AAPS Journal最新文献

Sotorasib is a novel KRAS^G12C inhibitor that has shown robust efficacy, safety, and tolerability in patients with KRAS^G12C mutation. The objectives of the population pharmacokinetic (PK) analysis were to characterize sotorasib population PK in healthy subjects and patients with advanced solid tumors with KRAS^G12C mutation from 6 clinical studies, evaluate the effects of intrinsic and extrinsic factors on PK parameters, and perform simulations to further assess the impact of identified covariates on sotorasib exposures. A two-compartment disposition model with three transit compartments for absorption and time-dependent clearance and bioavailability well described sotorasib PK. Sotorasib exposure increased in a less-than-dose proportional manner across the evaluated 180 mg to 960 mg dose range. Disease burden, measured by Eastern Cooperative Oncology Group (ECOG) score and baseline tumor size, were identified as significant covariates on clearance. Lower disease burden was associated with higher clearance (and thus lower sotorasib exposure). Low albumin was found to be associated with lower clearance of sotorasib. Use of PPIs was associated with reduced sotorasib exposures. Although sex, race, and high fat meal were significantly associated with PK parameters, their impact on exposures were not clinically relevant. Other evaluated covariates, including body weight, age, renal impairment (evaluated by chronic kidney disease stage score) and hepatic impairment (evaluated by NCI criteria) were not statistically significant. Greater baseline disease burden and low albumin were associated with lower sotorasib clearance; based on the established efficacy and safety profiles from clinical trials, the estimated magnitude of these effects does not warrant a dose adjustment.

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.

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.

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.

NH600001 is a new general anaesthetic drug with a structure similar to etomidate. The objective of this study was to investigate the relationship between concentrations of NH600001 and sedation efficacy based on data from phase I-II studies and factors influencing the pharmacokinetics and pharmacodynamics of NH600001. The dataset consisted of 2 phase I studies in healthy subjects and 1 phase II study in patients undergoing gastroscopy. Nonlinear mixed effects modeling was used in developing the population pharmacokinetics and pharmacodynamics (PopPK/PD) model of NH600001. Three-compartment model was used to describe the PK profile of NH600001. Parameters were used for allometric scaling on body weight, where the exponents were set to 0.75 for clearance and 1 for volumes. Co-administration of alfentanil hydrochloride influenced the distribution volume of the central compartment and clearance. Effect of patients undergoing gastroscopy (compared with healthy subjects) on clearance, the distribution volume of the superficial peripheral compartment and inter-compartmental clearance for deep peripheral compartment and central compartment was included the final PopPK model. The effect compartment model well characterized the PK/PD relationship of NH600001. Simulation results showed that an initial dose of 0.25 mg/kg of NH600001 resulted in rapid sedation, and three additional doses at 5-min intervals could maintain sedation for more than 20 min. A PopPK/PD model was successfully constructed for NH600001 in healthy subjects and in patients undergoing gastroscopy that could inform the dosing regimens of the forthcoming phase III study.

Characterizing and mitigating factors that impact product immunogenicity can aid in risk assessment and/or managing risk following manufacturing changes. For follow-on products that have the same indication, patient population, and active product ingredient, the residual immunogenicity risk resides predominantly on differences in product and process related impurities. Characterizing differences in innate immune modulating impurities (IIRMI), which could act as adjuvants by activating local antigen presenting cells (APCs), can inform the immunogenicity risk assessment potentially reducing the need for clinical trials. To date, assays to detect trace levels of IIRMI are being used to support regulatory decisions by FDA for selected synthetic peptide drug products that refer to reference listed drugs of rDNA origin but not recombinant protein or peptide products where more complex mixtures of trace impurities including host cell proteins are expected. Here we describe an exercise to explore whether or not there are differences in the innate immune response elicited by an insulin glargine (produced in E. coli) and its interchangeable biosimilar insulin (produced in P. pastoris) that could indicate differences in IIRMI. Our results suggest the two products elicit comparable innate immune responses as determined by the expression of 90 immune-related genes, including IL-1α, IL-1β, IL-6, CCL3, CCL2, and CXCL8. The data suggest that these assays can provide useful information when assessing recombinant proteins for the presence of IIRMI.

Optimizing the interaction between antibody (mAb)-based therapeutics and immune effector functions (EFs) offers opportunities to improve the therapeutic window of these molecules. However, the role of EFs in antibody-drug conjugate (ADC) efficacy and toxicity remains unknown, with limited studies that have investigated how modulation of EF affects the pharmacology of ADCs. This study aimed to evaluate the effect of EF modulation on ADC efficacy using trastuzumab-vc-MMAE as a model ADC. A series of ADCs with enhanced or eradicated EF were synthesized through Fc engineering of the antibody. Cell-based assays confirmed that the alteration of EFs in ADCs did not change their in vitro potency, and the conjugation of vc-MMAE did not alter the trends in EFs modulation. Pharmacokinetic/pharmacodynamic (PK/PD) studies of Fc engineered ADCs were conducted in a syngeneic mouse system. The enhancement of EFs led to lower systemic exposure, faster clearance, and potentially enhanced tissue distribution and accumulation of ADCs. ADCs with enhanced EFs demonstrated improved efficacy in the syngeneic mouse tumor model, which was quantitatively confirmed by PK/PD modeling. The model indicated that EF enhancement was synergistic for ADC efficacy, whereas the complete removal of EF was less than additive. Our study suggests that developing ADCs with enhanced EF may improve the therapeutic effectiveness of ADCs, although the effect of this modification on ADC safety and extrapolation of our findings to other ADCs necessitates further investigation.

Spectroscopy (UV-visible, circular dichroism, infrared, Raman, fluorescence, etc.) is of fundamental importance to determine the structures of macromolecules and monitor their stability, especially for drug products, based on proteins or nucleic acids. In their 2014 article, Dinh et al. proposed Weighted Spectral Difference (WSD) as a method to quantitatively compute the dissimilarity of a given spectrum to a reference one. Despite the various properties of this method, its lack of symmetry and dependence on the selection of a reference limits the range of possible applications. Here, we propose a reference-free, symmetrized version of WSD (SWSD) that allows the computation of a semi-distance between two spectra. SWSD can be applied to perform group comparisons, track spectral kinetics, or construct a SWSD matrix leading to the hierarchical clustering of spectra. This method was tested on circular dichroism spectra from a split-virus-based (influenza) vaccine and a recombinant spike protein (COVID-19 vaccine). This approach resulted, first, in a perfect clustering of influenza A and B viruses into two distinct clusters, and second, in the detection of the change of secondary structure of the spike protein during a heating experiment, identifying two main temperatures of denaturation (Tm) by SWSD kinetics, in agreement with results obtained by conventional DSC. In summary, we have shown that SWSD is a versatile and efficient tool for quantitative spectral comparison, tracking spectral kinetics and enabling relevant unsupervised classification.

Per FDA guidance, method comparability should be established if an anti-drug antibody (ADA) assay is run by two or more independent laboratories during a study. Genentech, Inc. is evaluating an immunogenicity risk-based comparability approach consisting of both technical and clinical aspects. Technical comparability of the relative sensitivity (RS) is assessed using the Two One-Sided T-tests (TOST) statistical analysis which evaluates if the difference (in absolute value) of the RS means of the two laboratories is less than a pre-specified level of comparability, the practically significant difference (PSD). Clinical comparability is based on the molecule's immunogenicity risk. A basic and in-depth assessment for low and high-risk molecules are used, respectively. An alternative strategy for molecules with limited incurred sample availability is to be used. In the basic assessment, samples are either unfortified or fortified with surrogate ADA positive control at method appropriate concentrations in a representative biological matrix. Acceptable comparability requires in both methods i) at least 80% of the unfortified samples screen and confirm negative, ii) at least 90% of the low concentration samples screen and confirm positive; and iii) 100% of the high concentration samples screen and confirm positive. The in-depth assessment uses at least 100 incurred samples from 30 or more ADA-positive and ADA-negative patients. The results are evaluated using a 2 by 2-confusion matrix and Cohen's Kappa score where 1 indicates perfect agreement. Acceptable comparability requires a Cohen's Kappa score of greater than 0.40. This strategy allows for a robust technical and clinical method comparability assessment.