搜索结果：ADMET & DMPK

Machine learning models for ADMET prediction benefit from large, diverse data sets, yet such data are typically siloed across organizations. Federated learning (FL) enables collaborative modeling while preserving data privacy. Here, we investigate a student-teacher model (STM) framework in which organizations train internal models on proprietary data and share predictions on a public data set to generate pseudolabels for a centralized student model. As a proof of concept, 11 pharmaceutical companies contributed predictions for rat steady-state volume of distribution, yielding a pseudolabeled data set of ∼133,000 compounds. The resulting student model achieved performance comparable to individual teacher models on an external test set (RMSE ≈ 0.51 vs 0.47-0.61). Compared with FL approaches such as MELLODY and Effiris, STM offers a simpler workflow that avoids direct data sharing or iterative collaboration, providing a practical and scalable framework for secure cross-company model development.

Targeted covalent inhibitors (TCIs) are low-molecular-weight drugs containing a reactive warhead to inactivate target proteins. In 2023, the IQ consortium DMPK Guidelines for Targeted Covalent Drugs Workgroup surveyed 23 IQ member companies to explore knowledge around this compound class. Areas deserving special consideration included human clearance prediction and modeling approaches to predict dose. Respondents highlighted the importance of achieving sufficient warhead reactivity to engage target, while avoiding excessive off-target binding. Stability assays with glutathione (GSH) were leveraged frequently, but data interpretation challenges were reported for more complex covalent binding assays; these are typically performed in the event of safety signals. Drug binding to endogenous proteins, while not necessarily a safety concern, may result in lower recovery of total radioactivity from human mass balance studies compared to non-TCI drugs. A comparison of drug safety profiles for TCI and non-TCI did not reveal any increased safety risks for TCIs.

Chirality is an important determinant of drug action, as enantiomers can exhibit markedly different pharmacological and toxicological profiles. Although the importance of stereochemistry in drug efficacy is well established, its role in drug metabolism and disposition remains comparatively underexplored, despite the inherently stereoselective nature of drug metabolizing enzymes. Given the high prevalence of chiral drugs in clinical use and among newly approved drugs, a systematic evaluation of stereoselective drug metabolism is needed. Understanding stereoselective biotransformations has important implications for predicting drug disposition and response and may also inspire novel biocatalytic and biomimetic strategies to address challenges in enantioselective synthesis of chiral active pharmaceutical ingredients and their metabolites. In this Systematic Review, we examine current trends and practices in the investigation of stereoselectivity in drug metabolism, the key factors influencing stereoselective metabolism, and the associated challenges and opportunities. We highlight how biocatalytic approaches can improve stereoselective access to chiral metabolites, and how insights from drug metabolism and pharmacokinetics (DMPK) studies can inspire the development of novel biocatalytic and biomimetic synthesis routes. Transfer of learning and cross‑disciplinary collaboration between biocatalysis and DMPK scientists will be critical for accelerating progress in these areas and for addressing shared challenges, including stereoselectivity prediction.

We designed and synthesized a series of novel 1,2,3,4-tetrahydroquinoxaline derivatives and evaluated their ability to increase nicotinamide adenine dinucleotide (NAD) levels in primary cortical neurons. Several compounds demonstrated nanomolar potency and enabled the establishment of clear structure-activity relationships (SAR), highlighting key substituents required for activity. Qualitative 3DSAR analysis further identified favorable steric, electrostatic, and hydrophobic features associated with NAD enhancement. Selected lead compounds were assessed for in vitro drug metabolism and pharmacokinetics (DMPK) properties, showing good cell permeability and species-dependent metabolic stability in liver microsomes, with improved stability in human systems compared with rodent systems. These findings identify tetrahydroquinoxalines as a promising class of neuronal NAD-boosting agents and provide a strong foundation for further optimization toward neuroprotective drug candidates.

Herein, we report the discovery and development of the first-in-class (FIC), selective, and centrally active metabotropic glutamate receptor subtype 3 (mGlu3) positive allosteric modulator (PAM), VU6053371/BI03738809. A high-throughput screening campaign identified a potent and selective mGlu3 PAM VU6048261/DI013166572 based on a tetra-substituted thiophene core but with poor DMPK properties. Chemical lead optimization efforts managed to dramatically improve protein binding and in vivo rat PK to afford VU6053371/BI03738809. With an FIC in vivo tool compound, VU6053371/BI03738809 demonstrated robust efficacy in rat novel object recognition (NOR) (minimum effective dose (MED) = 3 mg/kg PO) and a clear pharmacokinetic/pharmacodynamic (PK/PD) relationship (PD efficacy observed when free brain concentrations were at, or above, the rat mGlu3 EC50). Thus, selective activation of mGlu3 represents a novel mechanism to address the cognitive impairment associated with schizophrenia (CIAS) and other neurodegenerative diseases. Moreover, the discovery of VU6053371/BI03738809 completes the group II mGlu receptor toolkit of in vivo PAM and NAM probes for both mGlu2 and mGlu3.

Plasma stability assays are routinely applied in early drug discovery to evaluate enzymatic liability and to support lead optimization efforts. Although these assays are generally regarded as robust, the extent to which pre-analytical variables influence specific plasma hydrolase pathways has not been systematically examined. In this study, the impact of plasma anticoagulant selection on hydrolysis was investigated using procaine and pilocarpine as prototypical substrates of the serine hydrolase butyrylcholinesterase (BChE) and the calcium-dependent hydrolase paraoxonase 1 (PON1), respectively. Plasma stability was assessed in dipotassium ethylenediaminetetraacetic acid (K2-EDTA) and lithium heparin plasma collected from the same donors. Procaine exhibited comparable stability across both plasma matrices, consistent with BChE-mediated hydrolysis. In contrast, pilocarpine underwent substantial hydrolysis in lithium heparin plasma but appeared stable in K2-EDTA plasma. This effect is most consistent with calcium chelation by EDTA, as evidenced by complete suppression of PON1-mediated pilocarpine hydrolysis in lithium heparin plasma following exogenous EDTA supplementation. Collectively, these findings demonstrate that K2-EDTA anticoagulation can selectively mask calcium-dependent PON1-mediated plasma hydrolytic pathways, leading to underestimation of plasma lability for susceptible compounds. Anticoagulant choice therefore represents an underappreciated determinant in plasma stability assessment, with direct implications for mechanistic interpretation of plasma-mediated clearance pathways during early DMPK evaluation.

Bisphenol A and its structural analogues are ubiquitous environmental contaminants and potential endocrine disruptors, creating a need for mechanistically relevant descriptors that support early hazard assessment. This study asked whether lipophilicity indices derived from biomimetic chromatography better reflect baseline toxicity and membrane-relevant behaviour of bisphenols than commonly used in silico log P / log D descriptors. A set of 18 bisphenol derivatives was analysed using phosphatidylcholine- and sphingomyelin-functionalised stationary phases and a conventional C18 column to obtain chromatographic hydrophobicity indices, which were then compared with predicted log P / log D values and related to mechanistically diverse toxicity endpoints (in vitro cytotoxicity in mammalian cells, ex vivo cardiotoxicity assessed as vasodilation, and aquatic toxicity towards Daphnids). Biomimetic chromatographic indices showed consistently stronger and more coherent relationships with biological activity than theoretical descriptors. They also uniquely captured structural effects, such as positional isomerism, which were largely indistinguishable using theoretical lipophilicity indices. These findings support biomimetic chromatography as an early-tier IATA tool, providing membrane-relevant experimental indices linking bisphenol lipophilicity with baseline toxicity.

Impaired SUMOylation of the sarcoplasmic/endoplasmic reticulum Ca2+-ATPase (SERCA2a) is a key contributor to defective calcium cycling and contractile dysfunction in heart failure (HF). Although N106 was previously identified as a first-in-class small-molecule enhancer of SERCA2a SUMOylation, its poor metabolic stability and short half-life limited translational development. This study aimed to develop SC023, a second-generation analog with improved pharmacokinetic (PK) properties and therapeutic efficacy. Through structure-activity relationship (SAR) screening of 100 analogs, SC023 was identified as the lead candidate. SC023 demonstrated 1.5-fold higher in vitro SUMO E1 hydrolysis activity than N106 and dose-dependently enhanced SERCA2a SUMOylation, contractility, and calcium handling in isolated adult cardiomyocytes. SC023 exhibited significantly improved metabolic stability, with a 2.7-fold longer half-life in human hepatocytes and 14.4-fold longer oral half-life in mice compared with N106. In a murine transverse aortic constriction model, chronic oral administration of SC023 for one month significantly restored left ventricular systolic function and attenuated adverse remodeling. Mechanistically, SC023 targets the SUMO E1 enzyme to trigger intrinsic SERCA2a SUMOylation without altering SUMO-related regulatory enzymes. Importantly, safety profiling confirmed that SC023 exhibited reduced off-target activity, specifically lacking the adenosine A2A and serotonin 5-HT2B receptor inhibition observed with N106. SC023 is a potent, metabolically stable second-generation SERCA2a SUMOylation enhancer that overcomes the PK and safety limitations of N106. Sustained pharmacological enhancement of SERCA2a SUMOylation by SC023 represents a promising therapeutic strategy for restoring calcium homeostasis and cardiac function in HF.

TRPV4 is a polymodal, calcium-permeable channel broadly expressed and enriched in epithelia, where it integrates mechanical, osmotic, and chemical cues to regulate calcium signaling. Although TRPV4 antagonism has long been pursued therapeutically, only one antagonist has reached patients and it lacked efficacy, likely due to pharmacokinetic limitations. We describe a novel series of small-molecule TRPV4 antagonist discovered via high-throughput screening and optimized for potency, selectivity, and developability. The lead, compound 39, demonstrates favorable absorption and elimination supporting a low, predicted once-daily oral dose, with robust margins to off-target pharmacology in early safety studies. In vivo, compound 39 attenuates responses in a mechanistically relevant cough model, indicating target engagement and functional efficacy. These findings position the preclinical compound 39 as a differentiated TRPV4 antagonist with drug-like pharmacokinetics and an encouraging nonclinical safety profile.

Vutrisiran is an N-acetylgalactosamine (GalNAc)-conjugated small interfering RNA therapeutic approved for targeted hepatic delivery and long-acting gene silencing; however, detailed in vitro and in vivo metabolism data have not been published. In this study, a sensitive liquid chromatography coupled with high resolution mass spectrometry platform was established to systematically evaluate the metabolism and disposition of vutrisiran in rats after administration of a low, pharmacologically relevant dose (3 mg/kg). Vutrisiran exhibited high systemic metabolic stability, with the intact parent drug as the predominant species in plasma and urine. Tissue metabolite profiling revealed distinct organ-specific pathways, including hepatic GalNAc cleavage followed by slow 3'-exonuclease-mediated degradation, and a low-abundance but unique kidney-specific 5'-truncation of the sense strand (n-4). Renal excretion was the primary route for elimination of intact drug, whereas biliary excretion was responsible for clearance of extensively catabolized fragments. The overall excretion pattern was consistent with that reported for other GalNAc-conjugated oligonucleotides. These rat metabolic profiling data provide insight into the disposition of vutrisiran in humans and represent the first reported in vivo disposition characterization of vutrisiran. The liquid chromatography coupled with high resolution mass spectrometry platform developed in this study enabled highly sensitive metabolite profiling and identification. A semiquantitative approach based on mass spectrometry peak area integration was validated by demonstrating close numerical agreement with UV detection. This platform supports metabolite profiling in plasma and target tissues for pharmacokinetics/pharmacodynamics studies and rapid disposition characterization in animals and may serve as an alternative or pilot approach to inform the design and necessity of human radiolabeled mass-balance studies for oligonucleotide therapeutics. SIGNIFICANT STATEMENT: This work reports the first in vivo disposition assessment of vutrisiran using a sensitive liquid chromatography coupled with high resolution mass spectrometry platform for characterizing oligonucleotide metabolism and excretion at pharmacologically relevant doses. These findings advance the understanding of vutrisiran disposition and support the use of nonradiolabeled strategies for metabolite profiling and disposition evaluation of oligonucleotide therapeutics.

Dopamine and nicotinamide adenine dinucleotide (NADH) are key biomarkers associated with neurological and metabolic disorders. Developing rapid, low-cost, and portable detection platforms of these biomarkers is essential for a point-of-care diagnostic kit. In this work, we report a colorimetric sensing approach using paper-based microfluidic devices (μPADs) modified with graphene-supported palladium (G/Pd) and platinum (G/Pt) nanocatalysts to enhance detection performance. Monolayer G/Pd and G/Pt nanocomposites were synthesized via a hydrothermal method with precursor concentrations ranging from 0.1 to 10 mM. The catalytic behaviour and metal-graphene interactions were further investigated using spin-polarized density functional theory (DFT) calculation (PHASE/0). Microfluidic paper-based analytical devices (μPADs) were laser-printed on commercial filter paper and folded into 3D origami structures. Colorimetric responses were quantified using red, green, blue (RGB) and hue, saturation, value (HSV) analysis, where time-dependent Euclidean distance in RGB colour space was used to assess the reaction kinetics. DFT results indicate that Pd and Pt clusters preferentially adopt a top-site configuration on graphene, facilitating interfacial charge redistribution and enhancing catalytic activity experimentally. Catalyst-modified μPADs significantly improve reaction kinetics, reducing detection time by up to 3.7× for dopamine and 2.5× for NADH compared to unmodified devices. G/Pt (10 mM) exhibits the best overall performance, achieving limits of detection of 0.16 μM for dopamine and 0.195 μM for NADH with good linearity (R 2 = 0.91). G/Pd displays competitive sensitivity, particularly at lower precursor concentration. The findings highlight that optimizing catalyst morphology and interfacial electronic structure is more critical than minimizing activation energy for achieving high-performance colorimetric sensing. The resulting platform shows potential as a cost-effective and portable tool for the detection of clinically relevant biomarkers in point-of-care settings.

Cancer is one of the leading causes of death worldwide, failing to identify a complete cure. Liver cancer is the sixth most frequent cancer worldwide, and its cure is still not assured. Nanoparticles, especially the metal oxide nanoparticles, have been explored as anticancer agents in recent times. In an attempt to make the best use of waste, plantain peel, a byproduct of agriculture, was used to synthesize copper oxide nanoparticles. The plantain peel extract was evaluated for its chemical composition by GC-MS analysis, which revealed a predominant presence of tetratetracontane. The copper oxide nanoparticles were characterized by UV-visible spectrophotometry, dynamic light scattering, zeta potential, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDAX). Bio-inertness was assessed using an MTT assay of fibroblasts, a haemolysis assay, and zebrafish embryo analysis. The anticancer activity against HepG2 cells was estimated. The absorption peak was found at 402 nm, the hydrodynamic diameter was 323 nm, the zeta potential was +10.74 mV, and a band gap of 1.3 eV. The SEM images showed a size range of 54 to 85 nm with a chrysanthemum-petal-like morphology. EDAX showed the presence of Cu and O, and the XRD and FTIR peaks corroborated with that of CuO. The result showed that up to a dose of 50 μg mL-1, the nanoparticles did not induce any toxicity. Finally, the anticancer activity, evaluated using the HepG2 cell line, showed a dose-dependent cytotoxic effect with an IC50 of 26.20 μg mL-1. The outcome of this study suggested that the synthesized copper oxide nanoparticles can be used at controlled doses to kill cancer cells. Further studies are needed using other cancer cell lines and in vivo cancer models.

Enzymes are generally believed to evolve from promiscuous ancestors to more specialized descendants under some selection pressure related to their function. However, enzymes whose function depends on substrate promiscuity have not been studied. Here, we show that a group of highly diverse, xenobiotic-metabolizing enzymes, responsible for defense against a constantly changing battery of xenobiotic chemicals, evolved from highly thermostable ancestors. Thermostability declined in parallel with the accumulation of sequence diversity through evolution. The major lineages differed in their relative diversification, with the more stable lineage leading to greater extant sequence diversity. Thermostability was associated with a trend towards better sequestration of hydrophobic residues within the core of the protein and increased exposure of polar residues in solvent-accessible parts of the structure. Resurrected ancestral forms were active towards typical substrates and exhibited ligand-binding promiscuity comparable to, or greater than, their extant descendants. This work supports the hypothesis that robust ancestors facilitate evolutionary diversification and highlights features responsible for enhancing thermostability in a protein fold.

The Target-Mediated Drug Disposition (TMDD) model is an important framework in pharmacokinetics (PK) and pharmacodynamics (PD), providing insights into drug interactions with soluble and membrane-bound targets, particularly for monoclonal antibodies. This paper reviews TMDD modeling specifically focused on monoclonal antibodies targeting soluble ligands, synthesizing existing research and highlighting current advancements. By doing so, we aim to enhance understanding of the application and potential of TMDD modeling in predicting drug behavior and optimizing therapeutic outcomes for soluble targets.

Amides and trifluoromethyl groups are among the most widely used structural motifs in materials science, medicinal chemistry, and agrochemistry. In contrast, their direct combination as N-trifluoromethyl amides and the closely related N-trifluoromethyl carbamates and ureas has remained largely unexplored. This disconnect has primarily stemmed from the lack of synthetic methods and their unknown stabilities and physicochemical properties. Enabled by recently developed methodologies to synthesize N-trifluoromethyl carbonyl compounds, we systematically evaluated their aqueous stability and drug-relevant properties to assess their usefulness for compound optimization. All investigated N-trifluoromethyl derivatives display high aqueous stability at pH 7.4, including in human plasma, except for one N-trifluoromethyl carbamate series. N-Trifluoromethyl carbonyl motifs have a lipophilicity and Caco-2 permeability similar to their N-isopropyl analogues, while, in several cases, offering improved pharmacokinetic profiles. These findings establish N-trifluoromethyl carbonyl motifs as highly attractive functionalities, providing medicinal chemists with a framework for their incorporation into future drug-discovery programs.

The study presents a comprehensive evaluation of physiologically-based pharmacokinetic (PBPK) modeling for Proteolysis Targeting Chimeras (PROTACs), using ARV-110 (Bavdegalutamide) as a case example. We sought to develop a PBPK model that accurately predicts the human pharmacokinetics (PK) of ARV-110 and began with a bottom-up approach to predict ARV-110 PK in mice and rats using available ADME and physicochemical data. Owing to the observed in vitro-in vivo extrapolation (IVIVE) gaps in clearance, the published in vivo data was used for refinement, resulting in a middle-out PBPK model bridging this discrepancy. PBPK predictions were extrapolated to human and validated against observed clinical PK for single and multiple doses in healthy volunteers and cancer patients revealing IVIVE gaps for human clearance. Similar to rodents, a middle-out modeling approach was then used to refine the human PBPK prediction. This model effectively captured plasma drug concentration-time profiles reported for preclinical and clinical studies, including studies involving impact of food and drug-drug interactions with itraconazole and esomeprazole. All observed human concentrations were within 5th and 95th percentile of predictions and PK parameters were within two-fold of the observed in vivo data. Following administration of a single dose (280 mg) of ARV-110, the observed vs. predicted AUC0-inf for high fat, medium fat and low fat studies were 13563.0 vs. 7646.0 ng.h/ml, 4358.0 vs. 4618.3 ng.h/ml and 1919.0 vs. 1403.3 ng.h/ml. This work provides a translational PBPK framework for predicting human oral PK of PROTACs and emphasizes challenges in generating robust preclinical data to enhance prediction accuracy.

Inhibition of drug-metabolizing enzymes such as P450s and uridine 5'-diphosphoglucuronosyltransferase is routinely evaluated in drug discovery and development. Substantial efforts have been made over the years to standardize in vitro assay conditions and data interpretation. More recently, increasing importance has been given to the approaches for improving translation of in vitro data to predict in vivo outcomes. The International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) Enzyme Inhibition Working Group conducted a survey across IQ member companies to interrogate on the current state of inhibition assessment in the industry, including the strategies used as compounds progress through the pipeline, the kinetic endpoints utilized, and the accuracy of clinical drug-drug interaction predictions. Focus was also placed on how companies applied correction for unbound fraction of potential inhibitors as required by the various recent regulatory guidance documents. Results showed that most companies follow similar set-ups to identify strong inhibitors in discovery and to fully characterize drug candidates in development. Although there are some minor differences in evaluating and correcting for incubational binding, there is almost universal alignment regarding the use of kinetic endpoints with Ki = IC50/2 widely accepted to determine the inhibition constant. A majority of predictions align with clinical drug-drug interaction results, although instances of over- or underprediction were reported, and examples of these are discussed here as case studies. SIGNIFICANCE STATEMENT: Practices utilized to assess reversible inhibition of drug-metabolizing enzymes were evaluated based on 25 survey responses from IQ member companies. Results show how assay conditions, endpoints, and modeling approaches evolve as compounds advance through discovery to development. The accuracy of drug-drug interaction prediction is discussed, and recommendations for best practices are provided.

Neurodegenerative diseases such as Alzheimer's, Parkinson's, and Huntington's disease are characterized by a progressive loss of neuronal function and loss of synaptic capacity. Physical exercise (PE) is one of the non-clinical techniques for the management of brain health and neurodegeneration. PE enhances the body's metabolic functions through cellular and molecular changes. It trades off metabolic functions, energy expenditure, and signalling processes to ensure physiological homeostasis and defence against disease. Exercise produces cascades, at the molecular level, including neurotrophic signalling, similar to those generated by drugs. It increases the levels of the brain-derived neurotrophic factor (BDNF), insulin-like growth factor 1 (IGF-1), and vascular endothelial growth factor (VEGF). These elements favour the growth of new neurons, vascular enlargement, and synaptic plasticity. PE also induces microglial cells to attain a neuroprotective, anti-inflammatory phenotype, reduces detrimental cytokines, promotes cellular clearance through autophagy, restores neurotransmitter homogenisation, and induces hippocampal cell formation. Collectively, it acts as a powerful modulator of health and brain activity. The aggregate processes enhance neuronal vulnerability to harm, aid cognitive functioning, and ensure the stability of neural networks. PE is an exciting additive therapy for preventing and treating various neurodegenerative disorders by orchestrating a diverse array of cellular and molecular responses.

Therapeutic peptides offer high potency but are limited by rapid degradation, poor bioavailability, and the need for frequent dosing. Poly(lactic-co-glycolic acid) (PLGA) nanoparticles and microparticles are effective carriers that protect peptides and enable controlled release. This review summarizes the mechanisms governing peptide release from PLGA particles and identifies formulation factors critical for optimizing therapeutic performance. A comprehensive analysis of polymer characteristics, particle design parameters, peptide physicochemical properties, and formulation strategies was conducted using data from recent studies. Release mechanisms, including diffusion, polymer degradation, and erosion, were examined alongside manufacturing methods. The review also evaluates clinical PLGA-based peptide products to highlight translational relevance. Peptide release profiles are strongly influenced by PLGA molecular weight, lactide:glycolide ratio, particle size, end-group chemistry, drug loading, and excipients. Lower polymer molecular weight, higher glycolide content, and smaller particle dimensions accelerate release, whereas cationic peptides experience electrostatic retention within degrading matrices. Additives such as PEG, magnesium salts, and chitosan coatings effectively modulate burst release and stability. PLGA systems typically display triphasic release profiles governed by diffusion and erosion. Several PLGA microparticle-based peptide depots have achieved clinical success, although no nanoparticle-based products have yet reached the market due to manufacturing and regulatory challenges. PLGA nano- and microparticles provide versatile, tunable platforms for sustained peptide delivery. Understanding the interplay between polymer properties, particle architecture, and peptide characteristics is essential for designing next-generation long-acting formulations with improved efficacy and clinical translation.