AAPS Journal最新文献

Protein-based therapeutics may elicit undesired immune responses in a subset of patients, leading to the production of anti-drug antibodies (ADA). In some cases, ADAs have been reported to affect the pharmacokinetics, efficacy and/or safety of the drug. Accurate prediction of the ADA response can help drug developers identify the immunogenicity risk of the drug candidates, thereby allowing them to make the necessary modifications to mitigate the immunogenicity. In this study, we leveraged the rich clinical study data collected by Roche/Genentech to identify factors that impact drug immunogenicity. We focused on conventional monoclonal antibodies, but have included a variety of additional drug modalities in the analysis. We show that the clinical ADA incidences are associated with the mechanism of action of the drugs, the mechanism of action of comedications, the routes of drug administration and the diseases of the patient cohort. By combining these clinical factors with the in silico epitope prediction, we improved the prediction accuracy of drug immunogenicity in clinical trials (AUC of cross validation improved from 0.72 to 0.93).

Minimizing harm is a cornerstone of ethical research practices. A drug that has undergone extensive clinical pharmacological testing in healthy participants (HPs) and a diverse selection of patients can be described with a sufficiently predictive population pharmacokinetic (PopPK) model. In impaired clearance trials, recruitment is minimized and underpowered for all but major exposure differences. Virtual HP arms have been reported to support similar conclusions to conventional impaired clearance studies, and further minimize potential harm of drug exposure without medical benefit by eliminating an arm of the study. However, the extent to which the conventional analysis of impairment studies compare to the simulation approach is unknown. Here we assess the operating characteristics of the virtual cohort approach along with the conventional approach through controlled simulations. These simulations included a simple, widely accessible PopPK model and several internal models that have been used in a previous meta-analysis of the virtual cohort approach. In the pairwise comparisons assessed, the virtual cohort simulation approach had greater power per sample size than the conventional approach and the same power under the null hypothesis. Given key methodological differences, it is recommended that the simulation and conventional approaches be treated as having approximately the same power under equivalent conditions. These results provide a strong justification for the use of the virtual cohort approach when an adequate PopPK model is available, minimizing unnecessary exposure to study drugs that will not benefit healthy study participants.

Bile salts are biosurfactants released into the intestinal lumen which play an important role in the solubilisation of fats and certain drugs. Their concentrations vary along the gastrointestinal tract (GIT). This is significant for implementation in physiologically based pharmacokinetic (PBPK) modelling to mechanistically capture drug absorption. The aims of this meta-analysis were to collate all appropriate data on intestinal bile salt concentrations in healthy adults across all GIT segments in fasted and fed states for the purpose of PBPK modelling. Terms relating to bile composition were searched in PubMed and Google Scholar from inception to May 2024. Selected studies included aspirated intestinal fluid collected via gastric tubes or colonoscopy. Results showed high variability across studies and a time-dependency for the fed state. Data were rich for the duodenum, which showed a two-fold increase for the fed state versus the fasted state within multiple studies. Peaks and troughs in bile salt concentrations along the GIT were observed for both fasted and fed states, likely due to segmental water absorption differences. The highest between subject variability was observed for the duodenum in the fasted and fed state and the fed proximal jejunum, distal ileum, and colon. The findings from this meta-analysis can be used for the purpose of PBPK modelling to capture segmental drug solubilisation and absorption in fasted and fed states. However, data are lacking under different fed conditions, especially following low-fat meals, so the impact of different fat content associated with different meals on bile salt concentrations cannot be discerned.

In addition to the known therapeutic indications for cannabidiol, its administration by inhalation appears to be of great interest. Indeed, there is evidence of cannabidiol's efficacy in several physiological pathways, suggesting its potential for a wide range of applications for both local and systemic pulmonary administration like cancers. Significant advances in pulmonary drug delivery have led to innovative strategies to address the challenges of increasing the respirable fraction of drugs and standardizing inhalable products. Among different devices, dry powder inhalers offer significant advantages including high stability and ease of use. Particle engineering using techniques such as spray drying is now the focus of research and is expected to improve upon, rather than completely replace, traditional carrier-based formulations. The development of carrier-free powders (without lactose-carrier) is mainly used for medicines with low active ingredient doses, which limits the technology. Previously, we demonstrated the benefits of using a cyclodextrin to obtain deflated spherical-shaped powders by spray drying. In this study the potential of this excipient with a very poorly water-soluble active molecule was investigated. Inhalable cannabidiol powders were developed by spray drying, using the solubility enhancers hydroxypropyl-beta-cyclodextrin and ethanol to optimize cannabidiol water-solubility. Electron microscopy images revealed consistent deflated spherical shapes, while particle size analysis showed low polydispersity and suitable sizes for deep lung deposition (2 µm). The selected engineered powders (without ethanol) had very high fine particle fractions (> 60%) due to their deflated surface. Finally, the powder was instantly solubilized leading to drug dissolution, which is important for therapeutic efficacy. In conclusion, this study successfully develops a cannabidiol inhalation powder by particle engineering having suitable aerosolization behavior. Due to the speed of the process and the performance of the finished product, this work opens the door for future studies. It has been shown that active molecules that are only slightly soluble in water can be formulated effectively as a powder for inhalation. Other molecules could be tested and subsequent in vivo studies conducted to demonstrate correlation with these in vitro results.

Freeze drying is one of the common methods to extend the long-term stability of biologicals. Biological products in solid form have the advantages of convenient transportation and stable long-term storage. However, long reconstitution time and extensive visible bubbles are frequently generated during the reconstitution process for many freeze-dried protein formulations, which can potentially affect the management efficiency of staff, patient compliance, and product quality. The reconstitution time has been extensively studied, but the influence of the formulations on the formation of visible bubbles is often overlooked. This paper investigated the effect of freeze-drying formulation factors (i.e., protein concentrations, surfactant concentrations, and sucrose/mannitol compositions) on product stability and visible bubbles generated during reconstitution of freeze-dried etanercept formulations. The generating and breakup mechanisms of visible bubbles were detected via internal microstructure of cake, surface tension, and viscosity measurement. Under the same protein concentration, the formulation of mannitol mixed with sucrose in a weight ratio of 4:1 produces fewer visible bubbles during the reconstitution process compared to the formulation of sucrose with the same total mass. This has been proven to be due to the large number of smaller radius pores distributed in the pores of the freeze-dried cake of the former, while the average internal structure pores of the latter are much larger than those of the former. As an amorphous stabilizer, sucrose can ensure the long-term stability of protein and greatly reduce the generation and maintenance of foams in the reconstitution process, making it a more robust excipient for freeze-dried protein formulations.

The study quantitatively analyzes and compares the pharmacokinetics (PK) of methylprednisolone (MPL) in humans upon administration of various dosage forms. The PK parameters and profiles of MPL in healthy subjects were collected from 22 literature sources. A minimal physiologically based pharmacokinetic (mPBPK) model consisting of blood and two tissue (lumped liver and kidney, remainder) compartments with nonlinear tissue partitioning was applied to describe MPL disposition. Overall 18 plasma concentration profiles were well captured and 85% of PK parameters reasonably estimated. The clearance (CL) of MPL averaged 336 mL/h/kg and appeared slightly nonlinear across a dosage range of 5 to 800 mg, the distribution volume (V_d) averaged 1.17 L/kg, and the model predicted elimination half-life (t_1/2) was 2.6 h. Rapid prodrug conversion was found for intravenous MPL sodium succinate (MPSS) with a t_1/2 of 1.7 min, and followed by MPL phosphate (MPPS) 3.8 min, MPL hemisuccinate (MPHS) 16 min, and MPL suleptanate (MPSP) 2.9 h. Their bioavailabilities (F) varied slightly from 60 to 73%. Intramuscular doses showed an absorption rate constant (k_a) of 1.5 h^-1 for MPSS and 96 h^-1 for MPSP. Oral doses of 5 formulations were examined. Medrol exhibited greatest absorption with F of 74% and k_a of 2.1 h^-1, while one generic product had F of 32.6%. This study demonstrated the utility of a mechanistic mPBPK disposition model for comparing MPL formation from various esters, absorption from several oral dose formulations, and modest variability across numerous PK studies in healthy humans.

Nowadays, synthetic cathinones (SCs) is the second more representative subclass of New Psychoactive Substances, accounting for 104 analogues in the illegal market. Since its first report in 2011, α-pyrrolidinovalerophenone (α-PVP) gained popularity among drug users, provoking an increased number of intoxications. Nonetheless, pharmacokinetics data is still limited in the literature. An observational non-controlled naturalistic study on 8 healthy volunteers was conducted to assess the α-PVP and β-OH-α-PVP concentrations in OF and urine, after snorting 10 mg or 20 mg of α-PVP. A multi-analytical approach based on GC-EI-MS/MS and LC-HESI-HRMS/MS was developed and fully validated for the analytes quantification, while four untargeted LC-HESI-HRMS/MS methods in full-MS and ddMS² were set up for unknown metabolites characterization in urine samples assisted by a dedicated data mining software. In OF, α-PVP reached a mean C_max of 762 ± 323 ng/mL at 1 h after 10 mg administration, while a C_max of 2,900 ± 1,373 ng/mL at 47 min after 20 mg dose. In urine, a total α-PVP mean amount of 179.2 ± 94.9 µg was accumulated after 10 mg dose, (27.2 ± 9.8 µg between 0-2 h and 152.0 ± 98.2 µg between 2-5 h), while a total amount of 122.9 ± 44.0 µg, of (36.2 ± 16.5 and 86.7 ± 28.3 µg between 0-2 and 2-5 h, respectively) was detected after 20 mg dose. Among the 10 identified metabolites, β-OH-α-PVP was a minor metabolite (total amount: 56.4 ± 27.1 and 69.1 ± 38.1 µg after 10 mg and 20 mg). The N-butanoic acid metabolite was the most abundant, detected also as glucuronide. In conclusion, α-PVP showed a later time peak than non-pyrrolidine SCs, with comparable C_max. The pyrrolidine ring oxidative opening produced the most abundant urinary metabolite, independently from the dose.

Antibody-drug conjugates (ADCs) are intricate compounds that pose significant challenges in bioanalytical characterization. Therefore, multiple bioanalytical methods are required to comprehensively elucidate their pharmacokinetic (PK) profiles. In this study, we investigated DS001, an ADC consisting of a humanized monoclonal antibody (hRS7), a cleavable chemical linker, and the microtubule inhibitor monomethyl auristatin E (MMAE), with a drug-to-antibody ratio (DAR) of 8. This study established a rapid and sensitive hybrid immunoaffinity liquid-chromatography-tandem-mass-spectrometry (LC-MS/MS) approach for the simultaneous quantification of the total antibody and the enzymatically cleavable conjugated payload of DS001. This method is capable of monitoring fluctuations in average DAR values during PK assessments. The sample preparation procedure involved immunocapture, denaturation, trypsin digestion, papain digestion, and termination, all completed within a total processing time of less than 4 h. The method demonstrated linearity for the total antibody in the range of 100 ng/mL (lower-limit-of-quantification, LLOQ) to 100,000 ng/mL, and for the conjugated payload from 3.495 ng/mL (LLOQ) to 3495 ng/mL in rat serum. Both analytes exhibited standard curve correlation coefficients (r) greater than 0.990 within their respective linear ranges. The precision and accuracy of the method were within ± 15% (± 20% for LLOQ). The verified LC-MS/MS approach was successfully employed in the PK analysis following intravenous administration of 0.2 mg/kg DS001 in rats via tail vein injection.

Artificial Intelligence (AI) and AI-driven technologies are transforming industries across the board, with the pharmaceutical sector emerging as a frontrunner beneficiary. This article explores the growing impact of AI and Machine Learning (ML) within pharmaceutical Regulatory Affairs, particularly in dossier preparation, compilation, documentation, submission, review, and regulatory compliance. By automating time-intensive tasks, these technologies streamline workflows, accelerate result generation, and shorten the product approval timeline. However, despite their immense potential, AI and ML also introduce new challenges. Issues such as AI software validation, data management security and privacy, potential biases, ethical concerns, and change management requirements must be addressed. This review highlights current AI-based tools actively used by regulatory professionals such as DocShifter, Veeva Vault, RiskWatch, Freyr SubmitPro, Litera Microsystems, cortical.io etc., examines both the benefits and obstacles of integrating these advanced systems into regulatory practices. Given the rapid pace of technological innovation, the article underscores the need for proactive collaboration with regulatory bodies to manage these developments. It also stresses the importance of adapting to evolving regulatory frameworks and embracing new technologies. Although regulatory agencies like the United Sates Food and Drug Administration (USFDA), European Medicines Agency (EMA), and Medicines and Healthcare products Regulatory Agency (MHRA) are working on guidelines for AI and ML adoption, clear, standardized protocols are still in the works. While the journey ahead may be complex, the integration of AI promises to fundamentally reshape regulatory processes and accelerate the approval of safe, effective pharmaceutical products.