A genetic algorithm-based approach for the prediction of metabolic drug-drug interactions involving CYP2C8 or CYP2B6.

BACKGROUND AND OBJECTIVES: A genetic algorithm (GA) approach was developed to predict drug-drug interactions (DDIs) caused by cytochrome P450 2C8 (CYP2C8) inhibition or cytochrome P450 2B6 (CYP2B6) inhibition or induction. Nighty-eight DDIs, obtained from published in vivo studies in healthy volunteers, have been considered using the area under the plasma drug concentration-time curve (AUC) ratios (i.e., ratios of AUC of the drug substrate administered in combination with a DDI perpetrator to AUC of the drug substrate administered alone) to describe the extent of DDI. METHODS: The following parameters were estimated in this approach: the contribution ratios (CRCYP2B6 and CRCYP2C8, i.e., the fraction of the dose metabolized via CYP2B6 or CYP2C8, respectively) and the inhibitory or inducing potency of the perpetrator drug (IRCYP2B6, IRCYP2C8 and ICCYP2B6, for inhibition of CYP2B6 and CYP2C8, and induction of CYP2B6, respectively). The workflow consisted of three main phases. First, the initial estimates of the parameters were estimated through GA. Then, the model was validated using an external validation. Finally, the parameter values were refined via a Bayesian orthogonal regression using all data. RESULTS: The AUC ratios of 5 substrates, 11 inhibitors and 19 inducers of CYP2B6, and the AUC ratios of 19 substrates and 23 inhibitors of CYP2C8 were successfully predicted by the developed methodology within 50-200% of observed values. CONCLUSIONS: The approach proposed in this work may represent a useful tool for evaluating the suitable doses of a CYP2C8 or CYP2B6 substrates co-administered with perpetrators.

Pharmacokinetics of Intranasal Drugs, Still a Missed Opportunity?

The intranasal (IN) route of administration is important for topical drugs and drugs intended to act systemically. More recently, direct nose-to-brain input was considered to bypass the blood-brain barrier.Processes related to IN absorption and nose-to-brain distribution are complex and depend, sometimes in contrasting ways, on chemico-physical and structural parameters of the compounds, and on formulation options.Due to the intricacies of these processes and despite the large number of articles published on many different IN compounds, it appears that absorption after IN dosing is not yet fully understood. In particular, at variance of the understanding and modelling approaches that are available for predicting the pharmacokinetics (PK) following oral administration of xenobiotics, it appears that there is not a similar understanding of the chemico-physical and structural determinants influencing drug absorption and disposition of compounds after IN administration, which represents a missed opportunity for this research field. This is even more true regarding the understanding of the direct nose-to-brain input. Due to this, IN administrations may represent an interesting and open research field for scientists aiming to develop PK property predictions tools, mechanistic PK models describing rate and extent of IN absorption, and translational tools to anticipate the clinical PK following IN dosing based on in vitro and in vivo non clinical experiments.This review intends to provide: i) some basic knowledge related to the physiology of PK after IN dosing, ii) a non-exhaustive list of preclinical and clinical examples related to compounds explored for the potential nose-to-blood and nose-to-brain passage, and iii) the identification of some areas requiring improvements, the understanding of which may facilitate the development of IN drug candidates.

Pharmacokinetic-Pharmacodynamic Modeling of the Ponesimod Effect on Heart Rate in Patients With Multiple Sclerosis.

The purpose of this study was to characterize the ponesimod effect on the heart rate (HR) in patients with multiple sclerosis (MS). A previous pharmacokinetic (PK) and pharmacodynamic model developed in healthy participants was updated using data from phase II and III trials conducted in patients with MS. Clinically relevant covariates were assessed. Simulations were conducted to evaluate the impact of the lack of adherence to ponesimod treatment and provide guidance in cases of treatment re-initiation. The maximal effect parameter of the PK/HR model was lower in patients with MS (23.5% decrease) compared with healthy volunteers (43.2%). The effect of patient covariates on PK/HR was similar to those identified in healthy participants and not clinically relevant in patients with MS. The population PK/HR model well characterized the effect of ponesimod on the time course of HR in patients with MS. After 2 weeks of treatment with 10 mg or higher doses, the model indicated full tolerance development. After repeated dosing at 20 mg, tolerance was maintained > 60% of the steady-state tolerance for up to 4 days after the last dose. Re-initiating with gradual uptitration is recommended if drug discontinuation lasts ≥ 4 days. This managed the negative chronotropic effects of ponesimod. No bradycardia events were observed within the first 2 weeks of treatment in patients with relapsing MS with a baseline HR > 55 bpm. This justifies the recommendation included in the human prescription drug labeling to monitor HR after the first ponesimod dose in these patients.

General clinical and methodological considerations on the extrapolation of pharmacokinetics and optimization of study protocols for small molecules and monoclonal antibodies in children.

Pharmacometric modelling plays a key role in both the design and analysis of regulatory trials in paediatric drug development. Studies in adults provide a rich source of data to inform the paediatric investigation plans, including knowledge on drug pharmacokinetics (PK), safety and efficacy. In children, drug disposition differs widely from birth to adolescence but extrapolating adult to paediatric PK, safety and efficacy either with pharmacometric or physiologically based approaches can help design or in some cases reduce the need for clinical studies. Aspects to consider when extrapolating PK include the maturation of drug metabolizing enzyme expression, glomerular filtration, drug excretory systems, and the expression and activity of specific transporters in conjunction with other drug properties such as fraction unbound. Knowledge of these can be used to develop extrapolation tools such as allometric scaling plus maturation functions or physiologically based PK. PK/pharmacodynamic approaches and well-designed clinical trials in children are of key importance in paediatric drug development. In this white paper, state-of-the-art of current methods used for paediatric extrapolation will be discussed. This paper is part of a conect4children implementation of innovative methodologies including pharmacometric and physiologically based PK modelling in clinical trial design/paediatric drug development through dissemination of expertise and expert advice. The suggestions arising from this white paper should define a minimum set of standards in paediatric modelling and contribute to the regulatory science.

An exposure-response analysis of ponesimod clinical efficacy in a randomized phase III study in patients with relapsing multiple sclerosis.

The efficacy of ponesimod and teriflunomide for the treatment of relapsing multiple sclerosis (MS) was compared in a randomized phase III trial. This study explores the exposure-response (E-R) relationships of efficacy end points (annualized relapse rate [ARR] and combined unique active lesions [CUALs]) of ponesimod observed in this trial. The E-R relationships were described using nonlinear mixed effects models for count data. The effect of baseline covariates (demography and prognostic factors) was also explored. Ponesimod 20 mg reduced ARR (primary end point) by 30.5% (95% confidence interval [CI]: 9.8% to 46.4%) and the number of CUALs by 56% (95% CI: 46% to 64%) between baseline and week 108 compared to teriflunomide 14 mg. The E-R analyses indicated a significant relationship between ARR and CUAL. In turn, CUAL was significantly related to ponesimod systemic exposure. Based on these relationships, the predicted reduction of ARR was relatively flat in the range of ponesimod systemic exposure achieved with the 20 mg clinical dose: the expected ARR decrease ranged from 28% (95% CI: 11% to 42%) at the 5th percentile of ponesimod exposure to 34% (95% CI: 19% to 47%) at the 95th percentile. No significant baseline covariates affected the ponesimod effects and, consequently, dosage adjustments are not warranted by these analyses. Although significant relationships were found between ARR and CUAL and between ponesimod exposure and CUAL, these analyses were supportive of the use of a flat 20 mg maintenance dose for ponesimod in adult patients with MS.

Quantitative Prediction of Drug Interactions Caused by Cytochrome P450 2B6 Inhibition or Induction.

BACKGROUND: Numerous drugs have the potential to be affected by cytochrome P450 (CYP) 2B6-mediated drug-drug interactions (DDIs). OBJECTIVES: In this work, we extend a static approach to the prediction of the extent of pharmacokinetics DDIs between substrates and inhibitors or inducers of CYP2B6. METHODS: This approach is based on the calculation of two parameters (the contribution ratio [CR], representing the fraction of dose of the substrate metabolized via this pathway and the inhibitory or inducing potency of the perpetrator [IR or IC, respectively]) calculated from the area under the concentration-time curve (AUC) ratios obtained in in-vivo DDI studies. RESULTS: Forty-eight studies involving 5 substrates, 11 inhibitors and 18 inducers of CYP2B6 (overall 15 inhibition and 33 induction studies) were divided into test and validation sets and considered for estimation of the parameters. The proposed approach demonstrated a fair accuracy for predicting the extent of DDI related to CYP2B6 inhibition and induction, all predictions related to the validation test (N = 18) being 50-200% of the observed ratios. CONCLUSIONS: This methodology can be used for proposing initial dose adaptations to be adopted, for example in clinical use or for designing DDI studies involving this enzyme.

Erdafitinib's effect on serum phosphate justifies its pharmacodynamically guided dosing in patients with cancer.

A population pharmacokinetic (PK)-pharmacodynamic (PD) model was developed using data from 345 patients with cancer. The population PK-PD model evaluated the effect of erdafitinib total and free plasma concentrations on serum phosphate concentrations after once-daily oral continuous (0.5-12 mg) and intermittent (10-12 mg for 7 days on/7 days off) dosing, and investigated the potential covariates affecting erdafitinib-related changes in serum phosphate levels. Phosphate is used as a biomarker for erdafitinib's efficacy and safety: increases in serum phosphate were observed after dosing with erdafitinib, which were associated with fibroblast growth factor receptor target engagement via inhibition of renal fibroblast growth factor 23-mediated signaling. PK-PD model-based simulations were performed to assess the approved PD-guided dosing algorithm of erdafitinib (8 mg once-daily continuous dosing, with up-titration to 9 mg based on phosphate levels [<5.5 mg/dl] and tolerability at 14-21 days of treatment). The serum phosphate concentrations increased after the first dose and reached near maximal level after 14 days of continuous treatment. Serum phosphate increased with erdafitinib free drug concentrations: doubling the free concentration resulted in a 1.8-fold increase in drug-related phosphate changes. Dose adjustment after at least 14 days of dosing was supported by achievement of >95% maximal serum phosphate concentration. The peak-to-trough fluctuation within a dosing interval was limited for serum phosphate concentrations (5.68-5.65 mg/dl on Day 14), supporting phosphate monitoring at any time relative to dosing. Baseline phosphate was higher in women, otherwise, none of the investigated covariate-parameter relationships were considered clinically relevant. Simulations suggest that the starting dose of 8-mg with up-titration to 9-mg on Days 14-21 maximized the number of patients within the target serum phosphate concentrations (5.5-7 mg/dl) while limiting the number of treatment interruptions. The findings from the PK-PD model provided a detailed understanding of the erdafitinib concentration-related phosphate changes over time, which supports erdafitinib's dosing algorithm.

A Quantitative Approach to the Prediction of Drug-Drug Interactions Mediated by Cytochrome P450 2C8 Inhibition.

BACKGROUND: Ohno and Colleagues proposed an approach for predicting drug-drug interactions (DDIs) mediated by cytochrome P450 (CYP) 3A4 based on the use of the ratio of the inhibited to non-inhibited area under the plasma concentration time curve (AUC) of substrates to estimate the fraction of the dose metabolized via CYP3A4 (contribution ratio, CR) and the in vivo inhibitory potency of a perpetrator (inhibition ratio, IR). This study evaluated the performance of this approach on DDIs mediated by CYP2C8 inhibitors. RESEARCH DESIGN AND METHODS: Initial estimates of CR and IR of CYP2C8 substrates and inhibitors were calculated for 33 DDI in vivo studies. The approach was externally validated with 17 additional studies. Bayesian orthogonal regression was used to refine the estimates of the parameters. Assessment of prediction success was conducted by plotting observed versus predicted AUC ratios. RESULTS: Final estimates of CRs and IRs were obtained for 19 CYP2C8 substrates and 23 inhibitors, respectively. The method demonstrated good predictive capacity, with only two values outside of the prespecified limits. CONCLUSIONS: The approach may help to adapt dose regimens for CYP2C8 substrates when given in combination with CYP2C8 inhibitors and to map the potential DDIs of new molecular entities.

Prediction of the drug-drug interaction potential of the α1-acid glycoprotein bound, CYP3A4/CYP2C9 metabolized oncology drug, erdafitinib.

Erdafitinib is a potent oral pan-fibroblast growth factor receptor inhibitor being developed as oncology drug for patients with alterations in the fibroblast growth factor receptor pathway. Erdafitinib binds preferentially to α1-acid glycoprotein (AGP) and is primarily metabolized by cytochrome P450 (CYP) 2C9 and 3A4. This article describes a physiologically based pharmacokinetic (PBPK) model for erdafitinib to assess the drug-drug interaction (DDI) potential of CYP3A4 and CYP2C9 inhibitors and CYP3A4/CYP2C9 inducers on erdafitinib pharmacokinetics (PK) in patients with cancer exhibiting higher AGP levels and in populations with different CYP2C9 genotypes. Erdafitinib's DDI potential as a perpetrator for transporter inhibition and for time-dependent inhibition and/or induction of CYP3A was also evaluated. The PBPK model incorporated input parameters from various in vitro and clinical PK studies, and the model was verified using a clinical DDI study with itraconazole and fluconazole. Erdafitinib clearance in the PBPK model consisted of multiple pathways (CYP2C9/3A4, renal, intestinal; additional hepatic clearance), making the compound less susceptible to DDIs. In poor-metabolizing CYP2C9 populations carrying the CYP2C9*3/*3 genotype, simulations shown clinically relevant increase in erdafitinib plasma concentrations. Simulated luminal and enterocyte concentration showed potential risk of P-glycoprotein inhibition with erdafitinib in the first 5 h after dosing, and simulations showed this interaction can be avoided by staggering erdafitinib and digoxin dosing. Other than a simulated ~ 60% exposure reduction with strong CYP3A/2C inducers such as rifampicin, other DDI liabilities were minimal and considered not clinically relevant.

Modeling approaches for reducing safety-related attrition in drug discovery and development: a review on myelotoxicity, immunotoxicity, cardiovascular toxicity, and liver toxicity.

Introduction:Safety and tolerability is a critical area where improvements are needed to decrease the attrition rates during development of new drug candidates. Modeling approaches, when smartly implemented, can contribute to this aim.Areas covered:The focus of this review was on modeling approaches applied to four kinds of drug-induced toxicities: hematological, immunological, cardiovascular (CV) and liver toxicity. Papers, mainly published in the last 10 years, reporting models in three main methodological categories - computational models (e.g., quantitative structure-property relationships, machine learning approaches, neural networks, etc.), pharmacokinetic-pharmacodynamic (PK-PD) models, and quantitative system pharmacology (QSP) models - have been considered.Expert opinion:The picture observed in the four examined toxicity areas appears heterogeneous. Computational models are typically used in all areas as screening tools in the early stages of development for hematological, cardiovascular and liver toxicity, with accuracies in the range of 70-90%. A limited number of computational models, based on the analysis of drug protein sequence, was instead proposed for immunotoxicity. In the later stages of development, toxicities are quantitatively predicted with reasonably good accuracy using either semi-mechanistic PK-PD models (hematological and cardiovascular toxicity), or fully exploited QSP models (immuno-toxicity and liver toxicity).

A Population Pharmacokinetic Model of Macitentan and Its Active Metabolite Aprocitentan in Healthy Volunteers and Patients with Pulmonary Arterial Hypertension.

BACKGROUND: Macitentan and its active metabolite, aprocitentan, are non-peptide, potent, dual endothelin receptor antagonists. Macitentan is approved for the treatment of pulmonary arterial hypertension in adults, at a dose of 10 mg/day. OBJECTIVE: The objective of this study was to develop a comprehensive population model to describe the pharmacokinetics of macitentan and aprocitentan in healthy adults and adult subjects with pulmonary arterial hypertension. METHODS: Pharmacokinetic data of 452 subjects in nine studies, after single and repeated doses (dose range 0.2-600 mg), were pooled for a non-linear mixed-effects analysis and the assessment of covariates, i.e., body weight, age, sex, race, renal and hepatic impairment, health status (healthy volunteers vs patients with pulmonary arterial hypertension), and formulation (capsules vs tablets) on pharmacokinetic parameters. RESULTS: The final model was an open one-compartment disposition model, with linear elimination for macitentan and linear formation and elimination for aprocitentan. A semi-mechanistic absorption model described the dose dependency and multiple peaks observed for macitentan. For a female patient with pulmonary arterial hypertension after oral administration at 10 mg, macitentan reached a maximum concentration after 9 h and, following daily dosing, reached steady state after 3 days with a twofold accumulation factor. The apparent volume of distribution was 34 L and clearance was 1.39 L/h. Aprocitentan reached maximum concentration after 51 h and steady state after 9 days, with a 12.5-fold accumulation factor. Body weight, sex, race, renal impairment, health status, and formulation were statistically significant covariates on pharmacokinetic parameters. CONCLUSIONS: The comprehensive population pharmacokinetic model adequately described the pharmacokinetics of macitentan and aprocitentan across different dose concentrations, regimens, and formulations. Several covariates significantly influenced the pharmacokinetics of macitentan and aprocitentan, but none was considered clinically relevant.

Effect of Ponesimod Exposure on Total Lymphocyte Dynamics in Patients with Multiple Sclerosis.

OBJECTIVE: The aim of this study was to characterize the relationship between ponesimod plasma concentrations and the temporal evolution of lymphocyte counts in multiple sclerosis (MS) patients. METHODS: Population pharmacokinetic (PK) and PK/pharmacodynamic (PD) models were developed using data from phase I, II, and III trials, and the impact of clinically relevant covariates on PK and PD parameters was assessed. Simulations were conducted to evaluate the maximal lymphocyte count reduction after ponesimod treatment, and the time required for total lymphocyte counts to return to normal values after treatment interruption. RESULTS: In MS patients, ponesimod PK were characterized by a low mean apparent plasma clearance (5.52 L/h) and a moderate mean apparent volume of distribution at steady state (239 L). The model developed indicated that none of the evaluated covariates (age, sex, formulation, food, body weight, clinical condition, and renal impairment) had a clinically relevant impact on the PK/PD parameters. In MS patients, total lymphocyte counts were characterized by a maximum reduction of 88.0% and a half maximal inhibitory concentration (IC50) of 54.9 ng/mL. Simulations indicated that in patients with normal hepatic function treated with ponesimod 20 mg daily, total lymphocyte counts were reduced to 41% of baseline at trough. After stopping treatment, lymphocyte counts were restored to normal levels within one week. CONCLUSIONS: The population PK/PD model well-characterized the PK of ponesimod and the time course of total lymphocyte counts in MS patients. Additionally, none of the evaluated covariates had a clinically relevant impact. This should be taken into consideration when assessing the risk of infection, administration of live-attenuated vaccines, and concomitant use of immunosuppressants.

An Exposure-Response Analysis of the Clinical Efficacy of Ponesimod in a Randomized Phase II Study in Patients with Multiple Sclerosis.

BACKGROUND AND OBJECTIVE: Ponesimod is a sphingosphine-1-phosphate receptor modulator being developed for the treatment of multiple sclerosis. The effects of disease-modifying treatments on magnetic resonance imaging (MRI) lesions in relapsing multiple sclerosis accurately predict effects on clinical relapses, therefore MRI lesion counts are generally accepted efficacy endpoints in phase II clinical studies of multiple sclerosis disease-modifying treatments. Here, we characterize the effect of ponesimod systemic exposure on the cumulative number of T1 gadolinium-enhancing (Gd+) lesions and the annualized relapse rate in a phase IIb study. METHODS: This study assessed the cumulative number of new Gd+ lesions on T1-weighted MRI scans (primary endpoint) at weeks 12, 16, 20, and 24 and the annualized relapse rate (secondary endpoint). The effect of the demographic and prognostic covariates of sex, age, weight, T1 Gd+ lesions at baseline, and Expanded Disability Status Scale score at baseline were explored. Analyses were performed using NONMEM, Version 7.3.0 (ICON plc). RESULTS: An increase in ponesimod exposure led to a statistically significant decrease in the cumulative T1 Gd+ lesions on MRI from week 12 to 24 of treatment. Increasing the ponesimod daily dose beyond 20 mg did not provide significant additional  benefits. Sex, age, T1 Gd+ lesions at baseline, and Expanded Disability Status Scale score at baseline were associated with a higher number of new cumulative T1 Gd+ from week 12 to 24 of treatment. CONCLUSIONS: This analysis shows a relationship between ponesimod exposure and the cumulative number of new T1 Gd+ lesions. Sex, age, T1 Gd+ lesions at baseline, and Expanded Disability Status Score at baseline were not found to be importantly associated with the magnitude of ponesimod effect, and consequently, there is no indication from these analyses that dosage adjustments based on the explored covariates are warranted. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01006265, registration date 1 November, 2009.

Clopidogrel, a CYP2C8 inhibitor, causes a clinically relevant increase in the systemic exposure to the active metabolite of selexipag in healthy subjects.

AIMS: Selexipag is a prostacyclin receptor agonist approved for the treatment of pulmonary arterial hypertension. Cytochrome P450 (CYP) 2C8 is involved in the metabolism of selexipag and its active metabolite, ACT-333679. This study evaluated the interaction of selexipag and clopidogrel, a CYP2C8 inhibitor. METHODS: The study had a 2-treatment, 1-sequence, crossover design. Pharmacokinetics (PK) and CYP2C8 genotype were assessed in healthy male subjects administered selexipag (200 µg twice daily [b.i.d.]) alone or with clopidogrel (300 mg single dose or 75 mg once daily [o.d.]). PK modelling and simulation were conducted to support dosing recommendations. RESULTS: Clopidogrel had a comparatively small effect on selexipag (<1.5-fold difference in any PK variable). For ACT-333679, the major contributor to the drug effect, the area under the plasma concentration-time curve during a dose interval and the maximum plasma concentration increased 2.25-fold (90% confidence interval [CI] 2.06, 2.46) and 1.69-fold (90% CI 1.55, 1.84), respectively with clopidogrel 300 mg and 2.70-fold (90% CI 2.45, 2.96) and 1.90-fold (90% CI 1.72, 2.11), respectively with clopidogrel 75 mg. The effect of clopidogrel on selexipag and ACT-333679 exposure was comparable for all identified CYP2C8 genotypes. PK simulations predicted comparable exposure to ACT-333679 following selexipag 400 µg b.i.d., 400 µg o.d. in combination with clopidogrel 75 mg o.d and 200 µg b.i.d. with clopidogrel 75 mg o.d. CONCLUSION: Results suggest that ACT-333679 exposure can be maintained within the therapeutic range by reducing selexipag dosing frequency to o.d. or dose to half, when selexipag is coadministered with clopidogrel.

Metabolism and disposition in rats, dogs, and humans of erdafitinib, an orally administered potent pan-fibroblast growth factor receptor (FGFR) tyrosine kinase inhibitor.

This article describes in vivo biotransformation and disposition of erdafitinib following single oral dose of 3H-erdafitinib and 14C-erdafitinib to intact and bile duct-cannulated (BC) rats (4 mg/kg), 3H-erdafitinib to intact dogs (0.25 mg/kg), and 14C-erdafitinib to humans (12 mg; NCT02692677). Peak plasma concentrations of total radioactivity were achieved rapidly (Tmax: animals, 1 h; humans, 2-3 h). Recovery of drug-derived radioactivity was significantly slower in humans (87%, 384 h) versus animals (rats: 91-98%, 48 h; dogs: 81%, 72 h). Faeces was the primary route of elimination in intact rats (95%), dogs (76%), and humans (69%); and bile in BC rats (48%). Renal elimination of radioactivity was relatively low in animals (2-12%) versus humans (19%). Unchanged erdafitinib was major component in human excreta (faeces, 17%; urine, 11%) relative to animals. M6 (O-desmethyl) was the major faecal metabolite in humans (24%) and rats (intact, 46%; BC, 11%), and M2 (O-glucuronide of M6) was the prevalent biliary metabolite in rats (14%). In dogs, besides M6, majority of radioactive dose in faeces was composed of multiple minor metabolites. In humans, unchanged erdafitinib was the major circulating entity. O-demethylation of erdafitinib was the major metabolic pathway in humans and animals.

Physiologically-Based Pharmacokinetic Modeling in Renal and Hepatic Impairment Populations: A Pharmaceutical Industry Perspective.

The predictive performance of physiologically-based pharmacokinetics (PBPK) models for pharmacokinetics (PK) in renal impairment (RI) and hepatic impairment (HI) populations was evaluated using clinical data from 29 compounds with 106 organ impairment study arms were collected from 19 member companies of the International Consortium for Innovation and Quality in Pharmaceutical Development. Fifty RI and 56 HI study arms with varying degrees of organ insufficiency along with control populations were evaluated. For RI, the area under the curve (AUC) ratios of RI to healthy control were predicted within twofold of the observed ratios for > 90% (N = 47/50 arms). For HI, > 70% (N = 43/56 arms) of the hepatically impaired to healthy control AUC ratios were predicted within twofold. Inaccuracies, typically overestimation of AUC ratios, occurred more in moderate and severe HI. PBPK predictions can help determine the need and timing of organ impairment study. It may be suitable for predicting the impact of RI on PK of drugs predominantly cleared by metabolism with varying contribution of renal clearance. PBPK modeling may be used to support mild impairment study waivers or clinical study design.

A Double-Blind, Placebo-Controlled Parallel Group Study to Evaluate the Effect of a Single Oral Dose of 5-HT1A Antagonist GSK958108 on Ejaculation Latency Time in Male Patients Suffering From Premature Ejaculation.

BACKGROUND: Premature ejaculation (PE) is a common male neurobiological sexual disorder, related to a disturbance in central serotonin (5-hydroxytryptamine or 5-HT) neurotransmission. AIM: To assess the efficacy of a single oral dose of 5HT1A receptor antagonist GSK958108 on ejaculation latency time (ELT) in male subjects suffering from PE. METHODS: A total of 35 male subjects were enrolled in a Phase 1 double-blind, placebo-controlled, parallel group masturbation-model study. All subjects completed the study. No subject was withdrawn from the study. There were no major protocol deviations reported during the study. OUTCOMES: The primary outcome of the study was to evaluate the effect of a single oral dose of 5HT1A receptor antagonist GSK958108 on ELT as measured in the masturbation model; additionally, we investigated drug's safety and tolerability. RESULTS: In the 3 mg GSK958108 treatment group, the ELT was estimated to be 16% longer (1.542 vs 1.328, 95% CI: -16% to +61%) than if the subjects had taken placebo. In the 7 mg GSK958108 treatment group, the ELT was estimated to be 77% longer (2.346 vs 1.328, 95% CI: +28% to +144%) than in the placebo group. The systemic exposure to GSK958108 increased with dosage between 3 mg and 7 mg. A significant trend toward an increase of ELT was observed with increasing plasma concentrations of GSK958108. A total of 4 patients all treated with 7 mg dose experienced minor drug related adverse events (5 adverse events in 4 patients): somnolence (n = 3), headache (n = 1), tinnitus (n = 1). CLINICAL IMPLICATIONS: In the current double-blind, placebo-controlled parallel group study the 5HT1A receptor antagonist GSK958108 was tested in 3 mg and 7 mg doses for PE treatment in humans. It was shown that GSK958108 significantly delayed ejaculation showing a new and safe alternative in PE treatment. STRENGTHS & LIMITATIONS: The present study showed innovative results suggesting an important role of 5HT1A receptor antagonist in the PE treatment. However, the use of masturbation model and the small population are the main limitations of this investigation. CONCLUSION: 5HT1A receptor antagonist GSK958108 3 mg per day and 7 mg per day was found to be well-tolerated, safe and effective for the treatment of PE subjects and demonstrated a strong association between 5HT1A receptors and ejaculation control in humans (NCT00861484). Migliorini F, Tafuri A, Bettica P, et al. A Double-Blind, Placebo-Controlled Parallel Group Study to Evaluate the Effect of a Single Oral Dose of 5-HT1A Antagonist GSK958108 on Ejaculation Latency Time in Male Patients Suffering From Premature Ejaculation. J Sex Med 2021;18:63-71.

Effect of Fluconazole and Itraconazole on the Pharmacokinetics of Erdafitinib in Healthy Adults: A Randomized, Open-Label, Drug-Drug Interaction Study.

BACKGROUND AND OBJECTIVES: Erdafitinib, an oral selective pan-fibroblast growth factor receptor (FGFR) kinase inhibitor, is primarily metabolized by cytochrome P450 (CYP) 2C9 and 3A4. The aim of this phase 1 study was to assess the pharmacokinetics and safety of erdafitinib in healthy participants when coadministered with fluconazole (moderate CYP2C9 and CYP3A inhibitor), and itraconazole (a strong CYP3A4 and P-glycoprotein inhibitor). The effect of CYP2C9 genotype variants (*1/*1, *1/*2, *1/*3) on the pharmacokinetics of erdafitinib was also investigated. METHODS: In this open-label, parallel-group, single-center study, eligible healthy adults were randomized by CYP2C9 genotype to receive Treatment A (single oral dose of erdafitinib 4 mg) on day 1, Treatment B (fluconazole 400 mg/day orally) on days 1-11, or Treatment C (itraconazole 200 mg/day orally) on days 1-11. Healthy adults randomized to Treatment B and C received a single oral 4-mg dose of erdafitinib on day 5. The pharmacokinetic parameters, including mean maximum plasma concentration (Cmax), area under the curve (AUC) from time 0 to 168 h (AUC168h), AUC from time 0 to the last quantifiable concentration (AUClast), and AUC from time 0 to infinity (AUC∞) were calculated from individual plasma concentration-time data using standard non-compartmental methods. RESULTS: Coadministration of erdafitinib with fluconazole increased Cmax of erdafitinib by approximately 21%, AUC168h by 38%, AUClast by 49%, and AUC∞ by 48% while coadministration with itraconazole resulted in no change in erdafitinib Cmax and increased AUC168h by 20%, AUClast by 33% and AUC∞ by 34%. Erdafitinib exposure was comparable between participants with CYP2C9 *1/*2 or *1/*3 and with wild-type CYP2C9 genotype. The ratio of total amount of erdafitinib excreted in the urine (inhibited to non-inhibited) was 1.09, the ratio of total amount of excreted metabolite M6 was 1.21, and the ratio of the metabolite to parent ratio in the urine was 1.11, when coadministration of erdafitinib with itraconazole was compared with single-dose erdafitinib. Treatment-emergent adverse events (TEAEs) were generally Grade 1 or 2 in severity; the most commonly reported TEAE was headache. No safety concerns were identified with single-dose erdafitinib when administered alone and in combination with fluconazole or itraconazole in healthy adults. CONCLUSION: Coadministration of fluconazole or itraconazole or other moderate/strong CYP2C9 or CYP3A4 inhibitors may increase exposure to erdafitinib in healthy adults and thus may warrant erdafitinib dose reduction or use of alternative concomitant medications with no or minimal CYP2C9 or CYP3A4 inhibition potential. TRIAL REGISTRATION: ClinicalTrials.gov identifier number: NCT03135106.

Population pharmacokinetics of trabectedin in adolescent patients with cancer.

PURPOSE: To characterize the trabectedin population pharmacokinetics in children and adolescent patients with cancer and compare it with the trabectedin pharmacokinetics in adults. METHODS: Plasma concentrations from ten adolescent and three children with cancer (age range 4.0-17.0 years) treated with trabectedin at doses ranging from 1.1 to 1.7 mg/m2, administered as a 24-h continuous intravenous infusion every 3 weeks, were available for the analysis. An external model evaluation was performed to verify whether a previously developed adult population pharmacokinetic model was predictive of the pediatric plasma concentrations of trabectedin. The maximum a posteriori estimation of the individual pharmacokinetic parameters for pediatric patients was conducted, after successful completion of the external evaluation step. The relationships between pharmacokinetic parameters and body size were evaluated. RESULTS: External evaluation methods showed no major differences between the adult population and children and adolescent patients of this study. The mean ± standard deviation (SD) of the individual estimated clearance and central volume of distribution in these children/adolescent patients was 36.4 ± 16.1 L/h and 13.2 ± 6.54 L, respectively. These values were similar to the typical values reported for adult patients-37.6 L/h and 13.9 L (for females) and 16.1 L (for males). The median area under the plasma concentration versus time curve (AUC) in children/adolescent patients was 55.1 µg h/L, while in the adult population the median AUC was 61.3 µg h/L, both administered a 1.5 mg/m2 dose regimen with mean (range) BSA for adults = 1.86 (0.90-2.80) vs children/adolescent patients = 1.49 (0.66-2.54). CONCLUSIONS: The adult population pharmacokinetic model adequately described the trabectedin plasma concentrations and its variability in the pediatric population of patients involved in this assessment that mostly comprised adolescents. The trabectedin systemic exposure achieved in this population was comparable (within 12%) to the exposure obtained in adult population when the same dose, expressed in mg/m2, was administered.

Multicenter Phase I Study of Erdafitinib (JNJ-42756493), Oral Pan-Fibroblast Growth Factor Receptor Inhibitor, in Patients with Advanced or Refractory Solid Tumors.

PURPOSE: Here, we report results of the first phase I study of erdafitinib, a potent, oral pan-FGFR inhibitor. PATIENTS AND METHODS: Patients age ≥18 years with advanced solid tumors for which standard antineoplastic therapy was no longer effective were enrolled (NCT01703481). Parts 2 to 4 employed molecular screening for activating FGFR genomic alterations. In patients with such alterations, two selected doses/schedules identified during part 1 dose-escalation [9 mg once daily and 10 mg intermittently (7 days on/7 days off), as previously published (Tabernero JCO 2015;33:3401-8)] were tested. RESULTS: The study included 187 patients. The most common treatment-related adverse events were hyperphosphatemia (64%), dry mouth (42%), and asthenia (28%), generally grade 1/2 severity. All cases of hyperphosphatemia were grade 1/2 except for 1 grade 3 event. Skin, nail, and eye changes were observed in 43%, 33%, and 28% of patients, respectively (mostly grade 1/2 and reversible after temporary dosing interruption). Urothelial carcinoma and cholangiocarcinoma were most responsive to erdafitinib, with objective response rates (ORR) of 46.2% (12/26) and 27.3% (3/11), respectively, in response-evaluable patients with FGFR mutations or fusions. All patients with urothelial carcinoma and cholangiocarcinoma who responded to erdafitinib carried FGFR mutations or fusions. Median response duration was 5.6 months for urothelial carcinoma and 11.4 months for cholangiocarcinoma. ORRs in other tumor types were <10%. CONCLUSIONS: Erdafitinib shows tolerability and preliminary clinical activity in advanced solid tumors with genomic changes in the FGFR pathway, at two different dosing schedules and with particularly encouraging responses in urothelial carcinoma and cholangiocarcinoma.