Bietti crystalline dystrophy (BCD) is a hereditary retinal disease caused by loss-of-function mutations in the CYP4V2 gene. Gene replacement therapy using rAAV-hCYP4V2 represents a promising therapeutic strategy, requiring robust bioassays for product quality control. This study developed and validated a sensitive LC-MS/MS method for quantifying CYP4V2 enzyme activity. Lysates from HeLa-AAVR cells transduced with rAAV-hCYP4V2 (MOI = 3 × 105) were used, with lauric acid as substrate supplemented with cytochrome P450 reductase, cytochrome b5, and NADPH. The ω-hydroxylated product (12-hydroxy lauric acid) was quantified using tolbutamide as an internal standard. Method validation followed ICH guidelines. Results demonstrated excellent specificity with negligible background in negative controls. Linearity was achieved over 0.5-100 ng/mL (R2 > 0.99), with an average recovery of 100.6%. Intra-batch and inter-batch precision RSDs were <47.8% and <28.4%, respectively. Product stability was maintained for ≥4 weeks at -80°C. The method was successfully applied to three AAV serotypes (AAV2, AAV8, and AAV2/8), with all RSDs < 23.9%. This validated LC-MS/MS bioassay provides a crucial quality control tool for potency assessment, process development, batch release, and stability studies of rAAV-hCYP4V2 gene therapy products.

Levodopa remains the cornerstone of symptomatic treatment in Parkinson's disease, providing substantial motor benefit and improved quality of life. While epidemiological studies have suggested improved survival in the modern levodopa era compared with the pre-levodopa era, these observations derive primarily from observational cohorts rather than randomized trials. Yet many patients experience severe functional decline after 5-10 years, a paradox that challenges the reputation of our most potent therapy. Similar divergences between early symptomatic benefit and adverse long-term outcomes have been observed in other areas of medicine. For example, positive inotropic agents such as milrinone improved short-term exercise tolerance in heart failure but were later associated with increased mortality in long-term trials. Antiarrhythmic agents encainide and flecainide effectively suppressed ventricular arrhythmias yet increased mortality in the Cardiac Arrhythmia Suppression Trial (CAST). In diabetes, intensive glucose lowering strategies improved metabolic control but increased cardiovascular mortality in the ACCORD trial, and earlier studies of tolbutamide in the University Group Diabetes Program (UGDP) also suggested excess cardiovascular deaths despite improved glycemic control. These examples illustrate how therapies with clear short-term physiological benefits may reveal unanticipated risks when evaluated over longer time horizons. Similarly, the long-term use of levodopa may introduce a cumulative burden of complications that may independently accelerate decline. We propose the conceptual framework of levodopa-accelerated frailty as a testable hypothesis to explore this possibility. This framework synthesizes evidence across seven pathways that may interact or overlap in contributing to frailty: dyskinesia, psychosis, orthostatic hypotension, weight loss, impulse control disorders, sleep disturbances, and elevated homocysteine. Each complication has been associated with increased risks of dementia, hospitalization, falls, or mortality in observational studies, with reported hazard ratios generally ranging from approximately 1.5 to over 6. Together, they form a synergistic web of decline that may transform a highly effective symptomatic therapy into a contributor to late-stage vulnerability. This hypothesis reframes a potential therapeutic paradox: a treatment that improves early symptomatic outcomes may also interact with mechanisms that contribute to frailty later in the disease course. The clinical implication is not levodopa phobia, but a healthspan-preservation strategy focused on minimizing cumulative iatrogenic burden. This involves adhering to the lowest effective dose, continuous reassessment, and integration with exercise, nutrition, and adjunctive therapies. Recognizing this potential pattern of levodopa-accelerated frailty may help reconcile the discrepancy between early symptomatic success and the later emergence of vulnerability. We emphasize that this model is a hypothesis and call for long-term, prospective studies to test whether cumulative levodopa exposure contributes to frailty and reduced healthspan.

Microscale affinity chromatography (μAC) was used with covalent protein immobilization and zonal elution to quickly screen and compare binding by several sulfonylurea-based antidiabetic drugs with human serum albumin (HSA) and forms of this protein containing advanced glycation end-products (AGEs). The HSA was modified with glyoxal or methylglyoxal and examined for its binding to the following drugs: acetohexamide, chlorpropamide, gliclazide, glipizide, tolbutamide, and tolazamide. The HSA was coupled by the Schiff base method onto HPLC-grade silica, which was then placed into 10 mm × 2.1 mm i.d. affinity microcolumns. These microcolumns each contained ∼1 mg HSA and could be used for over 450-500 sample injections. The drugs were injected onto these microcolumns at 37 °C and pH 7.4, giving retention data at 0.50 mL/min within a few minutes (e.g., less than 5 min for normal HSA). The overall binding constants obtained for normal and AGE-modified HSA were consistent with the literature, showing a strong correlation with prior values estimated when using immunoaffinity chromatography and the biospecific adsorption of HSA. These results indicated that μAC combined with zonal elution screening and Schiff base immobilization was an effective approach for studying the interactions of sulfonylurea drugs with HSA and modified forms of this protein. This approach can be extended to other proteins and drug-protein interactions, as could be used for fundamental research or aid in the development of new treatments through personalized medicine.

This review evaluates the available pharmacokinetic data on the plasma-to-breastmilk transfer of first- and second-line T2DM drugs against available clinical guideline recommendations. A list of drug therapies for treating T2DM was generated from national and international clinical guidelines. A systematic search of research articles reporting human plasma and breastmilk drug concentrations was conducted in Scopus, PubMed, Google Scholar, and LactMed® in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies evaluating breastmilk drug transfer in T2DM, with fully accessible abstract and main text reported in English, were included. Study quality was evaluated using the ClinPK checklist. Authors evaluated clinical guideline recommendations on the use of T2DM drugs in lactation and the basis upon which such recommendations were made. Only 5 out of 20 drugs (metformin, glyburide, glipizide, tolbutamide, and semaglutide) have clinical data on plasma-to-breastmilk transfer. Metformin and tolbutamide were detectable in maternal plasma and breastmilk. Half (51.7%) of guideline recommendations provide explicit guidance. Only 4.4% of recommendations were based on clinical evidence. Over half (57.8%) of recommendations were accessible online, and most guideline recommendations (78%) were against the use of antiglycemic agents while breastfeeding. The scarce clinical evidence to guide T2DM drug therapy during breastfeeding available has several design and methodological limitations. Published recommendations remain largely inconsistent, thus perpetuating uncertainty in the use of T2DM drug therapies in lactation. Addressing knowledge gaps is critical in developing clinical consensus to optimize T2DM drug therapy among breastfeeding mothers.

Sulfonylureas are hypoglycemic agents used in type 2 diabetes mellitus, although their low water solubility implies high therapeutic doses. Inclusion complexes with β-cyclodextrin (β-CD), a cyclic oligosaccharide featuring a hydrophobic interior and hydrophilic exterior, offer a supramolecular polymer capable of encapsulating drugs, improving solubility and stability. We explore how substituent size and interaction type influence the stability of β-CD complexes with p-toluenesulfonylurea, tolbutamide, and tolazamide. Using molecular dynamics simulations, clustering analysis, and quantum chemistry calculations at the M06-2X-D3/ACP-6-31G(d) + SMD level of theory, we identified the most stable binding modes. Boltzmann populations of complexes revealed a single dominant conformation for p-toluenesulfonylurea (∼97%), two major coexisting conformations for tolbutamide (75/25%), and two near-equal conformations for tolazamide (56/43%). Predominant conformations adopted by guest molecules are in line with experimental reports. Binding free energies, determined via molecular mechanics Poisson-Boltzmann surface area analysis, for p-toluensulfonylurea, tolbutamide and tolazamide in β-CD inclusion complexes, averaged -10.75, -13.42, and -12.84 kcal mol[-1], respectively. Interaction energies increased with bulkier substituents, though this was partially offset by higher deformation costs. Analyses of ρ(r) showed that stabilization arises from networks of spatially distributed weak interactions rather than from strong directional intermolecular hydrogen bonds. These findings offer a detailed view of β-CD host-guest recognition within a carrier context, guiding the design of β-cyclodextrin-based systems to improve the formulation, stability, and therapeutic effectiveness of drugs in type 2 diabetes mellitus.

Efavirenz's effects on cytochrome P450 2C9 (CYP2C9) activity have not been formally characterized in vivo. We conducted the first clinical drug-drug interaction (DDI) study to test the effect of chronic efavirenz dosing on CYP2C9 activity, using tolbutamide as a selective probe. Healthy participants received a single oral dose of tolbutamide (250 mg) with a single 600 mg dose of efavirenz (SD) before and after 600 mg daily efavirenz for 17 days (MD). Tolbutamide, efavirenz, and their metabolites were quantified in plasma and urine samples by LC-MS/MS method. Participants were genotyped for CYP2C9*2 and *3 and for CYP2B6*4, *9, and *18. Pharmacokinetic data were valid for 71 and 59 participants for SD- and MD groups, respectively. MD efavirenz caused more than 50% increase in median tolbutamide AUC0-∞ and C24 in all subjects, and 1.42-1.46-fold increase in the paired analysis (p < 0.0001); tolbutamide/metabolite ratios were also increased (p < 0.001), while tolbutamide's CL/F/kg, metabolite formation clearance, and metabolite Cmax were significantly reduced. CYP2C9 genetic variants were associated with reduced tolbutamide elimination compared to *1/*1 and *1/*2 (slowest, *3/*3; and intermediate, *1/*3, *2/*2, and *2/*3). The lowest percent change occurred in *2/*2 and *3/*3 genotypes, though small sample sizes limited reliable assessment of genotype-specific DDI effects. In conclusion, chronic efavirenz use inhibits CYP2C9 activity in vivo. This inhibition may increase the risk of adverse effects from narrow-therapeutic-index CYP2C9 substrates (e.g., warfarin, phenytoin, and sulfonylureas). Therefore, therapeutic drug monitoring and dose adjustments are warranted when efavirenz is co-administered with these medications.

Myeloid cell leukemia-1 (Mcl-1), an anti-apoptotic member of the Bcl-2 family, is frequently overexpressed and amplified in chronic myeloid leukemia (CML) as well as in several other malignancies, contributing to tumor progression and therapeutic resistance. The present study employed a multi-step virtual screening approach to identify potential inhibitors of the Mcl-1 protein and subsequently validated their inhibitory activity through computational approaches. The 3-D structure of Mcl-1 protein was retrieved from the protein data bank and subjected to structure-based virtual screening. A series of drug-likeness and ADMET filters, including Lipinski filter, Swiss ADME, ADME-Tox, pKCSM and Protox-3 web, were applied to prioritize the compounds with favorable pharmacokinetic and toxicity profile. Further evaluated by molecular docking, with particular emphasis on -CDOCKER interaction energy, identified tolbutamide (-101.09 kcal/mol), leucodelphinidin (-89.304 kcal/mol), and gossypetin -70.49 (kcal/mol) as, most promising candidates. To assess the conformational stability and dynamic behavior of the protein-ligand complexes, molecular dynamics simulation was performed for 100ns and extended to 500 ns for the best screened compound. Trajectory analysis was conducted using multiple descriptors, including root mean square deviation, root mean square fluctuation, the radius of gyration, solvent-accessible surface area (SASA), hydrogen bonds, and free energy landscape. In vitro toxicity studies using the MTT assay on the K562 chronic myeloid leukemia cell line demonstrated a significant reduction in cell viability, indicating potent antiproliferative activity. These computational studies highlight novel compounds as potent Mcl-1 inhibitors, suggesting their potential as promising therapeutic candidates for the treatment of CML. These findings lay the foundation for further optimization and preclinical evaluation of Mcl-1 targeted compounds in cancer therapy.

Drug clearance and drug-drug interactions (DDIs) are important in the pharmacokinetic assessment of investigational drugs, yet predicting in vivo fraction metabolized (fm) and DDI intensity remains challenging, particularly for low-clearance compounds. This study demonstrates how human liver chimeric mice (hu-PXB mice) can predict CYP2C9-mediated drug disposition for low-clearance compounds in humans. To estimate human in vitro CYP2C9 fraction metabolized (fm,CYP2C9,in vitro), 3 CYP2C9 substrates (phenytoin, tolbutamide, and warfarin) were incubated in human hepatocytes with or without sulfaphenazole (CYP2C9 inhibitor). The fm,CYP2C9,in vitro was calculated based on hepatic intrinsic clearance. For in vivo estimation (fm,CYP2C9,in vivo), clinical DDI data obtained using CYP2C9 inhibitors were analyzed to calculate fm,CYP2C9,in vivo based on observed clearance changes. To evaluate human DDI predictability, the 3 drugs were administered intravenously to hu-PXB and SCID mice with or without CYP2C9 inhibitors (sulfaphenazole or tienilic acid). Clearance changes were calculated and compared among humans, hu-PXB mice, and SCID mice. Results showed that fm,CYP2C9,in vitro values for phenytoin and tolbutamide were overestimated compared to fm,CYP2C9,in vivo, whereas warfarin could not be evaluated under current conditions. Hu-PXB mice demonstrated a better correlation with humans in both clearance changes and absolute values compared to SCID mice. Notably, hu-PXB mice predicted CYP2C9-mediated DDI magnitude within 15% of clinical values and predicted clearance for CYP2C9 substrates within 2-fold of clinical values. These findings establish hu-PXB mice as a reliable preclinical model for predicting human CYP2C9-mediated drug disposition. SIGNIFICANCE STATEMENT: Human liver chimeric mice can accurately predict the clearance and magnitude of drug-drug interaction for CYP2C9 substrate drugs. Findings from humanized mice enable the selection of better candidates in drug discovery and facilitate the design of efficient clinical trials for investigational drugs.

Tolbutamide is metabolized by cytochrome P450 2C9 into 4-hydroxytolbutamide (4-OH TB), which retains pharmacological activity. 4-OH TB is further oxidized to the inactive metabolite 4-carboxytolbutamide, likely via the intermediate tolbutamide aldehyde (4-CHO TB). Because the conversion of 4-OH TB to 4-CHO TB is considered the rate-limiting step, the enzyme(s) catalyzing this reaction may play a crucial role in determining drug efficacy. We aimed to identify the enzyme(s) responsible for this process in the human liver. 4-CHO TB was formed from 4-OH TB in human liver cytosol (HLC) in the presence of nicotinamide-adenine dinucleotide (NAD+). The relative activity factor approach revealed that this reaction was primarily attributed to alcohol dehydrogenase 4 (ADH4). Interestingly, 4-CHO TB was also formed in HLC in the presence of nicotinamide-adenine dinucleotide phosphate (NADP+), with a 1.6-fold higher intrinsic clearance than that of NAD+. Untargeted proteomic analysis revealed a significant correlation between aldo-keto reductase 1A1 (AKR1A1) protein levels and NADP+-dependent 4-CHO TB formation in 15 HLC samples (r = 0.627, P < .05). Recombinant AKR1A1 effectively catalyzed this reaction, contributing 92% of NADP+-dependent 4-CHO TB formation in HLC. Based on hepatic NAD+ and NADP+ concentrations and the expression levels of ADH4 and AKR1A1, AKR1A1 was estimated to contribute one-third of ADH4 to 4-CHO TB formation in the human liver. In conclusion, we demonstrated that ADH4 and AKR1A1 jointly mediate the oxidation of 4-OH TB to 4-CHO TB in the human liver, highlighting the novel role of AKR1A1 as an oxidase in drug metabolism. SIGNIFICANCE STATEMENT: This study identifies aldo-keto reductase 1A1 as a novel enzyme involved in the oxidation of 4-hydroxytolbutamide in the human liver. Alongside alcohol dehydrogenase 4, aldo-keto reductase 1A1 contributes to NADP+-dependent aldehyde formation, suggesting a previously unrecognized role in drug metabolism and variability in tolbutamide clearance.

ATP-sensitive potassium (KATP) channels composed of Kir6.2 and sulfonylurea receptor 1 (SUR1) couple glucose metabolism with insulin secretion in pancreatic β-cells. Loss-of-function mutations in the large regulatory SUR1 subunit encoded by ABCC8 are the most common causes of severe persistent hypoglycemia in infants and children seen in the rare disease congenital hyperinsulinism. The N-terminal transmembrane domain, TMD0, and the linker immediately C-terminal to TMD0, L0, of SUR1 (TMD0/L0) forms direct contact with Kir6.2 in KATP channels. Mutations in SUR1-TMD0/L0 often impair KATP channel trafficking to the plasma membrane, causing severe disease unresponsive to treatment by the KATP activator diazoxide; however, surface expression and function of many such mutant channels can be rescued by reversible KATP inhibitor pharmacochaperones. Here, we identified seven new SUR1 missense mutations in TMD0/L0 from hyperinsulinism patients unresponsive to diazoxide and investigated their effects on KATP channel expression, function, and response to pharmacochaperones. All seven mutations, N32K, Y124F, P133R, W143R, L171P, G228D, and Y230C, reduced channel function in Rb[+] efflux assays. Further characterization by immunoblotting, immunostaining and electrophysiology revealed that Y124F primarily causes defective channel gating, while the others impair channel trafficking to different extents. The trafficking mutations showed varied response to surface expression and function rescue by the reversible KATP inhibitor pharmacochaperones, tolbutamide, and Aekatperone. The study underscores the critical role of SUR1-TMD0/L0 in KATP expression and gating. It further highlights the importance of detailed biochemical and functional studies of mutant channels in understanding their pathogenic roles and response to potential pharmacological therapies.

Direct mechanocatalysis has arisen as a promising tool to achieve synthetic transformations by utilizing reaction vessels and/or media made of a material capable of acting as a source of catalysis. One common metal utilized for this purpose is copper, the surface of which is not a static environment but rather undergoes many transformations (particularly upon exposure to water and oxygen). Here we have utilized in-house developed equipment for work under controlled atmosphere milling, including a composite milling jar design that enables investigating the behaviour of the copper surface in either impact- or shear-dominated milling regimes. We exploit the unique sensitivity to Cu(ii) species of the mechanocatalytic coupling of isocyanate and sulfonamide to form the sulfonylurea diabetic drug tolbutamide to establish methods to control the copper surface composition and reveal the factors that influence copper transformation into different states during milling. We reveal the active catalyst formed through direct mechanocatalysis to be a hydroxylated copper species and demonstrate that the reaction proceeds via surface wear and subsequent catalyst formation. Any initial surface oxide is observed to be insignificant to the overall process. The use of the composite reaction jar further revealed that wear dominates from the end regions of the vessel, undergoing primarily impact forces. Based on these finding and density functional theory (DFT) calculations, we present a reaction mechanism which explains the different yields of in situ generated Cu(OH)2 and a traditional CuCl2 pre-catalyst. These results highlight the importance of systematic investigations of surface characteristics for understanding and controlling direct mechanocatalysis and demonstrate methods to realize these goals.

Background/Objectives: Hepatic clearance is important in determining clinical drug administration strategies. Achieving accurate hepatic clearance predictions through in vitro-to-in vivo extrapolation (IVIVE) relies on appropriate model selection, which is a critical step. Although numerous models have been developed to estimate drug dosage, some may fail to predict liver drug clearance owing to inappropriate hepatic clearance models during IVIVE. To address this limitation, an in silico-based model selection approach for optimizing hepatic clearance predictions was introduced in a previous study. The current study extends this strategy by verifying the accuracy of the selected models using ex situ experimental data, particularly for drugs whose model choices are influenced by protein binding. Methods: Commonly prescribed drugs were classified according to their hepatic extraction ratios and protein-binding properties. Building on previous studies that employed multinomial logistic regression analysis for model selection, a three-phase classification method was implemented to identify five representative drugs: diazepam, diclofenac, rosuvastatin, fluoxetine, and tolbutamide. Subsequently, an isolated perfused rat liver (IPRL) system was used to evaluate the accuracy of the in silico method. Results: As the unbound fraction increased for diazepam and diclofenac, the most suitable predictive model shifted from the initially preferred well-stirred model (WSM) to the modified well-stirred model (MWSM). For rosuvastatin, the MWSM provided a more accurate prediction. These three capacity-limited, binding-sensitive drugs conformed to the outcomes predicted by the multinomial logistic regression analysis. Fluoxetine was best described by the WSM, which is consistent with its flow-limited classification. For tolbutamide, a representative capacity-limited, binding-insensitive drug, no significant differences were observed among the various models. Conclusions: These findings demonstrate the accuracy of an in silico-based model selection approach for predicting liver metabolism and highlight its potential for guiding dosage adjustments. Furthermore, the IPRL system serves as a practical tool for validating the accuracy of the results derived from this approach.