear mixed effects modeling. Exposure-driven disease-drug models were built to describe tumor metabolic and proliferative dynamics evaluated by positron emission tomography (PET) using 2'-deoxy-2'-[F]fluoro-D-glucose (FDG) and 3'-[F]fluoro-3'-deoxy-L-thymidine (FLT), respectively, at baseline, weeks 1 and 6 after starting erlotinib treatment. A parametric time-to-event model was built to describe overall survival (OS). Demographics, histology, mutational, smoking, and baseline performance statuses were tested for their effects on models developed, in addition to tumor dynamics on survival. RESULTS: An exponential relationship described progression, and a concentration-driven drug effect model described erlotinib effect. An activating epidermal growth factor receptor (EGFR) mutation increased the drug effect as assessed using FDG-PET by 2.19-fold (95% confidence interval [CI]:1.35-4.44). An exponential distribution described the times-to-death distribution. Baseline FDG uptake (p=0.0005; hazard ratio [HR] =1.26 for every unit increase, 95%CI: 1.13-1.42) and relative change in FDG uptake after 1 week of treatment (p=0.0073; HR=0.84 for every 10% drop, 95%CI: 0.71-0.91) were significant OS predictors irrespective of the EGFR mutational status. FLT-PET was statistically less significant than FDG-PET for OS prediction. CONCLUSION: Models describing tumor dynamics and survival of advanced NSCLC patients first-treated with erlotinib were developed. The impacts of different covariates were quantified.

Population pharmacokinetic analysis of circadian rhythms in hepatic CYP3A activity using midazolam.

Diurnal changes in the activity of drug metabolizing enzymes may contribute to the variability in drug disposition and drug effects. The aim of this study was to quantify the circadian rhythmicity exhibited by hepatic CYP3A. A 10 µg/kg intravenous bolus dose, followed by a 30-hour 4 µg/kg/h intravenous infusion of midazolam, used as a probe substrate for hepatic CYP3A activity, was administered to 16 healthy volunteers (8 males and 8 females). Blood samples were drawn hourly for 24 hours after achieving steady state, and plasma concentrations of midazolam and its main metabolite 1-OH midazolam were determined. Population pharmacokinetic analysis was performed using nonlinear mixed effects modeling. One-compartment pharmacokinetic models best described midazolam and 1-OH midazolam pharmacokinetic disposition. An unequivocal but minor diurnal pattern was identified in the midazolam plasma concentration profiles, which was described using a cosine function with a 24-hours period. The fluctuation in the relative CYP3A activity ranged between 10% above average around 15:00, and 10% below average around 03:00. None of the covariates tested had a significant impact on the parameters estimated. Although a diurnal pattern in hepatic CYP3A activity was identified, its magnitude suggests that it is small and without clinical significance for drug therapy.

A semiphysiological population pharmacokinetic model for dynamic inhibition of liver and gut wall cytochrome P450 3A by voriconazole.

BACKGROUND: Accurate predictions of cytochrome P450 (CYP) 3A-mediated drug-drug interactions (DDIs) account for dynamic changes of CYP3A activity at both major expression sites (liver and gut wall) by considering the full pharmacokinetic profile of the perpetrator and the substrate. Physiological-based in vitro-in vivo extrapolation models have become of increasing interest. However, due to discrepancies between the predicted and observed magnitude of DDIs, the role of models fully based on in vivo data is still essential. OBJECTIVE: The primary objective of this study was to develop a coupled dynamic model for the interaction of the CYP3A inhibitor voriconazole and the prototypical CYP3A substrate midazolam. METHODS: Raw concentration data were obtained from a DDI study. Ten subjects were given either no pretreatment (control) or voriconazole twice daily orally. Midazolam was given either intravenously or orally after the last voriconazole dose and during control phases. Data analysis was performed by the population pharmacokinetic approach using non-linear mixed effects modelling (NONMEM 7.2.0). Model evaluation was performed using visual predictive checks and bootstrap analysis. RESULTS: A semiphysiological model was able to describe the pharmacokinetics of midazolam, its major metabolite and voriconazole simultaneously. By considering the temporal disposition of all three substances in the liver and gut wall, a time-varying CYP3A inhibition process was implemented. Only the incorporation of hypothetical enzyme site compartments resulted in an adequate fit, suggesting a sustained inhibitory effect through accumulation. Novel key features of this analysis are the identification of (1) an apparent sustained inhibitory effect by voriconazole due to a proposed quasi accumulation at the enzyme site, (2) a significantly reduced inhibitory potency of intravenous voriconazole for oral substrates, (3) voriconazole as a likely uridine diphosphate glucuronosyltransferase (UGT) 2B inhibitor and (4) considerable sources of interindividual variability. CONCLUSION: The proposed semiphysiological modelling approach generated a mechanistic description of the complex DDI occurring at major CYP3A expression sites and thus may serve as a powerful tool to maximise information acquired from clinical DDI studies. The model has been shown to draw precise and accurate predictions. Therefore, simulations based on this kind of models may be used for various clinical scenarios to improve pharmacotherapy.

Pharmacokinetic-pharmacodynamic modeling of antipsychotic drugs in patients with schizophrenia Part I: the use of PANSS total score and clinical utility.

BACKGROUND: To develop a pharmacokinetic-pharmacodynamic (PK-PD) model using individual-level data of Positive and Negative Syndrome Scale (PANSS) total score to characterize the antipsychotic drug effect taking into account the placebo effect and dropout rate. In addition, a clinical utility (CU) criterion that describes the usefulness of a drug therapy was calculated using the efficacy of the drug and dropout rates. METHODS: Data from 12 clinical trials in schizophrenia patients was used to quantify the effects of the antipsychotic drugs (APs), namely, haloperidol, risperidone, olanzapine, ziprasidone and paliperidone. Compartmental PK models were used to describe the time course of plasma drug concentrations. The combination of an Emax and the Weibull model was used to describe the drug and placebo effects. The steady-state drug concentrations were assumed to be the drivers of the exposure-response relationship. An exponential model was utilized to identify the predictors of probability of dropout. Simulations were performed to check the predictability of the model, and to calculate the CU of the drugs based on PANSS scores and dropout rates. RESULTS: The maximal drug effect (E(max)) was highest for olanzapine whilst it was lowest for ziprasidone. Higher observed PANSS scores resulted in a greater likelihood of dropout. Taking into account the efficacy and the drop-out rate, all APs possessed a comparable CU at the therapeutic doses. The resulting PK-PD model parameters were used to compute the effective concentration and dose required to produce a clinically meaningful 30% drop in PANSS score from the baseline. CONCLUSIONS: The developed PK-PD model and the associated CU score allow the evaluation of the time course of the PANSS scores of the different APs and a proper comparison of their clinically relevant treatments effects.

Pharmacokinetic-pharmacodynamic modelling of antipsychotic drugs in patients with schizophrenia: part II: the use of subscales of the PANSS score.

BACKGROUND AND OBJECTIVES: The superiority of atypical antipsychotics (also known as second-generation antipsychotics (SGAs)) over typical antipsychotics (first generation antipsychotics (FGAs)) for negative symptom control in schizophrenic patients is widely debated. The objective of this study was to characterize the time course of the scores of the 3 subscales (positive, negative, general) of the Positive and Negative Syndrome Scale (PANSS) after treatment of patients with antipsychotics, and to compare the control of negative symptom by SGAs versus a FGA (haloperidol) using pharmacokinetic and pharmacodynamic (PKPD) modelling. In addition, to obtain insight in the relationship between the clinical efficacy and the in vitro and in vivo receptor pharmacology profiles, the D2 and 5-HT2A receptor occupancy levels of antipsychotics were related to the effective concentrations. METHODS: The PKPD model structure developed earlier (part I) was used to quantify the drug effect using the 3 PANSS subscales. The maximum drug effect sizes (Emax) of oral SGAs (risperidone, olanzapine, ziprasidone, and paliperidone) across PANSS subscales were compared with that of haloperidol, while accounting for the placebo effect. Using the estimates of PKPD model parameters, the effective concentrations (Ceff) needed to achieve 30% reduction in the PANSS subscales were computed. Calculated effective concentrations were then correlated with receptor pharmacology profiles. RESULTS: Positive symptoms of schizophrenia responded well to all antipsychotics. Olanzapine showed a better effect towards negative symptoms than the other SGAs and haloperidol. Dropout modelling results showed that the probability of a patient dropping out from a trial was associated with all subscales, but was more strongly correlated with the positive subscale than with the negative or the general subscales. Our results suggest that different levels of D2 or 5-HT2A receptor occupancy are required to achieve improvement in PANSS subscales. CONCLUSIONS: This PKPD modelling approach can be helpful to differentiate the effect of antipsychotics across the different symptom domains of schizophrenia. Our analysis revealed that olanzapine seems to be superior in treating the negative symptoms compared to other non-clozapine SGAs. The relationship between receptor pharmacology profiles of the antipsychotics and their clinical efficacy is not yet fully understood.

Modeling NSCLC progression: recent advances and opportunities available.

Non-small cell lung cancer (NSCLC) is one of the leading causes of death around the world with an estimated 5-year relative survival rate of 16% at diagnosis. Development of drugs treating NSCLC is not easy, and the success rate for an anticancer treatment to pass through the whole clinical development process is as low as 5%. Modeling and simulation lend themselves as tools which can potentially streamline drug development. A critical component of the models developed is a description of how the disease progresses over time and how a treatment would affect its trajectory. Our aim was to review the literature to present the models and growth functions which have been used for describing NSCLC dynamics, and how anticancer treatments can affect such dynamics, both in animals and in humans. Only a limited set of models were identified for such a purpose. Most of the models which have been used were descriptive of tumor growth, yet there were attempts to account for the underlying processes, especially in animals where it is more feasible to collect data needed for developing such models. Moreover, we discuss how modeling and simulation can aid in decision making across the different stages of drug development. Based on some encouraging results from trials of other cancer types where modeling tumor dynamics has played an important role, we propose further exploration of NSCLC using model-based techniques and further use of these techniques in designing and evaluating NSCLC trials.

Modelling and simulation of the Positive and Negative Syndrome Scale (PANSS) time course and dropout hazard in placebo arms of schizophrenia clinical trials.

BACKGROUND AND OBJECTIVES: The likelihood of detecting a therapeutic signal of an effective drug for schizophrenia is impeded by a high placebo effect and by high dropout of patients. Several unsuccessful trials of schizophrenia, at least partly due to highly variable placebo effects, have indicated the necessity for a robust methodology to evaluate such a placebo effect and reasons for dropout. Hence, the objectives of this analysis were to (i) develop a longitudinal placebo model that accounts for dropouts and predictors of the placebo effect, using the Positive and Negative Syndrome Scale (PANSS) score; (ii) compare the performance of empirical and semi-mechanistic placebo models; and (iii) compare different time-to-event (TTE) dropout modelling approaches used to account for dropouts. METHODS: The PANSS scores from 1436 individual patients were used to develop and validate a placebo model. This pooled dataset included 16 trials (conducted between 1989 and 2009), with different study durations, in both acute and chronic schizophrenic patients. A nonlinear mixed-effects modelling approach was employed, using NONMEM VII software. RESULTS: Among the different tested placebo models, the Weibull model and the indirect response model adequately described the PANSS data. Covariate analysis showed that the disease condition, study duration, study year, geographic region where the trial was conducted, and route of administration were important predictors for the placebo effect. All three parametric TTE dropout models, namely the exponential, Weibull and Gompertz models, described the probability of patients dropping out from a clinical trial equally well. The study duration and trial phase were found to be predictors for high dropout rates. Results of joint modelling of the placebo effect and dropouts indicated that the probability of patients dropping out is associated with an observed high PANSS score. The indirect response model was found to be a slightly better model than the Weibull placebo model to describe the time course of the PANSS score. CONCLUSIONS: Our modelling approach was shown to adequately simulate the longitudinal PANSS data and the dropout trends after placebo treatment. Data analyses suggest that the Weibull and indirect response models are more robust than other placebo models to describe the nonlinear trends in the PANSS score. The developed placebo models, accounting for dropouts and predictors of the placebo effect, could be a useful tool in the evaluation of new trial designs and for better quantification of antipsychotic drug effects.