AAPS Journal最新文献

Wound healing is a complex process often impaired in severe injuries, requiring innovative therapeutic strategies. Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) modulate key cellular pathways, but their clinical application is limited by low stability and bioavailability. This study aimed to evaluate the safety and potential of sodium alginate hydrogels (SAH-EVs) loaded with mesenchymal stem cell-derived extracellular vesicles, focusing on cell migration, cytotoxicity, genotoxicity, and irritation potential. MSC-EVs from Sprague-Dawley rat bone marrow were isolated from conditioned medium collected at 24, 36, 48 and 60 h using size exclusion chromatography and characterized by Nanoparticle Tracking Analysis. The highest EV concentration was obtained from the conditioned medium collected at 36 h, with a main peak at 123 nm. The heterogeneous particle population suggests the presence of EV subtypes. Scanning Electron Microscopy confirmed successful MSC-EVs incorporation into hydrogels with desirable viscoelastic properties. SAH-EVs stimulated HaCaT keratinocyte migration while exhibiting low cytotoxicity in 2D and 3D models, with no genotoxic or mutagenic effects. HET-CAM assays confirmed the absence of irritation potential. These findings highlight the potential of SAH-EVs as a safe biomaterial and lay the groundwork for further investigations into their role in wound healing, reinforcing their relevance in regenerative medicine and tissue engineering.

Antibody-drug conjugates (ADCs) are composed of a tumor-targeting mAb conjugated to a cytotoxic payload to enable the selective delivery of the cytotoxic moiety while reducing the side effects and immunogenicity to the patient. Since the first ADC approval by the FDA, the design of new generation of ADC products has been extensively developed to improve the therapeutic efficiency of first-generation ADCs. Concomitantly, different analytical methods have been improved to enable critical quality attributes (CQA) assessment and thus support ADCs development and production at different stages. In this context, liquid chromatography (LC), capillary electrophoresis (CE), and mass spectrometry (MS) have played a predominant role in ADCs characterization, showcasing the advantages of these methods to identify and potentially quantify the different ADCs populations resulting from the bioconjugation process. This review provides a detailed overview about cutting-edge analytical methods with a particular focus on studies reported during the last five years related to LC, CE, and MS, allowing not only a deeper insight into ADCs structure, but also to provide further evidence about their in vitro and in vivo biotransformation products. The maturity, robustness, and high throughput associated to these methods allow their progressive introduction in regulatory and clinical environments, ensuring the structural integrity of ADCs prior to their administration to the patients. The examples reported in this review article clearly highlight the relevance of using tailored analytical strategies for a more comprehensive ADC characterization and thus continue the contribution to early developability assessment and bring next-generation ADCs into the market.

This study developed a novel aprepitant (APT) nanocrystal-containing oral disintegrating tablet (ODT) to enhance the oral bioavailability of APT through "rapid disintegration". APT nanocrystal suspension (APT-NS) was prepared via miniaturized media milling, with a particle size of 199.25 ± 12.88 nm, a polydispersity index (PDI) of 0.148 ± 0.026 and zeta potential of -24.82 ± 1.28 mV. The APT-NS was spray-dried into dry powders (APT-NCS) and further processed into ODTs via freeze-drying. Through central composite design-response surface methodology (CCD-RSM) optimization, the final APT-ODT formulation demonstrated rapid disintegration (< 5 s) and excellent dissolution (> 95% within 2 min). Results of X-ray diffraction (XRD), differential scanning calorimetry (DSC), and Fourier transform infrared spectroscopy (FTIR) confirmed the absence of crystalline transformation or chemical degradation during processing. Pharmacokinetic results demonstrated that both APT-NS and APT-ODTs exhibited approximately twofold higher AUC_0-48 h (28.51 ± 1.62 μg·h/mL and 32.61 ± 2.19 μg·h/mL, respectively) compared to free APT. In conclusion, the optimized APT-ODT successfully improved the oral bioavailability of APT, representing a promising new strategy for clinical application.

Target-mediated drug disposition (TMDD) refers to non-linear pharmacokinetic (PK) profiles arising from the saturable interaction between a drug and its pharmacological target. Recently, our group revisited the TMDD cases observed in small-molecule drugs interacting with high-specificity targets, obtaining quantitative insights into in vivo target binding. In this study, we developed a physiologically-based PK (PBPK) model incorporating TMDD and pharmacodynamic (PD) responses (TMDD-PD) for finasteride and dutasteride, two time-dependent inhibitors of 5α-reductase (5αR). In addition to the tissue- and subtype-dependent 5αR inhibition, the model incorporated irreversible inactivation of 5αR and its turnover to account for the mechanism of time-dependent inhibition. We simultaneously analyzed the non-linear PK and PD (dihydrotestosterone level decline and recovery) data for both finasteride and dutasteride. Our model effectively captured the observed PK/PD profiles of both drugs, and the model-derived 5αR inhibition parameters were comparable to those obtained from in vitro 5αR inhibition data. Sensitivity analysis revealed that saturation of target binding is the primary driver of the non-linear PK and corresponding PD profiles, while slow turnover of 5αR contributes to the prolonged PD effect. Our results further suggest that the distinct PD profiles of finasteride and dutasteride are attributable to their differing inhibition characteristics against 5αR subtypes (selectivity and affinity). These findings extend our previous work and further support the utility of TMDD-PD modeling for optimizing clinical dose and improving therapeutic outcomes for small-molecule drugs exhibiting TMDD with time-dependent target inhibition.

Randomized, well-controlled trials are the gold-standard for evaluating novel therapies, but they often fail to fully account for the placebo response, particularly in pain-related conditions such as migraine, where subjective improvement is common in placebo groups. This placebo response is influenced by individual-level factors, such as prior treatment experience, expectations of treatment benefit, and demographic characteristics such as age, race, sex, and clinical trial location. As clinical trials grow increasingly global and diverse, ensuring balanced demographic distribution across treatment arms is essential to accurately assess efficacy. We conducted a meta-analysis of placebo arm data from 14 pivotal Phase 2 and 3 trials that supported approval of six drugs for the preventive treatment of episodic and chronic migraine. Data were stratified by migraine type and analyzed by demographic variables including age, sex, race, menopause status, trial region, prior prophylactic medication use, route of administration, and frequency. Changes from baseline were evaluated for monthly migraine days (primary endpoint) and migraine-related symptoms (e.g., headache days, headache days of moderate/severe intensity, photophobia/phonophobia days, and nausea/vomiting days). Placebo responses were consistently higher in subjects who had not used prior preventive medications, African Americans, and participants enrolled in North America. These findings suggest that placebo response in migraine trials may be modulated by demographic and treatment-related factors, especially when subjective endpoints are used. Accounting for these variables during trial design and subject allocation could help minimize bias, reduce the risk of false negative outcomes, and enhance the likelihood of accurately demonstrating treatment efficacy.

Orodispersible films (ODFs) are increasingly employed for individualized drug delivery due to their ease of administration and precise dosing. However, their drug loading capacity is often limited by the need to maintain thin, flexible structures, posing a particular challenge for incorporating poorly soluble drugs. This study aimed to develop and characterize porous ODF matrices optimized for 3D printing of medicated inks. The primary objective was to investigate the impact of macroporosity on the dissolution kinetics of both poorly soluble and readily soluble drugs, with a focus on enhancing the release of the poorly soluble dexamethasone. Porous ODFs were fabricated via solvent casting using silica- and silicate-based porogens, then loaded with caffeine or dexamethasone through 3D printing. The films were comprehensively characterized using structural (micro-CT, BET), mechanical, and solid-state techniques (SEM, Raman microscopy, FTIR, XRD) to assess porosity, drug crystallization behavior, and drug-matrix compatibility. Drug release was evaluated through dissolution studies. Silica-based porogens yielded films with tunable macroporosity, supporting high drug loads (up to 3-5 times the ink volume). Dexamethasone printed on the SY2 substrate exhibited markedly enhanced dissolution (79.2 ± 1.8%) compared to its powdered form (29.9 ± 11.5%), achieving 61.5% release within 20 min. In contrast, caffeine (readily soluble) showed a transient reduction in dissolution rate during the initial two minutes, attributed to increased particle size and delayed film disintegration. Overall, integrating porous matrix design with 3D printing significantly improved the dissolution of poorly soluble dexamethasone without inducing drug-matrix interactions, confirming that structural modifications drive the enhanced release.

Typically, parent drug is measured for bioequivalence (BE) assessment because it's more sensitive to detect formulation differences, compared to its metabolite(s). For simvastatin immediate release (IR) tablets, current product-specific guidance (PSG) recommends measuring both parent and metabolite but taking metabolite as supportive data. This study aims to utilize physiologically based pharmacokinetic (PBPK) modeling and virtual BE (VBE) simulation to evaluate the sensitivity of parent vs metabolite as analyte on BE assessment, using simvastatin case and explore relevant mechanism. PBPK model was developed to describe drug exposures of parent drug simvastatin (SV) and metabolite simvastatin acid (SVA) in healthy individuals administered with 20-80 mg IR tablets under fasting condition. VBE simulations were conducted to evaluate the sensitivity of SV and SVA as analytes to assess BE between test product and reference listed drug. PBPK model incorporating enzyme- and transporter-mediated kinetics reasonably captures fasting PK profiles for SV and SVA. VBE simulations indicate that parent drug, in general, is more sensitive to demonstrate BE as compared to metabolite. However, this study highlighted the importance of conducting BE analysis using PK data for both SV and SVA when the test product contains certain excipients in the formulation that may impact transporter activity for changing clearance and subsequent drug exposure of metabolite. The VBE simulation results further implied that in some cases, SVA as analyte is more sensitive to show drug exposure differences and may enhance the assessment of formulation effect, as compared to SV. This aligns with current PSG recommendations.

Drug development can take up to 15 years, costing as much as $11 billion USD, and relies heavily on high-quality data. The goal of this investigation of contract research organizations (CROs) was to assess the impact of data management activities (such as curation, quality assessment and integration) on model-informed drug development (MIDD) deliverables. A survey was sent to a diverse sample of CROs, to evaluate their baseline experience with assessing the data quality of sponsor-provided data and the time required to create analysis-ready datasets. It was distributed to 44 colleagues from 32 companies offering pharmacometrics services, including data management. The survey included 11 questions; 9 were multiple choice and 2 open-ended. Responses were gathered anonymously to ensure confidentiality and intellectual property protection and later shared with all participants. Of the 17 survey respondents, most develop data specifications and create analysis-ready datasets. The majority (65%) said the data they received from sponsors was rarely (< 10%) immediately usable due to improper formatting and quality issues like missing data and inconsistencies. Over 50% cited lack of definition/specifications as the primary reason. Assuming an average programming cost of $250/hour, cleaning client data takes CROs 3 to 24 h, costing between $750 and $6000 per dataset. Significant time is spent on rectifying poor-quality data. Automated data quality assessments can improve efficiency checks, though automation alone cannot resolve all quality issues. Better communication, collaboration, and systematic approaches to address data quality issues involving automation and AI are essential to further improve data quality.

International reference standards have been established as gold standards for several biological products. Use of international units can drive consistency and standardization for biosimilar products across manufacturers. However, our research and development for Retacrit® (epoetin alfa-epbx), the first and only biosimilar FDA approved for all indications of Epogen®/Procrit® (epoetin alfa), showed that use of a compendial reference standard overestimated the potency of both the biosimilar and the originator product. Possible causes are or imprecision in the methods used to assign potency, or differences in the isoform composition between the compendial reference standard and product. Tracing the history of international reference standard potency assignment for erythropoietin provided insight into this issue. An internal product specific reference standard and process for qualifying and maintaining future replacements are recommended. Use of specific activity as compared to percent potency or units/mL was a useful tool and can provide a means to normalize data from multiple methods and samples with differences in labelled activity from various manufacturers.

The evaluation of monoclonal antibodies (mAbs) charge variants during their entire life cycle is crucial, as their profiles represent a critical quality attribute of biotherapeutics. While the current scenario still shows marked analytical non-uniformity in the evaluation of charge variants with imaged capillary isoelectric focusing (icIEF) with many "product-specific" methods, regulatory authorities are increasingly encouraging the utilization of horizontal standards, such as Platform Analytical Procedures (PAPs). A practical Analytical Quality by Design (AQbD) workflow is provided, emphasizing the Design of Experiments as a Quality Risk Management tool to develop a PAP based on icIEF, able to accurately measure charge variants pI values. Infliximab was chosen as the leading molecule. The cause-effect matrix, combined with an asymmetric screening design, identified key parameters exerting a critical impact on the Analytical Procedure Attributes. PAP quality measurements were ensured by a 10% risk acceptance level, employing response surface methodology and Monte Carlo simulation. The developed PAP was validated using three independent System Suitability samples and exhibited a low bias in the pI measurement (less than 2%), while maintaining satisfactory separation performance. Good intra-day and inter-day repeatability, combined with a robustness test and an exploratory application to real samples of three different therapeutic mAbs, confirmed its versatility. The study supports regulatory trends by demonstrating the successful application of AQbD in PAP development. This icIEF platform would ensure a systematically consistent analysis of charge variants, where pI is promoted to an objective tool, to be used as an additional reliable parameter in the Quality Control context.