Association of genetic mutations and loss of ambulation in childhood-onset dystrophinopathy.

BACKGROUND: Quantifying associations between genetic mutations and loss of ambulation (LoA) among males diagnosed with childhood-onset dystrophinopathy is important for understanding variation in disease progression and may be useful in clinical trial design. METHODS: Genetic and clinical data from the Muscular Dystrophy Surveillance, Tracking, and Research Network for 358 males born and diagnosed from 1982 to 2011 were analyzed. LoA was defined as the age at which independent ambulation ceased. Genetic mutations were defined by overall type (deletion/duplication/point mutation) and among deletions, those amenable to exon-skipping therapy (exons 8, 20, 44-46, 51-53) and another group. Cox proportional hazards regression modeling was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Mutation type did not predict time to LoA. Controlling for corticosteroids, Exons 8 (HR = 0.22; 95% CI = 0.08, 0.63) and 44 (HR = 0.30; 95% CI = 0.12, 0.78) were associated with delayed LoA compared to other exon deletions. CONCLUSIONS: Delayed LoA in males with mutations amenable to exon-skipping therapy is consistent with previous studies. These findings suggest that clinical trials including exon 8 and 44 skippable males should consider mutation information prior to randomization.

Application of Model-Informed Drug Development in Dose Selection and Optimization for siRNA Therapies.

The application of model-informed drug development (MIDD) has revolutionized drug development and regulatory decision making, transforming the process into one that is more efficient, effective, and patient centered. A critical application of MIDD is to facilitate dose selection and optimization, which play a pivotal role in improving efficacy, safety, and tolerability profiles of a candidate drug. With the surge of interest in small interfering RNA (siRNA) drugs as a promising class of therapeutics, their applications in various disease areas have been extensively studied preclinically. However, dosing selection and optimization experience for siRNA in humans is limited. Unique challenges exist for the dose evaluation of siRNA due to the temporal discordance between pharmacokinetic and pharmacodynamic profiles, as well as limited available clinical experience and considerable interindividual variability. This review highlights the pivotal role of MIDD in facilitating dose selection and optimization for siRNA therapeutics. Based on past experiences with approved siRNA products, MIDD has demonstrated its ability to aid in dose selection for clinical trials and enabling optimal dosing for the general patient population. In addition, MIDD presents an opportunity for dose individualization based on patient characteristics, enhancing the precision and effectiveness of siRNA therapeutics. In conclusion, the integration of MIDD offers substantial advantages in navigating the complex challenges of dose selection and optimization in siRNA drug development, which in turn accelerates the development process, supports regulatory decision making, and ultimately improves the clinical outcomes of siRNA-based therapies, fostering advancements in precision medicine across a diverse range of diseases.

Driving Efficiency: Leveraging Model-Informed Approaches in 505(b)(2) Regulatory Actions.

Introduced by the Hatch-Waxman Amendments of 1984, 505(b)(2) applications permit the US Food and Drug Administration to rely, for approval of a new drug application, on information from studies not conducted by or for the applicant and for which the applicant has not obtained a right of reference. This pathway is designed to circumvent the unnecessary duplication of studies already conducted on a previously approved drug. It can lead to a considerably more efficient and expedited route to approval compared to a traditional development path. Model-informed drug development refers to the utilization of a diverse array of quantitative models in drug development to streamline the decision-making process. In this approach, diverse quantitative models that integrate knowledge of physiology, disease processes, and drug pharmacology are employed to address drug development challenges and guide regulatory decisions. Integration of these model-informed approaches into 505(b)(2) regulatory submissions and decision-making can further expedite the approval of new drugs. This article discusses some applications of model-informed approaches that were used to support 505(b)(2) drug development and regulatory actions. Specifically, various quantitative models such as population pharmacokinetic and exposure-response models have been employed to provide evidence of effectiveness, guide dosing in subgroups such as subjects with hepatic or renal impairment, and inform policies. These case study examples collectively underscore the significance of model-informed approaches in drug development and regulatory decisions associated with 505(b)(2) submissions.

Model-Informed Approach Supporting Drug Development and Regulatory Evaluation for Rare Diseases.

A rare disease is defined as a condition affecting fewer than 200 000 people in the United States by the Orphan Drug Act. For rare diseases, it is challenging to enroll a large number of patients and obtain all critical information to support drug approval through traditional clinical trial approaches. In addition, over half of the population affected by rare diseases are children, which presents additional drug development challenges. Thus, maximizing the use of all available data is in the interest of drug developers and regulators in rare diseases. This brings opportunities for model-informed drug development to use and integrate all available sources and knowledge to quantitatively assess the benefit/risk of a new product under development and to inform dosing. This review article provides an overview of 4 broad categories of use of model-informed drug development in drug development and regulatory decision making in rare diseases: optimizing dose regimen, supporting pediatric extrapolation, informing clinical trial design, and providing confirmatory evidence for effectiveness. The totality of evidence based on population pharmacokinetic simulation as well as exposure-response relationships for efficacy and safety, provides the regulatory ground for the approval of an unstudied dosing regimen in rare diseases without the need for additional clinical data. Given the practical and ethical challenges in drug development in rare diseases, model-informed approaches using all collective information (eg, disease, drug, placebo effect, exposure-response in nonclinical and clinical settings) are powerful and can be applied throughout the drug development stages to facilitate decision making.

Population pharmacokinetics of eniporide and its metabolite in healthy subjects and patients with acute myocardial infarction.

Eniporide (EMD 96 875) is a novel and selective inhibitor of the Na+-H+ exchange (NHE-1) inhibitor. The study objectives were to identify a structural model for population pharmacokinetic analysis of eniporide and its metabolite (EMD 112 843) using nonlinear mixed-effects modeling after short-term infusion (dose: 2.5-400 mg) in healthy subjects and patients undergoing myocardial reperfusion therapy. Pooled concentrations of eniporide and its metabolite from healthy subjects (n = 153; 4815 observations) and patients (n = 304; 1465 observations) were included in the pharmacokinetic analysis. Population estimates of clearance and volume of distribution of eniporide were 29.2 L/h (24.1% coefficient of variation [CV], healthy), 20.8 L/h (28.0% CV, patients) and 20.4 L (13.1% CV, healthy), 16.9 L (24.9% CV, patients), respectively. Statistical significance was achieved for the effect of age on clearance and creatinine clearance on volume of distribution of eniporide. The impact of the covariates on eniporide pharmacokinetics is minimal to warrant any dosage adjustments in patient population.

Population pharmacokinetics of cilengitide in adult and pediatric cancer patients from a nonlinear mixed-effects analysis.

Cilengitide is an αvß3/αvß5-integrin inhibitor investigated as an anticancer agent. This study aimed to develop a cilengitide population pharmacokinetic model using nonlinear mixed-effects modeling of 136 adult patients with advanced solid tumors and to scale the pharmacokinetic parameters to the pediatric population. A stepwise approach was used, beginning with exploratory analyses checking database/target covariate relationships. A two-compartment structural model was developed to describe cilengitide's concentration-time profile and assess covariates' impact on pharmacokinetic parameters. A bootstrap procedure validated the base/final model stability. A two-compartment model best described concentration-time data. Estimated structural model parameters were: 2.79 L h(-) (1) m(-) (2) central compartment mean systemic clearance, 6.75 L m(-) (2) central compartment volume of distribution, 1.3 L h(-) (1) m(-) (2) intercompartmental clearance, and 3.85 L m(-) (2) peripheral compartment volume of distribution. Mean half-life was 0.9 and 3.8 h (α/ß-phase). Co-medications and study populations had no impact, as the different studies were not significant model covariates. Weight and body surface area correlated with the pharmacokinetic parameters (r = 0.95, P < 0.01). Pharmacokinetic parameters were consistent with individual study-derived parameters; their allometric scaling enabled pediatric pharmacokinetic profile predictions as corroborated by independent data. This model provides the basis for pharmacokinetic profile simulations of different dosages/regimens in different populations.

Endpoints and analyses to discern disease-modifying drug effects in early Parkinson's disease.

Parkinson's disease is an age-related degenerative disorder of the central nervous system that often impairs the sufferer's motor skills and speech, as well as other functions. Symptoms can include tremor, stiffness, slowness of movement, and impaired balance. An estimated four million people worldwide suffer from the disease, which usually affects people over the age of 60. Presently, there is no precedent for approving any drug as having a modifying effect (i.e., slowing or delaying) for disease progression of Parkinson's disease. Clinical trial designs such as delayed start and withdrawal are being proposed to discern symptomatic and protective effects. The current work focused on understanding the features of delayed start design using prior knowledge from published and data submitted to US Food and Drug Administration (US FDA) as part of drug approval or protocol evaluation. Clinical trial simulations were conducted to evaluate the false-positive rate, power under a new statistical analysis methodology, and various scenarios leading to patient discontinuations from clinical trials. The outcome of this work is part of the ongoing discussion between the US FDA and the pharmaceutical industry on the standards required for demonstrating disease-modifying effect using delayed start design.

Application of two-point assay of digoxin serum concentration in studying population pharmacokinetics in Egyptian pediatric patients with heart failure: does it make sense?

Digoxin pharmacokinetics (PK) was studied among a selected group of Egyptian pediatric patients (n = 40) with an age range of 0.33 to 15 years. All the patients had heart failure and were maintained on i.v. digoxin (10 microg/kg/d in 2 equal doses). For population PK analysis, 2 serum samples of digoxin were taken per patient. From 30 patients' trough (before the next dose) and 4 hours postdose samples were obtained, while in the other 10 patients, 0.5- and 6-hour postdose samples were taken. Serum concentrations were measured by fluorescence polarization immunoassay. PK modeling was performed using NONMEM software on log-transformed serum digoxin data. The best structural covariate-free model was a linear 2-compartment model with an exponential error model for intersubject variability and an additive model for intrasubject variability. Serum creatinine (SCR) was a significant covariate for clearance. The final population PK parameters were CL (L/h) = 0.388 - [0.78 x (SCR-0.6)], V1 (L/kg) = 1.38, Q (L/h/kg) = 0.48, V2 (L/kg) = 9.11, where CL is the total body clearance, V1 and V2 are the apparent volumes of distribution in the central and peripheral compartments, and Q is intercompartment clearance. A bootstrap resampling for internal validation achieved excellent agreement with the original data sets for PK parameters. In conclusion, 2 points of digoxin concentration allow good regression analysis for clearance-covariate relationship. The inclusion of SCR into the final model might allow better selection of initial maintenance dose of the drug. A prospective study on larger sample size of pediatric patients is recommended for clinical validation of the final model.

Evaluation of pharmacokinetics, brain levels and protein binding of centpropazine in rats.

The pharmacokinetics of centpropazine (CNPZ), an antidepressant, was studied in rats. CNPZ was administered to groups of rats (n=3 to 5) via oral (40 mg/kg), intravenous (5 mg/kg), intraperitoneal (5 mg/kg) and intraduodenal (4 and 8 mg/kg) routes. The AUCs of CNPZ were estimated and the bioavailabilities were calculated. CNPZ was characterized by a short elimination half-life (39.5 min), a high clearance (118 ml/min/kg) and a relatively large volume of distribution (1945 ml/kg) after intravenous administration. After oral administration CNPZ exhibited a very low oral bioavailability ( approximately 0.2%). The total first pass effect (Egit+liver) was calculated as 98.7%. The bioavailability of CNPZ was similar when administered by intraduodenal and oral routes. CNPZ readily penetrated into the brain and reached Cmax by 30 min post oral dosing. About 92.0%+/-0.8% of the drug was bound to serum proteins. Low oral bioavailability of CNPZ following oral administration is likely due to its metabolism by intestinal mucosa and liver.

Pharmacokinetics and bioavailability of herbal medicinal products.

The use of herbs for treating various ailments dates back several centuries. Usually, herbal medicine has relied on tradition that may or may not be supported by empirical data. The belief that natural medicines are much safer than synthetic drugs has gained popularity in recent years and led to tremendous growth of phytopharmaceutical usage. Market driven information on natural products is widespread and has further fostered their use in daily life. In most countries there is no universal regulatory system that insures the safety and activity of phytopharmaceuticals. Evidence-based verification of the efficacy of HMPs (herbal medicinal products, botanicals) is still frequently lacking. However, in recent years, data on evaluation of the therapeutic and toxic activity of herbal medicinal products became available. The advances in analytical technology have led to discovery of many new active constituents and an ever-increasing list of putatively active constituents. Establishing the pharmacological basis for efficacy of HMPs is a constant challenge. Of particular interest is the question of bioavailability to assess to what degree and how fast compounds are absorbed after administration of HMPs. Of further interest is the elucidation of metabolic pathways (yielding potentially new active compounds), and the assessment of elimination routes and their kinetics. These data become an important issue to link data from pharmacological assays and clinical effects. Of interest are currently also interactions of herbal medicinal products with synthetically derived drug products. A better understanding of the pharmacokinetics and bioavailability of phytopharmaceuticals can also help in designing rational dosage regimens. In this review, pharmacokinetic and bioavailability studies that have been conducted for some of the more important or widely used phytopharmaceuticals are critically evaluated. Furthermore, various drug interactions are discussed which show that caution should be exercised when combining phytopharmaceuticals with chemically derived active pharmaceutical ingredients.