AAPS Journal最新文献

Methylphenidate extended-release (ER) products are used in the treatment of attention-deficit/hyperactivity disorder (ADHD). These products exhibit diverse pharmacokinetic (PK) profiles that influence early systemic exposure and clinical response. To ensure bioequivalence (BE) for products such as Concerta and Ritalin LA, both the FDA and EMA recommend the use of pAUC_0-3h, with the EMA additionally suggesting the inclusion of C_max,0-3h. However, it remains unclear whether C_max,0-3h offers added discriminatory value beyond pAUC_0-3h in BE evaluation. The objective was to assess the sensitivity of early exposure metrics (pAUC_0-3h, C_max,0-3h, and C_3h) to changes in the SKAMP (Swanson, Kotkin, Agler, M-Flynn, and Pelham rating scale) response, a pharmacodynamic (PD) endpoint commonly used to assess clinical response in ADHD. PK/PD model simulations were performed for seven methylphenidate ER products. These products were categorized by PK absorption model: parallel dual first-order (e.g., Concerta) and parallel zero-order and first-order (e.g., Metadate CD). The PD model described placebo-adjusted SKAMP response based on simulated plasma concentrations. Simulations were conducted by varying the fast absorption rate constant (ka_Fast) to assess how changes in early exposure metrics affect AUEC_0-3h of the SKAMP response. The results indicated that pAUC_0-3h generally showed greater sensitivity to SKAMP response than C_max,0-3h and C_3h. Although C_max,0-3h exhibited high sensitivity in products with dual first-order absorption, its responsiveness remained inferior to pAUC_0-3h. These findings support the use of pAUC_0-3h as the primary early exposure metric for therapeutic equivalence assessment and suggest that C_max,0-3h may not provide further discriminatory value beyond that of pAUC_0-3h.

Drug permeability across epithelial barriers is critical for predicting oral bioavailability and efficacy. Conventional models, including animals and simple cell cultures, lack intestinal complexity and translational value. Organoids and organ-on-a-chip technologies address these limitations, offering physiologically relevant, human-specific platforms for more accurate drug permeability assessment [1]. Intestinal organoids, derived from stem cells, reproduce key structural and functional features of the gut, including crypt-villus organization, transporter and enzyme expression, and absorptive and secretory functions. Organoids are grown inside of microfluidic chips under dynamic media flow that attempt to recapitulate one or more tissue-specific functions, thereby supporting epithelial maturation and enabling more predictive drug transport measurements. Permeability can be studied by introducing compounds at the apical surface and quantifying their translocation to the basolateral compartment using analytical techniques. Compared with animal models, these approaches yield data of greater human relevance while reducing ethical concerns [2]. Furthermore, they enable the evaluation of passive permeability, active transport, intestinal metabolism, and interactions with microbial products [3]. In this study, permeability was investigated for three model compounds with distinct properties: lisinopril (low permeability), metoprolol (moderate permeability), and fluconazole (high permeability). Experiments were conducted using the Emulate human duodenum-on-a-chip platform and benchmarked against the Ralph Russ Canine Kidney (RRCK) cell line. Apparent permeability (P_app) values were correlated with literature-reported effective permeability (P_eff) using linear regression. This regression was implemented in Simcyp® Simulator and GastroPlus™ to predict systemic exposure, which was compared against observed plasma concentration-time profiles.

The liquid and solid formulations of self-nano-emulsifying drug delivery systems (SNEDDS) have garnered significant attention in the pharmaceutical field for their ability to enhance the solubility and absorption of hydrophobic drugs. While both liquid and solid SNEDDS result in improved bioavailability; portability, patient compliance, desired administration route, and ease of preparation are some factors that contribute to the decision-making of the final SNEDDS dosage form. This review provides a comprehensive analysis of SNEDDS formulations in the liquid and solid state, including production and performance factors that researchers ought to consider when developing their final dosage form. We investigate excipient characteristics, stability concerns, liquid-to-solid preparation methods and their challenges, and in vivo and in vitro comparisons of both dosage forms. Finally, we explore the potential of artificial intelligence in the design of SNEDDS formulations.

In drug development, exposure-response models are widely used to inform decisions in dose optimization processes. Type I error (T1) due to misspecified models can lead to critical and costly decisions. Therefore, a new approach called: "Randomized-exposure mixture-model analysis with type 1 error control (REMIX)" to account for model misspecification is proposed and compared against the standard approach (STA). A total of 82 simulation-estimation scenarios for a hypothetical antidiabetic drug were investigated. T1 rate and power was tested in presence or absence of model misspecification. Moreover, predictive performance of both approaches and accurary of the drug-effec parameter estimates was assessed. Precision and accuracy for the drug-effect parameter were compared to the STA parameter estimates for each structural model with the most patients. REMIX outperformed STA regarding T1 rate inflation (21/82, 44/82 for REMIX and STA, respectively) but led to lower power. In a case study with an example of a clear drug effect and no model misspecification, 27 patients were needed for REMIX compared to 17 for STA to reach 80% power. rRMSE and rBias for full REMIX and STA models were similar in most scenarios if a drug effect was present, but REMIX outperformed STA when no real drug effect was present. Precision and accuracy of parameter estimates were similar for REMIX and STA. Application of REMIX in further studies and comparison to other approaches to control T1 are warranted.

Melanoma is a highly aggressive skin cancer that accounts for only ~ 1% of all skin cancer cases but is responsible for most skin cancer-related deaths. Despite advances in systemic therapies, localized treatment options remain limited. Dacarbazine (DCB), the only FDA-approved chemotherapeutic agent for melanoma, is administered intravenously and is associated with systemic toxicity, poor patient compliance, and nonspecific drug distribution. This study presents a bilayer dissolving microneedle array patch (dMAP) for localized, minimally invasive delivery of DCB to the skin, offering a potential alternative for treating cutaneous melanoma. The tip-casting gel formulation was optimized to ensure sharp, defect-free MAP tips with uniform drug distribution. The optimized bilayer dMAP exhibited strong mechanical properties (< 10% needle deformation) and effective insertion capability, reaching approximately 390 µm in depth within the Parafilm® M model. Ex vivo evaluations using full-thickness neonatal porcine skin demonstrated the complete dissolution of bilayer dMAP tips within 60 min and effective pore formation, as confirmed by methylene blue staining. In ex vivo setup, the bilayer dMAP formulation demonstrated 3.93-fold increase in permeability and a 3.02-fold increase in DCB deposition compared with those of the suspension. Furthermore, bilayer dMAP maintained complete drug stability over 8 days at room temperature under light-protected conditions, whereas free DCB showed approximately 7.5% degradation in aqueous media over the same duration. Therefore, bilayer dMAP provides a stable, minimally invasive, and efficient platform for localized drug delivery to the skin, highlighting its potential as a promising alternative to conventional topical formulations for the treatment of cutaneous melanoma.

Although the use of demographic matching in organ impairment studies is recommended to exclude the confounding effect of demographics on the pharmacokinetic (PK) study results, very little guidance exists on the practical implementation of this approach. Individual matching (IM) as well as several strategies for group matching (GM) have been described in literature. We conducted a systematic review, including 170 renal (RI) and 173 hepatic impairment (HI) studies completed in the last 25 years and characterized used matching methodologies and selected matching criteria. In RI, GM appears more common (70%), while in HI IM was preferred (55%). Age, body weight or body mass index (BMI), and sex were the most commonly used matching criteria, with the most common acceptance margins of ± 10 years for age, ± 10-20% for body weight, and ± 15-20% for BMI, irrespective of matching method used. While IM required notably more subjects in the control group, we did not find a significant effect of various matching strategies on study duration or recruitment between different matching strategies. No matching was used in most of the studies conducted in the target patient population with organ impairment, as opposed to the studies conducted in general organ impairment population without the target indication. Based on the results of this review, we proposed a framework for selection of matching strategy, with IM being a recommended matching method in most cases and GM being suitable for compounds that have well-characterized impact of demographic characteristics on PK and a low between-subject variability.

The tissue response to long-acting injectables (LAIs) suspension injection may impact the product in vivo performance. One such response is the formation of an inflammatory cell layer (ICL) resulting in an envelope around the injected particles. This study aims to use a mechanistic model to describe the clinical in vivo exposure and performance of an intramuscular LAI suspension and evaluate impact of ICL physiological response at the injection site in humans. Aripiprazole lauroxil (AR-L) was used as the model drug. A baseline pharmacokinetics model was built and validated for aripiprazole. The impact of inflammation on the LAI in vivo performance was assessed by including an ICL model. The developed pharmacokinetic model adequately described the observed plasma profiles of AR following intravenous and oral administration in humans. The initial intramuscular predictions assumed that the absorption rate is dependent on the dissolution and partitioning of AR-L into the systemic circulation from the intramuscular (IM) depot. The simulation resulted in a shape mismatch between the simulated and observed data and an earlier predicted T_max. The inclusion of an ICL in the model resulted in adequate predictions (fold errors less than 25%) of the exposure and shape of the plasma concentration-time profiles. Utilizing a time-dependent change in ICL thickness resulted in reasonable predictions of AR pharmacokinetic profiles following IM administration of multiple strengths of the AR-L suspension. This shows the utility of physiologically based pharmacokinetic (PBPK) model in mechanistically describing the in vivo performance of LAIs.

Raman spectroscopy is a proven Process Analytical Technology (PAT) for monitoring mammalian cell culture processes in biopharmaceutical manufacturing. In-line Raman probes provide real-time chemical fingerprints of metabolites and cell culture health analyzed via chemometric modeling. However, Raman hardware (e.g. cables, detectors, optics, probes, and lasers) and software - performing calibration, noise reduction, and cosmic ray removal - impart vendor specific spectral signatures, rendering Raman chemometric models specific to the vendors. This vendor specificity complicates method validation and transfer between manufacturing sites deploying different vendor equipment and impedes upgrades, maintenance, and replacement of obsolete Raman equipment. In this work, we compared two calibration transfer methods to address vendor-to-vendor variation. Piecewise Direct Standardization (PDS) and Spectral Subspace Transformation (SST) methods successfully reduced spectral response variation between previous (Parent) and new (Child) Raman systems. We tested calibration transfer results with offline samples and an established validation approach utilizing paired spectra from Parent and Child Raman systems. Finally, we explored the influence of calibration transfer parameters including training set size, preprocessing position, and window size (number of components) for PDS and SST. Through this investigation we demonstrate the feasibility of this proposed vendor-to-vendor calibration transfer approach as a promising and effective chemometric model transfer between Raman vendors without significant method re-development or re-validation. This approach improves agility within the deployment strategy of chemometric models across supply chain networks and bolsters Raman spectroscopy as a versatile PAT tool for advanced manufacturing within the biopharmaceutical industry.

Here we challenge the assumption that hepatic uptake can be rate-limited solely by transporter-mediated influx clearance, as commonly concluded in interpretations based on the Extended Clearance Concept (ECC). We initially review the derivation of renal and hepatic clearance independent of differential equations based on adaptation of Kirchhoff's Laws from physics, incorporating clinically relevant aspects such as transporter activity, organ blood flow, and clearance from the site of drug delivery into systemic circulation. In doing so, we highlight the limitations of the ECC framework, which does not adequately capture all aspects of these mechanistic elements and note that no experimental data or PBPK analyses definitively support its validity. In contrast, we show that all hepatic clearance data can be adequately explained based on our derivations, which provide a more robust and mechanistically consistent framework for interpreting renal and hepatic clearance. The derived equations define the net difference between influx and efflux clearances as the key determinant of transporter involvement in hepatic drug disposition, rather than considering influx alone as in the ECC. This approach is analogous to the treatment of secretion and reabsorption clearances as opposing processes in renal clearance, where their difference determines the net transport. We also question the mechanistic accuracy of determining hepatic influx and efflux clearances in vitro using initial rates of membrane passage, as is typically done for passive processes. Such measurements inherently reflect the net intramembrane difference between influx and efflux clearances, and do not allow for independent quantification of directional transport, due to the inability to measure drug concentrations within the membrane. Finally, while we acknowledge the utility of ECC and PBPK analyses for predicting changes in pharmacokinetic exposure due to DDIs (or other variables such as disease state, pharmacogenomics, etc.), we caution that model-based data fitting, however useful, does not constitute mechanistic validation.

The administration of therapeutic proteins, such as monoclonal antibodies (mAbs) may result in the formation of anti-drug antibodies (ADA), but there is limited publicly available data for biotherapeutics with exogenous targets or with targets in low abundance systemically. ADAs can impact a biotherapeutic's safety, efficacy, and pharmacokinetics, so evaluation of immunogenicity is required for all therapeutic proteins. This analysis sought to evaluate the immunogenicity of two mAbs against COVID-19, casirivimab (CAS) and imdevimab (IMD) administered as a cocktail (CAS + IMD), in multiple clinical trials across different participant populations to add knowledge about the immunogenicity risk of protein therapeutics against exogenous targets and the association between immunogenicity and drug exposure. Overall, the incidence of treatment-boosted and treatment-emergent ADAs and neutralizing antibodies in both disease treatment and prophylaxis settings were low (i.e., < 11%). Participants in these studies were followed for up to 225 days post-last dose. Over time, the incidence of treatment-emergent and treatment-boosted immunogenicity for each mAb increased, but the rates and titers remained low overall; when it developed, patients usually developed ADA to both mAbs. Frequency of administration, dose, and route of administration did not appear to impact rates of immunogenicity. Concentrations of CAS and IMD were similar between participants of different immunogenicity status, indicating immunogenicity of CAS and IMD had no impact on pharmacokinetics of these mAbs; there was also no observed impact on safety or efficacy. The data presented here may provide supportive information for assessing the immunogenicity risk of protein therapeutics with exogenous targets.