Physiologically-based pharmacokinetic modeling of the drug-drug interaction between ivacaftor and lefamulin in cystic fibrosis patients

Lefamulin is being evaluated as a treatment for bacterial exacerbations in cystic fibrosis (CF). Ivacaftor is approved for the treatment of patients with CF. Lefamulin is a moderate CYP3A inhibitor and co-administration with ivacaftor may result in a drug-drug interaction (DDI). A CF population was built based on literature using the Simcyp Simulator. A previously developed and validated physiologically-based pharmacokinetic (PBPK) model for ivacaftor was used. A PBPK model for lefamulin was developed and verified. Predicted concentrations and pharmacokinetic (PK) parameters for both ivacaftor and lefamulin in healthy subjects and patients with CF were in reasonable agreement with observed data (within 1.4-fold, majority within 1.25-fold). The lefamulin model as a CYP3A4 perpetrator was validated using a different Ki value for oral (p.o.) and intravenous (i.v.) routes. The simulated changes in area under the curve of ivacaftor in patients with CF when co-administered with p.o. and i.v. lefamulin were weak-to-moderate. The predicted change in ivacaftor PK when co-administered with oral lefamulin was less than observed between ivacaftor and fluconazole. These results suggest a low liability for a DDI between lefamulin and ivacaftor in patients with CF.

Creation of Novel Sensitive Probe Substrate and Moderate Inhibitor Models for a Comprehensive Prediction of CYP2C8 Interactions for Tucatinib

A physiologically-based pharmacokinetic (PBPK) model was developed to simulate plasma concentrations of tucatinib (TUKYSA®) after single-dose or multiple-dose administration of 300 mg b.i.d. orally. This PBPK model was subsequently applied to support evaluation of drug-drug interaction (DDI) risk as a perpetrator resulting from tucatinib inhibition of CYP3A4, CYP2C8, CYP2C9, P-gp, or MATE1/2-K. The PBPK model was also applied to support evaluation of DDI risk as a victim resulting from co-administration with CYP3A4 or CYP2C8 inhibitors, or a CYP3A4 inducer. After refinement with clinical DDI data, the final PBPK model was able to recover the clinically observed single and multiple-dose plasma concentrations for tucatinib when tucatinib was administered as a single agent in healthy subjects. In addition, the final model was able to recover clinically observed plasma concentrations of tucatinib when administered in combination with itraconazole, rifampin, or gemfibrozil as well as clinically observed plasma concentrations of probe substrates of CYP3A4, CYP2C8, CYP2C9, P-gp, or MATE1/2-K. The PBPK model was then applied to prospectively predict the potential perpetrator or victim DDIs with other substrates, inducers, or inhibitors. To simulate a potential interaction with a moderate CYP2C8 inhibitor, two novel PBPK models representing a moderate CYP2C8 inhibitor and a sensitive CYP2C8 substrate were developed based on the existing PBPK models for gemfibrozil and rosiglitazone, respectively. The simulated population geometric mean area under the curve ratio of tucatinib with a moderate CYP2C8 inhibitor ranged from 1.98- to 3.08-fold, and based on these results, no dose modifications were proposed for moderate CYP2C8 inhibitors for the tucatinib label.

Real-world application of PBPK in drug discovery

The utility of PBPK models in support of drug development has been well documented. During the discovery stage, PBPK has increasingly been applied for early risk assessment, prediction of human dose, toxicokinetic dose projection and early formulation assessment. Previous review articles have proposed model building and application strategies for PBPK-based first in human predictions with comprehensive descriptions of the individual components of PBPK models. This includes the generation of decision trees, based on comprehensive literature reviews, to guide the application of PBPK in the discovery setting. The goal of this mini review is to provide additional guidance on the real-world application of PBPK, in support of the discovery stage of drug development. In this mini review, our goal is to provide guidance on the typical steps involved in the development and application of a PBPK model during drug discovery to assist in decision making. We have illustrated our recommended approach through description of case examples, where PBPK has been successfully applied to aid in human PK projection, candidate selection and prediction of drug interaction liability for parent and metabolite. Through these case studies, we have highlighted fundamental issues, including pre-verification in preclinical species, the application of empirical scalars in the prediction of in vivo clearance from in vitro systems, in silico prediction of permeability and the exploration of aqueous and biorelevant solubility data to predict dissolution. In addition, current knowledge gaps have been highlighted and future directions proposed. Significance Statement Through description of three case studies, we have highlighted the fundamental principles of PBPK application during drug discovery. These include pre-verification of the model in preclinical species, application of empirical scalars where necessary in the prediction of clearance, in silico prediction of permeability, and the exploration of aqueous and biorelevant solubility data to predict dissolution. In addition, current knowledge gaps have been highlighted and future directions proposed.

A comprehensive evaluation in clinic and physiologically-based pharmacokinetic modeling and simulation to confirm lack of cytochrome P450-mediated drug-drug interaction potential for pomotrelvir

Pomotrelvir is a new chemical entity and potent direct-acting antiviral inhibitor of the main protease of coronaviruses. Here the cytochrome P450 (CYP)-mediated drug-drug interaction (DDI) potential of pomotrelvir was evaluated for major CYP isoforms, starting with in vitro assays followed by the basic static model assessment. The identified CYP3A4-mediated potential DDIs were evaluated clinically at a supratherapeutic dose of 1050 mg twice daily (b.i.d.) of pomotrelvir, including pomotrelvir coadministration with ritonavir (strong inhibitor of CYP3A4) or midazolam (sensitive substrate of CYP3A4). Furthermore, a physiologically-based pharmacokinetic (PBPK) model was developed within the Simcyp Population-based Simulator using in vitro and in vivo information and validated with available human pharmacokinetic (PK) data. The PBPK model was simulated to assess the DDI potential for CYP isoforms that pomotrelvir has shown a weak to moderate DDI in vitro and for CYP3A4 at the therapeutic dose of 700 mg b.i.d. To support the use of pomotrelvir in women of childbearing potential, the impact of pomotrelvir on the exposure of the representative oral hormonal contraceptive drugs ethinyl estradiol and levonorgestrel was assessed using the PBPK model. The overall assessment suggested weak inhibition of pomotrelvir on CYP3A4 and minimal impact of a strong CYP3A4 inducer or inhibitor on pomotrelvir PK. Therefore, pomotrelvir is not anticipated to have clinically meaningful DDIs at the clinical dose. These comprehensive in vitro, in clinic, and in silico efforts indicate that the DDI potential of pomotrelvir is minimal, so excluding patients on concomitant medicines in clinical studies would not be required.

Development and application of a PBPK modeling strategy to support antimalarial drug development

As part of a collaboration between Medicines for Malaria Venture (MMV), Certara UK and Monash University, physiologically-based pharmacokinetic (PBPK) models were developed for 20 antimalarials, using data obtained from standardized in vitro assays and clinical studies within the literature. The models have been applied within antimalarial drug development at MMV for more than 5 years. During this time, a strategy for their impactful use has evolved. All models are described in the supplementary material and are available to researchers. Case studies are also presented, demonstrating real-world development and clinical applications, including the assessment of the drug-drug interaction liability between combination partners or with co-administered drugs. This work emphasizes the benefit of PBPK modeling for antimalarial drug development and decision making, and presents a strategy to integrate it into the research and development process. It also provides a repository of shared information to benefit the global health research community.

Physiologically Based Pharmacokinetic Model Development and Verification for Bioequivalence Testing of Bempedoic Acid Oral Suspension and Reference Tablet Formulation

The bioequivalence of bempedoic acid oral suspension and commercial immediate release (IR) tablet formulations were assessed using a physiologically based pharmacokinetic (PBPK) model. The mechanistic model, developed from clinical mass balance results and in vitro intrinsic solubility, permeability, and dissolution data, was verified against observed clinical pharmacokinetics (PK) results. Model inputs included a fraction of a dose in solution (0.01%), viscosity (118.8 cps), and median particle diameter (50 µm) for the suspension and particle diameter (36.4 µm) for IR tablets. Dissolution was determined in the relevant media (pH 1.2-6.8) in vitro. Model simulations of bioequivalence predicted oral suspension (test) to IR tablet (reference) geometric mean ratio estimates of 96.9% (90% confidence interval [CI]: 92.6-101) for maximum concentration and 98.2% (90% CI: 87.3-111) for the area under the concentration-time curve. Sensitivity analyses showed gastric transit time had a minor impact on model predictions. Oral suspension biopharmaceutical safe space was defined by extremes of particle size and the percent of bempedoic acid in solution. PBPK model simulations predicted that the rate and extent of bempedoic acid absorption are unlikely to exhibit clinically meaningful differences when dosed as an oral suspension compared with an IR tablet without requiring a clinical bioequivalence study in adults.

Tiered approach to evaluate the CYP3A victim and perpetrator drug-drug interaction potential for vonoprazan using PBPK modeling and clinical data to inform labeling

Vonoprazan is metabolized extensively through CYP3A and is an in vitro time-dependent inhibitor of CYP3A. A tiered approach was applied to understand the CYP3A victim and perpetrator drug-drug interaction (DDI) potential for vonoprazan. Mechanistic static modeling suggested vonoprazan is a potential clinically relevant CYP3A inhibitor. Thus, a clinical study was conducted to evaluate the impact of vonoprazan on the exposure of oral midazolam, an index substrate for CYP3A. A physiologically-based pharmacokinetic (PBPK) model for vonoprazan was also developed using in vitro data, drug- and system-specific parameters, and clinical data and observations from a [¹⁴ C] human absorption, distribution, metabolism, and excretion study. The PBPK model was refined and verified using data from a clinical DDI study with the strong CYP3A inhibitor, clarithromycin, to confirm the fraction metabolized by CYP3A, and the oral midazolam clinical DDI data assessing vonoprazan as a time-dependent inhibitor of CYP3A. The verified PBPK model was applied to simulate the anticipated changes in vonoprazan exposure due to moderate and strong CYP3A inducers (efavirenz and rifampin, respectively). The clinical midazolam DDI study indicated weak inhibition of CYP3A, with a less than twofold increase in midazolam exposure. PBPK simulations projected a 50% to 80% reduction in vonoprazan exposure when administered concomitantly with moderate or strong CYP3A inducers. Based on these results, the vonoprazan label was revised and states that lower doses of sensitive CYP3A substrates with a narrow therapeutic index should be used when administered concomitantly with vonoprazan, and co-administration with moderate and strong CYP3A inducers should be avoided.

Cure4Kids: Two decades of knowledge transfer

Cure4Kids is a free web-based knowledge platform for professionals providing care for children with cancer and hematologic diseases, offering its users a comprehensive suite of learning opportunities. It has been a resource for the pediatric oncology community across the world for the past two decades, with 60,107 users having logged in 1,412,514 times with 22,045,553 content hits. A transformation of Cure4Kids is being planned and will include an improved user interface, increased interactivity, and more content.

Outcomes of Children With Low-Grade Gliomas in Low- and Middle-Income Countries: A Systematic Review

PURPOSE

Pediatric CNS tumors are increasingly a priority, particularly with the WHO designation of low-grade glioma (LGG) as one of six index childhood cancers. There are currently limited data on outcomes of pediatric patients with LGGs in low- and middle-income countries (LMICs).

METHODS

To better understand the outcomes of LGGs in LMICs, this systematic review interrogated nine literature databases.

RESULTS

The search identified 14,977 publications. Sixteen studies from 19 countries met the selection criteria and were included for data abstraction and analysis. Eleven studies (69%) were retrospective reviews from single institutions, and one (6%) captured institutional data prospectively. The studies captured a total of 957 patients with a median of 49 patients per study. Seven (44%) of the studies described the treatment modalities used. Of 373 patients for whom there was information, 173 (46%) had a gross total or near total resection, 109 (29%) had a subtotal resection, and 91 (24%) had only a biopsy performed. Seven studies, with a total of 476 patients, described the frequency of use of radiotherapy and/or chemotherapy in the cohorts: 83 of these patients received radiotherapy and 76 received chemotherapy. The 5-year overall survival ranged from 69.2% to 93.5%, although lower survival rates were reported at earlier time points. We identified limitations in the published studies with respect to the cohort sizes and methodologies.

CONCLUSION

The included studies reported survival rates frequently exceeding 80%, although the ultimate number of studies was limited, pointing to the paucity of studies describing the outcomes of children with LGGs in LMICs. This study underscores the need for more robust data on outcomes in pediatric LGG.

Development of a pediatric physiologically-based pharmacokinetic model to support recommended dosing of atezolizumab in children with solid tumors

Background: Atezolizumab has been studied in multiple indications for both pediatric and adult patient populations. Generally, clinical studies enrolling pediatric patients may not collect sufficient pharmacokinetic data to characterize the drug exposure and disposition because of operational, ethical, and logistical challenges including burden to children and blood sample volume limitations. Therefore, mechanistic modeling and simulation may serve as a tool to predict and understand the drug exposure in pediatric patients.

Objective: To use mechanistic physiologically-based pharmacokinetic (PBPK) modeling to predict atezolizumab exposure at a dose of 15 mg/kg (max 1,200 mg) in pediatric patients to support dose rationalization and label recommendations.

Methods: A minimal mechanistic PBPK model was used which incorporated age-dependent changes in physiology and biochemistry that are related to atezolizumab disposition such as endogenous IgG concentration and lymph flow. The PBPK model was developed using both in vitro data and clinically observed data in adults and was verified across dose levels obtained from a phase I and multiple phase III studies in both pediatric patients and adults. The verified model was then used to generate PK predictions for pediatric and adult subjects ranging from 2- to 29-year-old.

Results: Individualized verification in children and in adults showed that the simulated concentrations of atezolizumab were comparable (76% within two-fold and 90% within three-fold, respectively) to the observed data with no bias for either over- or under-prediction. Applying the verified model, the predicted exposure metrics including C_min, C_max, and AUC_tau were consistent between pediatric and adult patients with a geometric mean of pediatric exposure metrics between 0.8- to 1.25-fold of the values in adults.

Conclusion: The results show that a 15 mg/kg (max 1,200 mg) atezolizumab dose administered intravenously in pediatric patients provides comparable atezolizumab exposure to a dose of 1,200 mg in adults. This suggests that a dose of 15 mg/kg will provide adequate and effective atezolizumab exposure in pediatric patients from 2- to 18-year-old.

Opportunities and Challenges for PBPK Model of mAbs in Paediatrics and Pregnancy

New drugs may in some cases need to be tested in paediatric and pregnant patients. However, it is difficult to recruit such patients and there are many ethical issues around their inclusion in clinical trials. Modelling and simulation can help to plan well-designed clinical trials with a reduced number of participants and to bridge gaps where recruitment is difficult. Physiologically based pharmacokinetic (PBPK) models for small molecule drugs have been used to aid study design and dose adjustments in paediatrics and pregnancy, with several publications in the literature. However, published PBPK models for monoclonal antibodies (mAb) in these populations are scarce. Here, the current status of mAb PBPK models in paediatrics and pregnancy is discussed. Seven mAb PBPK models published for paediatrics were found, which report good prediction accuracy across a wide age range. No mAb PBPK models for pregnant women have been published to date. Current challenges to the development of such PBPK models are discussed, including gaps in our knowledge of relevant physiological processes and availability of clinical data to verify models. As the availability of such data increases, it will help to improve our confidence in the PBPK model predictive ability. Advantages for using PBPK models to predict mAb PK in paediatrics and pregnancy are discussed. For example, the ability to incorporate ontogeny and gestational changes in physiology, prediction of maternal, placental and foetal exposure and the ability to make predictions from in vitro and preclinical data prior to clinical data being available.

Estimation of brain receptor occupancy for trazodone immediate release and once a day formulations

Trazodone is approved for the treatment of major depressive disorders, marketed as immediate release (IR), prolonged release, and once a day (OAD) formulation. The different formulations allow different administration schedules and may be useful to facilitate patients’ compliance to the antidepressant treatment. A previously verified physiologically‐based pharmacokinetic model based on in vitro and in vivo information on trazodone pharmacokinetics was applied, aiming at predicting brain receptor occupancy (RO) after single and repeated dosing of the IR formulation and repeated dosing of the OAD formulation in healthy subjects. Receptors included in the simulations were selected using static calculations of RO based on the maximum unbound brain concentration (C_max,brain,u) of trazodone for each formulation and dosing scheme, resulting in 16 receptors being simulated. Seven receptors were simulated for the IR low dose formulation (30 mg), with similar t_onset and duration of coverage (range: 0.09–0.25 h and 2.1–>24 h, respectively) as well as RO (range: 0.64–0.92) predicted between day 1 and day 7 of dosing. The 16 receptors evaluated for the OAD formulation (300 mg) showed high RO (range: 0.97–0.84 for the receptors also covered by the IR formulation and 0.73–0.48 for the remaining) correlating with affinity and similar duration of time above the target threshold to the IR formulation (range: 2–>24 h). The dose‐dependent receptor coverage supports the multimodal activity of trazodone, which may further contribute to its fast antidepressant action and effectiveness in controlling different symptoms in depressed patients.

A Mechanistic Site-Of-Action Model: A Tool for Informing Right Target, Right Compound, And Right Dose for Therapeutic Antagonistic Antibody Programs

Quantitative modeling is increasingly utilized in the drug discovery and development process, from the initial stages of target selection, through clinical studies. The modeling can provide guidance on three major questions–is this the right target, what are the right compound properties, and what is the right dose for moving the best possible candidate forward. In this manuscript, we present a site-of-action modeling framework which we apply to monoclonal antibodies against soluble targets. We give a comprehensive overview of how we construct the model and how we parametrize it and include several examples of how to apply this framework for answering the questions postulated above. The utilities and limitations of this approach are discussed.

Fast-Acting Insulin Aspart Versus Insulin Aspart Using a Second-Generation Hybrid Closed-Loop System in Adults With Type 1 Diabetes: A Randomized, Open-Label, Crossover Trial

OBJECTIVE

To evaluate glucose control using fast-acting insulin aspart (faster aspart) compared with insulin aspart (IAsp) delivered by the MiniMed Advanced Hybrid Closed-Loop (AHCL) system in adults with type 1 diabetes.

RESEARCH DESIGN AND METHODS

In this randomized, open-label, crossover study, participants were assigned to receive faster aspart or IAsp in random order. Stages 1 and 2 comprised of 6 weeks in closed loop, preceded by 2 weeks in open loop. This was followed by stage 3, whereby participants changed directly back to the insulin formulation used in stage 1 for 1 week in closed loop. Participants chose their own meals except for two standardized meal tests, a missed meal bolus and late meal bolus. The primary outcome was the percentage of time sensor glucose values were from 70 to 180 mg/dL (time in range; [TIR]).

RESULTS

Twenty-five adults (52% male) were recruited; the median (interquartile range) age was 48 (37, 57) years, and the median HbA1c was 7.0% (6.6, 7.2) (53 [49, 55] mmol/mol). Faster aspart demonstrated greater overall TIR compared with IAsp (82.3% [78.5, 83.7] vs. 79.6% [77.0, 83.4], respectively; mean difference 1.9% [0.5, 3.3]; P = 0.007). Four-hour postprandial glucose TIR was higher using faster aspart compared with IAsp for all meals combined (73.6% [69.4, 80.2] vs. 72.1% [64.5, 78.5], respectively; median difference 3.5% [1.0, 7.3]; P = 0.003). There was no ketoacidosis or severe hypoglycemia.

CONCLUSIONS

Faster aspart safely improved glucose control compared with IAsp in a group of adults with well-controlled type 1 diabetes using AHCL. The modest improvement was mainly related to mealtime glycemia. While the primary outcome demonstrated statistical significance, the clinical impact may be small, given an overall difference in TIR of 1.9%.

A Physiologically-Based Pharmacokinetic Model for the Prediction of "Half-Life Extension" and "Catch and Release" Monoclonal Antibody Pharmacokinetics

Monoclonal antibodies (mAbs) can be engineered to have “extended half‐life” and “catch and release” properties to improve target coverage. We have developed a mAb physiologically‐based pharmacokinetic model that describes intracellular trafficking, neonatal Fc receptor (FcRn) recycling, and nonspecific clearance of mAbs. We extended this model to capture target binding as a function of target affinity, expression, and turnover. For mAbs engineered to have an extended half‐life, the model was able to accurately predict the terminal half‐life (82% within 2‐fold error of the observed value) in the human FcRn transgenic (Tg32) homozygous mouse and human. The model also accurately captures the trend in pharmacokinetic and target coverage data for a set of mAbs with differing catch and release properties in the Tg32 mouse. The mechanistic nature of this model allows us to explore different engineering techniques early in drug discovery, potentially expanding the number of “druggable” targets.

Impact of Disease on Plasma and Lung Exposure of Chloroquine, Hydroxychloroquine and Azithromycin: Application of PBPK Modeling

We use a mechanistic lung model to demonstrate that accumulation of chloroquine (CQ), hydroxychloroquine (HCQ), and azithromycin (AZ) in the lungs is sensitive to changes in lung pH, a parameter that can be affected in patients with coronavirus disease 2019 (COVID-19). A reduction in pH from 6.7 to 6 in the lungs, as observed in respiratory disease, led to 20-fold, 4.0-fold, and 2.7-fold increases in lung exposure of CQ, HCQ, and AZ, respectively. Simulations indicated that the relatively high concentrations of CQ and HCQ in lung tissue were sustained long after administration of the drugs had stopped. Patients with COVID-19 often present with kidney failure. Our simulations indicate that renal impairment (plus lung pH reduction) caused 30-fold, 8.0-fold, and 3.4-fold increases in lung exposures for CQ, HCQ, and AZ, respectively, with relatively small accompanying increases (20 to 30%) in systemic exposure. Although a number of different dosage regimens were assessed, the purpose of our study was not to provide recommendations for a dosing strategy, but to demonstrate the utility of a physiologically-based pharmacokinetic modeling approach to estimate lung concentrations. This, used in conjunction with robust in vitro and clinical data, can help in the assessment of COVID-19 therapeutics going forward.

Glucose and Counterregulatory Responses to Exercise in Adults With Type 1 Diabetes and Impaired Awareness of Hypoglycemia Using Closed-Loop Insulin Delivery: A Randomized Crossover Study

OBJECTIVE

To evaluate exercise-related glucose and counterregulatory responses (CRR) in adults with type 1 diabetes with impaired awareness of hypoglycemia (IAH) using hybrid closed-loop (HCL) insulin delivery to maintain glucose homeostasis.

RESEARCH DESIGN AND METHODS

Twelve participants undertook 45-min high-intensity intermittent exercise (HIIE) and moderate-intensity exercise (MIE) in random order. The primary outcome was continuous glucose monitoring (CGM) time in range (70-180 mg/dL) for 24-h post-exercise commencement.

RESULTS

CGM time in range was similar for HIIE and MIE (median 79.5% [interquartile range 73.2, 87.6] vs. 76.1% [70.3, 83.9], P = 0.37), and time with levels <54mg/dL post-exercise commencement was 0%. HIIE induced greater increases in cortisol (P = 0.002), noradrenaline (P = 0.005), and lactate (P = 0.002), with no differences in adrenaline, dopamine, growth hormone, or glucagon responses.

CONCLUSIONS

IAH adults using HCL undertaking HIIE and MIE exhibit heterogeneity in CRR. Novel findings were a preserved cortisol response and variable catecholamine responses to HIIE.

A Physiologically-Based Pharmacokinetic Model for the Prediction of Monoclonal Antibody Pharmacokinetics From In Vitro Data

Monoclonal antibody (mAb) pharmacokinetics (PK) have largely been predicted via allometric scaling with little consideration for cross-species differences in neonatal Fc receptor (FcRn) affinity or clearance/distribution mechanisms. To address this, we developed a mAb physiologically-based PK model that describes the intracellular trafficking and FcRn recycling of mAbs in a human FcRn transgenic homozygous mouse and human. This model uses mAb-specific in vitro data together with species-specific FcRn tissue expression, tissue volume, and blood-flow physiology to predict mAb in vivo linear PK a priori. The model accurately predicts the terminal half-life of 90% of the mAbs investigated within a twofold error. The mechanistic nature of this model allows us to not only predict linear PK from in vitro data but also explore the PK and target binding of mAbs engineered to have pH-dependent binding to its target or FcRn and could aid in the selection of mAbs with optimal PK and pharmacodynamic properties.

Neural correlates of early deliberate emotion regulation: Young children's responses to interpersonal scaffolding

Deliberate emotion regulation, the ability to willfully modulate emotional experiences, is shaped through interpersonal scaffolding and forecasts later functioning in multiple domains. However, nascent deliberate emotion regulation in early childhood is poorly understood due to a paucity of studies that simulate interpersonal scaffolding of this skill and measure its occurrence in multiple modalities. Our goal was to identify neural and behavioral components of early deliberate emotion regulation to identify patterns of competent and deficient responses. A novel probe was developed to assess deliberate emotion regulation in young children. Sixty children (age 4-6 years) were randomly assigned to deliberate emotion regulation or control conditions. Children completed a frustration task while lateral prefrontal cortex (LPFC) activation was recorded via functional near-infrared spectroscopy (fNIRS). Facial expressions were video recorded and children self-rated their emotions. Parents rated their child's temperamental emotion regulation. Deliberate emotion regulation interpersonal scaffolding predicted a significant increase in frustration-related LPFC activation not seen in controls. Better temperamental emotion regulation predicted larger LPFC activation increases post- scaffolding among children who engaged in deliberate emotion regulation interpersonal scaffolding. A capacity to increase LPFC activation in response to interpersonal scaffolding may be a crucial neural correlate of early deliberate emotion regulation.

Glucose Control in Adults with Type 1 Diabetes Using a Medtronic Prototype Enhanced-Hybrid Closed-Loop System: A Feasibility Study

Background: Experience from first-generation closed-loop (CL) systems informs refinements to enhance glucose control and user acceptance. A next-generation prototype enhanced-hybrid CL (E-HCL) system incorporates iterative changes to the Medtronic MiniMed 670G CL system, including automated correction boluses, lower target glucose level, and user enhancements. The aim was to explore safety, system performance, and glucose control using E-HCL in adults with type 1 diabetes. Methods: Twelve adults underwent this first in-human feasibility study. After a 1-week run-in using open-loop (OL), E-HCL was activated at the start of a supervised 1-week hotel phase, followed by 3 weeks free living at home. Supervised challenges included two meal interventions (unannounced and late meal bolus) and a sensor calibration intervention. Primary outcome was sensor glucose time-in-range (TIR); OL run-in and E-HCL at home were compared by Wilcoxon signed-rank test. Results: Twelve adults (seven men; median [interquartile range] age 48 [39, 57] years; HbA_1c 6.8 [6.2, 7.2]%, 51 [44, 55] mmol/mol; diabetes duration 31 [13, 41] years) completed the protocol. E-HCL resulted in greater TIR (85.3 [79.4, 88.4]% vs. 75.0 [66.6, 83.7]%, P = 0.003) and lower mean sensor glucose (123.0 [119.3, 129.6] mg/dL vs. 143.5 [135.8, 154.5] mg/dL, P = 0.002) than OL. Time spent <70 mg/dL increased using E-HCL (4.4 [3.3, 6.1]% vs. 3.0 [1.8, 3.8]%, P = 0.02) with no difference in time <54 mg/dL (P = 0.64). Time in CL was 99.98 [99.0, 100.0]%. All participants were satisfied using E-HCL. Conclusions: In adults with well-controlled HbA_1c levels, a prototype E-HCL resulted in high TIR, few CL exits, and positive user experiences at the expense of increased hypoglycemia (<70 mg/dL). E-HCL represents a positive step in the journey toward optimizing glucose control in people living with type 1 diabetes.

Viewpoints of adolescents with overweight and obesity attending lifestyle obesity treatment interventions: a qualitative systematic review

BACKGROUND

Current UK guidance recommends that adolescents with obesity attend a family-based multi-component obesity intervention. However, these programmes suffer from low recruitment and high rates of attrition. Understanding the views of adolescents is necessary for developing future interventions. The aim of this systematic review was to synthesize and explore the views of adolescents who have attended an obesity intervention.

METHODS

Published literature was identified by searching six databases. Studies of adolescents (12-17 years) who attended an obesity intervention were examined. Only studies that collected and analysed data qualitatively were included. Full texts were analysed using thematic synthesis.

RESULTS

Twenty-eight studies were included. Thirty-five analytical themes were developed that were broadly divided into seven domains. Key themes included ensuring adolescents receive a 'tailored intervention' that involves 'active engagement'. Support from professionals, family and peers were valued highly. Adolescents expressed 'prior fears of attending interventions' and wanted 'longer term support'. 'Enjoyment of sport and physical activity' was evident, and adolescents were strongly motivated by improving body image and social desirability.

DISCUSSION

Considering the views of adolescents attending obesity interventions may help to inform policy makers in the development of future interventions. This may lead to an improvement in recruitment and attrition rates.

Glucose Control Using a Standard Versus an Enhanced Hybrid Closed Loop System: A Randomized Crossover Study

Hybrid closed loop (HCL) insulin delivery with the Medtronic Minimed 670G system is effective and safe in people with type 1 diabetes (T1D). This study compared glucose control, closed loop (CL) exits, and alarm frequency with the standard HCL (s-HCL) versus enhanced HCL (e-HCL) Medtronic system. Pump-experienced T1D adults (n = 11; 9 female; mean [SD] age: 51 years [15 years]; HbA1c 7.5% [1.0%] or 58 mmol/mol [7.7 mmol/mol]) were assigned, in random order, s-HCL or e-HCL for 1 week each in a supervised live-in setting. e-HCL incorporated enhanced bolus reminders and iterative changes, broadening glucose and insulin delivery parameters permitting persistence in CL. For both s-HCL and e-HCL, insulin delivery was by a Medtronic pump with identical interventions (missed bolus, exercise, high-glycemic index, and high-fat meals), insulin action times, and insulin-carbohydrate ratios implemented. The primary outcome was continuous glucose monitoring time in target range. Analysis was by paired t-test for normally distributed data and Wilcoxon-signed rank test otherwise. e-HCL resulted in significantly fewer CL alerts and exits. Time in target and mean glucose favored e-HCL but did not reach statistical significance. No episodes of severe hypoglycemia or ketoacidosis occurred. Relative to s-HCL, e-HCL use significantly decreases CL exits and alerts, and tended to improve glycemia without compromising safety, despite multiple food and exercise challenges during the study. Longer term studies at home are merited.

Using facial muscular movements to understand young children's emotion regulation and concurrent neural activation

Individual differences in young children's frustration responses set the stage for myriad developmental outcomes and represent an area of intense empirical interest. Emotion regulation is hypothesized to comprise the interplay of complex behaviors, such as facial expressions, and activation of concurrent underlying neural systems. At present, however, the literature has mostly examined children's observed emotion regulation behaviors and assumed underlying brain activation through separate investigations, resulting in theoretical gaps in our understanding of how children regulate emotion in vivo. Our goal was to elucidate links between young children's emotion regulation-related neural activation, facial muscular movements, and parent-rated temperamental emotion regulation. Sixty-five children (age 3-7) completed a frustration-inducing computer task while lateral prefrontal cortex (LPFC) activation and concurrent facial expressions were recorded. Negative facial expressions with eye constriction were inversely associated with both parent-rated temperamental emotion regulation and concurrent LPFC activation. Moreover, we found evidence that positive expressions with eye constriction during frustration may be associated with stronger LPFC activation. Results suggest a correspondence between facial expressions and LPFC activation that may explicate how children regulate emotion in real time.

Erratum: Atorvastatin exhibits anti-tumorigenic and anti-metastatic effects in ovarian cancer in vitro

[This corrects the article on p. 2478 in vol. 7, PMID: 29312801.].

Atorvastatin exhibits anti-tumorigenic and anti-metastatic effects in ovarian cancer in vitro

Ovarian cancer is the 8th most common cancer in women, and the 5th leading cause of cancer-related deaths among women in the United States. Statins have been shown to have promising anti-tumorigenic activity in many types of cancers. We sought to determine the effects of atorvastatin (ATO) on cell proliferation in ovarian cancer and identify the mechanisms by which ATO inhibits cell growth in this disease. ATO inhibited cell proliferation of both the Hey and SKOV3 ovarian cancer cells in a dose-dependent manner. The anti-proliferative activity of ATO in the ovarian cancer cell lines was associated with induction of apoptosis, autophagy, cellular stress and cell cycle G1 arrest via inhibition of AKT/mTOR and activation of the MAPK pathways. Moreover, ATO inhibited cell adhesion and invasion as well as decreased expression of VEGF and MMP9. c-Myc was downregulated in ovarian cancer cells exposed to ATO. Inhibition of c-Myc by JQ1 synergistically increased the sensitivity of ovarian cancer cells to ATO. This data suggests that ATO may have a therapeutic role in the treatment of ovarian cancer and warrant further exploration in clinical trials.

Phenformin has anti-tumorigenic effects in human ovarian cancer cells and in an orthotopic mouse model of serous ovarian cancer

Obesity and diabetes have been associated with increased risk and worse outcomes in ovarian cancer (OC). The biguanide metformin is used in the treatment of type 2 diabetes and is also believed to have anti-tumorigenic benefits. Metformin is highly hydrophilic and requires organic cation transporters (OCTs) for entry into human cells. Phenformin, another biguanide, was taken off the market due to an increased risk of lactic acidosis over metformin. However, phenformin is not reliant on transporters for cell entry; and thus, may have increased potency as both an anti-diabetic and anti-tumorigenic agent than metformin. Thus, our goal was to evaluate the effect of phenformin on established OC cell lines, primary cultures of human OC cells and in an orthotopic mouse model of high grade serous OC. In three OC cell lines, phenformin significantly inhibited cellular proliferation, induced cell cycle G1 arrest and apoptosis, caused cellular stress, inhibited adhesion and invasion, and activation of AMPK and inhibition of the mTOR pathway. Phenformin also exerted anti-proliferative effects in seven primary cell cultures of human OC. Lastly, phenformin inhibited tumor growth in an orthotopic mouse model of serous OC, coincident with decreased Ki-67 staining and phosphorylated-S6 expression and increased expression of caspase 3 and phosphorylated-AMPK. Our findings demonstrate that phenformin has anti-tumorigenic effects in OC as previously demonstrated by metformin but it is yet to be determined if it is superior to metformin for the potential treatment of this disease.

Dual inhibition of glycolysis and glutaminolysis as a therapeutic strategy in the treatment of ovarian cancer

Cancer cell metabolism is required to support the biosynthetic demands of cell growth and cell division, and to maintain reduction oxidaton (redox) homeostasis. This study was designed to test the effects of glucose and glutamine on ovarian cancer cell growth and explore the inter-relationship between glycolysis and glutaminolysis. The SKOV3, IGROV-1 and Hey ovarian cancer cell lines were assayed for glucose, pyruvate and glutamine dependence by analyzing cytotoxicity, cell cycle progression, apoptosis and ATP production. As determined by MTT assay, glucose stimulated cell growth while the combination of glucose, glutamine and pyruvate resulted in the greatest stimulation of cell proliferation. Furthermore, 2-deoxy-glucose (2-DG) and 3-bromopyruvate (3-BP) induced apoptosis, caused G1 phase cell cycle arrest and reduced glycolytic activity. Moreover, 2-DG in combination with a low dose of aminooxyacetate (AOA) synergistically increased the sensitivity to 2-DG in the inhibition of cell growth in the ovarian cancer cell lines. These studies suggest that dual inhibition of glycolysis and glutaminolysis may be a promising therapeutic strategy for the treatment of ovarian cancer.

Assessing the Impact of Tissue Target Concentration Data on Uncertainty in In Vivo Target Coverage Predictions

Understanding pharmacological target coverage is fundamental in drug discovery and development as it helps establish a sequence of research activities, from laboratory objectives to clinical doses. To this end, we evaluated the impact of tissue target concentration data on the level of confidence in tissue coverage predictions using a site of action (SoA) model for antibodies. By fitting the model to increasing amounts of synthetic tissue data and comparing the uncertainty in SoA coverage predictions, we confirmed that, in general, uncertainty decreases with longitudinal tissue data. Furthermore, a global sensitivity analysis showed that coverage is sensitive to experimentally identifiable parameters, such as baseline target concentration in plasma and target turnover half‐life and fixing them reduces uncertainty in coverage predictions. Overall, our computational analysis indicates that measurement of baseline tissue target concentration reduces the uncertainty in coverage predictions and identifies target‐related parameters that greatly impact the confidence in coverage predictions.

Glutaminase inhibitor compound 968 inhibits cell proliferation and sensitizes paclitaxel in ovarian cancer

Our overall goal was to investigate the anti-tumor activity of the glutaminase 1 (GLS1) Inhibitor compound 968 in ovarian cancer cells. The human ovarian cancer cell lines, HEY, SKOV3 and IGROV-1 were used. Cell proliferation was assessed by MTT assay after treatment with compound 968. Cell cycle progression and Annexin V expression were evaluated using Cellometer. Western blotting was performed to determine changes in GLS1, cellular stress and cell cycle checkpoints. Reactive oxygen species (ROS) and glutamate dehydrogenase (GDH) activity were assessed by ELISA assay. Compound 968 significantly inhibited cell proliferation and the expression of GLS1 in a dose-dependent manner in all three ovarian cancer cell lines. Compound 968 induced G1 phase cell cycle arrest and apoptosis. Treatment with compound 968 increased ROS levels and induced the protein expression of calnexin, binding immunoglobulin protein (BiP) and protein kinase RNA-like endoplasmic reticulum kinase (PERK). Deprivation of glutamine increased the sensitivity of cells to paclitaxel, and compound 968 sensitized cells to the anti-proliferative effects of paclitaxel. Compound 968 inhibited cell growth in ovarian cancer cells through induction of G1 phase cell cycle arrest, apoptosis and cellular stress, suggesting that targeting GLS1 provide a novel therapeutic strategy for ovarian cancer.

Buformin exhibits anti-proliferative and anti-invasive effects in endometrial cancer cells

OBJECTIVE

Biguanides are anti-diabetic drugs that are thought to have anti-tumorigenic effects. Most pre-clinical studies have focused on metformin for cancer treatment and prevention; however, buformin may be potentially more potent than metformin. Given this, our goal was to evaluate the effects of buformin on cell growth, adhesion and invasion in endometrial cancer cell lines.

METHODS

The ECC-1 and Ishikawa endometrial cancer cell lines were used. Cell proliferation was assessed by MTT assay. Apoptosis and cell cycle analysis was performed by FITC Annexin V assay and propidium iodide staining, respectively. Adhesion was analyzed using the laminin adhesion assay. Invasion was assessed using the transwell invasion assay. The effects of buformin on the AMPK/mTOR pathway were determined by Western immunoblotting.

RESULTS

Buformin and metformin inhibited cell proliferation in a dose-dependent manner in both endometrial cancer cell lines. IC50s were 1.4-1.6 mM for metformin and 8-150 μM for buformin. Buformin induced cell cycle G1 phase arrest in the ECC-1 cells and G2 phase arrest in the Ishikawa cells. For both ECC-1 and Ishikawa cells, treatment with buformin resulted in induction of apoptosis, reduction in adhesion and invasion, activation of AMPK and inhibition of phosphorylated-S6. Buformin potentiated the anti-proliferative effects of paclitaxel in both cell lines.

CONCLUSION

Buformin has significant anti-proliferative and anti-metastatic effects in endometrial cancer cells through modulation of the AMPK/mTOR pathway. IC50 values were lower for buformin than metformin, suggesting that buformin may be more potent for endometrial cancer treatment and worthy of further investigation.

Utility of a human FcRn transgenic mouse model in drug discovery for early assessment and prediction of human pharmacokinetics of monoclonal antibodies

Therapeutic antibodies continue to develop as an emerging drug class, with a need for preclinical tools to better predict in vivo characteristics. Transgenic mice expressing human neonatal Fc receptor (hFcRn) have potential as a preclinical pharmacokinetic (PK) model to project human PK of monoclonal antibodies (mAbs). Using a panel of 27 mAbs with a broad PK range, we sought to characterize and establish utility of this preclinical animal model and provide guidance for its application in drug development of mAbs. This set of mAbs was administered to both hemizygous and homozygous hFcRn transgenic mice (Tg32) at a single intravenous dose, and PK parameters were derived. Higher hFcRn protein tissue expression was confirmed by liquid chromatography-high resolution tandem mass spectrometry in Tg32 homozygous versus hemizygous mice. Clearance (CL) was calculated using non-compartmental analysis and correlations were assessed to historical data in wild-type mouse, non-human primate (NHP), and human. Results show that mAb CL in hFcRn Tg32 homozygous mouse correlate with human (r(2) = 0.83, r = 0.91, p < 0.01) better than NHP (r(2) = 0.67, r = 0.82, p < 0.01) for this dataset. Applying simple allometric scaling using an empirically derived best-fit exponent of 0.93 enabled the prediction of human CL from the Tg32 homozygous mouse within 2-fold error for 100% of mAbs tested. Implementing the Tg32 homozygous mouse model in discovery and preclinical drug development to predict human CL may result in an overall decreased usage of monkeys for PK studies, enhancement of the early selection of lead molecules, and ultimately a decrease in the time for a drug candidate to reach the clinic.

A mechanistic PK/PD model for two anti-IL13 antibodies explains the difference in total IL-13 accumulation observed in clinical studies

IMA-638 and IMA-026 are humanized IgG1 monoclonal antibodies (mAbs) that target non-overlapping epitopes of IL-13. Separate first-in-human single ascending dose studies were conducted for each mAb. These studies had similar study designs, but mild to moderate asthmatics were recruited for the IMA-638 study and healthy subjects were recruited for the IMA-026 study. IMA-638 and IMA-026 showed similar pharmacokinetic (PK) profiles, but very different total IL-13 (free and drug bound IL-13) profiles; free IL13 was not measured. IMA-026 treatment induced a dose-dependent accumulation of total IL-13, while IMA-638 treatment led to a much smaller accumulation without any clear dose-response. To understand the differences between the two total IL-13 profiles and to predict the free IL-13 profiles for each mAb treatment, a mechanistic PK/pharmacodynamic model was developed. PK-related parameters were first fit to the mean PK profiles of each mAb separately; thereafter, the target-related parameters were fit to both total IL-13 profiles simultaneously. The IL-13 degradation rate was assumed to be the same for asthma patients and healthy subjects. The model suggests that an approximately 100× faster elimination of IL-13-IMA-638 complex than IL-13-IMA-026 complex could be responsible for the differences observed in total IL-13 profiles for the two mAbs. Furthermore, the model predicts that IMA-638 administration results in greater and more prolonged free IL-13 inhibition than equivalent dosing of IMA-026 despite similar binding KD and PK profile. In conclusion, joint modeling of two similar molecules provided mechanistic insight that the elimination rate of mAb-target complex can regulate the degree of free target inhibition.

Glutamine promotes ovarian cancer cell proliferation through the mTOR/S6 pathway

Glutamine is one of the main nutrients used by tumor cells for biosynthesis. Therefore, targeted inhibition of glutamine metabolism may have anti-tumorigenic implications. In the present study, we aimed to evaluate the effects of glutamine on ovarian cancer cell growth. Three ovarian cancer cell lines, HEY, SKOV3, and IGROV-1, were assayed for glutamine dependence by analyzing cytotoxicity, cell cycle progression, apoptosis, cell stress, and glucose/glutamine metabolism. Our results revealed that administration of glutamine increased cell proliferation in all three ovarian cancer cell lines in a dose dependent manner. Depletion of glutamine induced reactive oxygen species and expression of endoplasmic reticulum stress proteins. In addition, glutamine increased the activity of glutaminase (GLS) and glutamate dehydrogenase (GDH) by modulating the mTOR/S6 and MAPK pathways. Inhibition of mTOR activity by rapamycin or blocking S6 expression by siRNA inhibited GDH and GLS activity, leading to a decrease in glutamine-induced cell proliferation. These studies suggest that targeting glutamine metabolism may be a promising therapeutic strategy in the treatment of ovarian cancer.

Evaluation of the antitumor effects of c-Myc-Max heterodimerization inhibitor 100258-F4 in ovarian cancer cells

Epithelial ovarian carcinoma is the most lethal gynecological cancer due to its silent onset and recurrence with resistance to chemotherapy. Overexpression of oncogene c-Myc is one of the most frequently encountered events present in ovarian carcinoma. Disrupting the function of c-Myc and its downstream target genes is a promising strategy for cancer therapy. Our objective was to evaluate the potential effects of small-molecule c-Myc inhibitor, 10058-F4, on ovarian carcinoma cells and the underlying mechanisms by which 10058-F4 exerts its actions. Using MTT assay, colony formation, flow cytometry and Annexin V FITC assays, we found that 10058-F4 significantly inhibited cell proliferation of both SKOV3 and Hey ovarian cancer cells in a dose dependent manner through induction of apoptosis and cell cycle G1 arrest. Treatment with 10058-F4 reduced cellular ATP production and ROS levels in SKOV3 and Hey cells. Consistently, primary cultures of ovarian cancer treated with 10058-F4 showed induction of caspase-3 activity and inhibition of cell proliferation in 15 of 18 cases. The response to 10058-F4 was independent the level of c-Myc protein over-expression in primary cultures of ovarian carcinoma. These novel findings suggest that the growth of ovarian cancer cells is dependent upon c-MYC activity and that targeting c-Myc-Max heterodimerization could be a potential therapeutic strategy for ovarian cancer.

Systems pharmacology of the nerve growth factor pathway: use of a systems biology model for the identification of key drug targets using sensitivity analysis and the integration of physiology and pharmacology

The nerve growth factor (NGF) pathway is of great interest as a potential source of drug targets, for example in the management of certain types of pain. However, selecting targets from this pathway either by intuition or by non-contextual measures is likely to be challenging. An alternative approach is to construct a mathematical model of the system and via sensitivity analysis rank order the targets in the known pathway, with respect to an endpoint such as the diphosphorylated extracellular signal-regulated kinase concentration in the nucleus. Using the published literature, a model was created and, via sensitivity analysis, it was concluded that, after NGF itself, tropomyosin receptor kinase A (TrkA) was one of the most sensitive druggable targets. This initial model was subsequently used to develop a further model incorporating physiological and pharmacological parameters. This allowed the exploration of the characteristics required for a successful hypothetical TrkA inhibitor. Using these systems models, we were able to identify candidates for the optimal drug targets in the known pathway. These conclusions were consistent with clinical and human genetic data. We also found that incorporating appropriate physiological context was essential to drawing accurate conclusions about important parameters such as the drug dose required to give pathway inhibition. Furthermore, the importance of the concentration of key reactants such as TrkA kinase means that appropriate contextual data are required before clear conclusions can be drawn. Such models could be of great utility in selecting optimal targets and in the clinical evaluation of novel drugs.

Dose selection based on physiologically based pharmacokinetic (PBPK) approaches

Physiologically based pharmacokinetic (PBPK) models are built using differential equations to describe the physiology/anatomy of different biological systems. Readily available in vitro and in vivo preclinical data can be incorporated into these models to not only estimate pharmacokinetic (PK) parameters and plasma concentration-time profiles, but also to gain mechanistic insight into compound properties. They provide a mechanistic framework to understand and extrapolate PK and dose across in vitro and in vivo systems and across different species, populations and disease states. Using small molecule and large molecule examples from the literature and our own company, we have shown how PBPK techniques can be utilised for human PK and dose prediction. Such approaches have the potential to increase efficiency, reduce the need for animal studies, replace clinical trials and increase PK understanding. Given the mechanistic nature of these models, the future use of PBPK modelling in drug discovery and development is promising, however some limitations need to be addressed to realise its application and utility more broadly.

Use of modelling and simulation techniques to support decision making on the progression of PF-04878691, a TLR7 agonist being developed for hepatitis C

AIM

To use non-linear mixed effects modelling and simulation techniques to predict whether PF-04878691, a toll-like receptor 7 (TLR7) agonist, would produce sufficient antiviral efficacy while maintaining an acceptable side effect profile in a 'proof of concept' (POC) study in chronic hepatitis C (HCV) patients.

METHODS

A population pharmacokinetic-pharmacodynamic (PKPD) model was developed using available 'proof of pharmacology' (POP) clinical data to describe PF-04878691 pharmacokinetics (PK) and its relationship to 2',5'-oligoadenylate synthetase (OAS; marker of pharmacology) and lymphocyte levels (marker of safety) following multiple doses in healthy subjects. A second model was developed to describe the relationship between change from baseline OAS expressed as fold change and HCV viral RNA concentrations using clinical data available in HCV patients for a separate compound, CPG-10101 (ACTILON™), a TLR9 agonist. Using these models the antiviral efficacy and safety profiles of PF-04878691 were predicted in HCV patients.

RESULTS

The population PKPD models described well the clinical data as assessed by visual inspection of diagnostic plots, visual predictive checks and precision of the parameter estimates. Using these relationships, PF-04878691 exposure and HCV viral RNA concentration was simulated in HCV patients receiving twice weekly administration for 4 weeks over a range of doses. The simulations indicated that significant reductions in HCV viral RNA concentrations would be expected at doses > 6 mg. However at these doses grade ≥ 3 lymphopenia was also predicted.

CONCLUSIONS

The model simulations indicate that PF-04878691 is unlikely to achieve POC criteria and support the discontinuation of this compound for the treatment of HCV.