Mefenamic Acid

Vericiguat (Verquvo; US: Merck, other countries: Bayer) is a novel drug for the treatment of chronic heart failure. Preclinical studies have demonstrated that the primary route of metabolism for vericiguat is glucuronidation, mainly catalyzed by uridine diphosphate‐glucuronosyltransferase (UGT)1A9 and to a lesser extent UGT1A1. Whereas a drug–drug interaction (DDI) study of the UGT1A9 inhibitor mefenamic acid showed a 20% exposure increase, the effect of UGT1A1 inhibitors has not been assessed clinically. This modeling study describes a physiologically‐based pharmacokinetic (PBPK) approach to complement the clinical DDI liability assessment and support prescription labeling. A PBPK model of vericiguat was developed based on in vitro and clinical data, verified against data from the mefenamic acid DDI study, and applied to assess the UGT1A1 DDI liability by running an in silico DDI study with the UGT1A1 inhibitor atazanavir. A minor effect with an area under the plasma concentration‐time curve (AUC) ratio of 1.12 and a peak plasma concentration ratio of 1.04 was predicted, which indicates that there is no clinically relevant DDI interaction anticipated. Additionally, the effect of potential genetic polymorphisms of UGT1A1 and UGT1A9 was evaluated, which showed that an average modest increase of up to 1.7‐fold in AUC may be expected in the case of concomitantly reduced UGT1A1 and UGT1A9 activity for subpopulations expressing non‐wild‐type variants for both isoforms. This study is a first cornerstone to qualify the PK‐Sim platform for use of UGT‐mediated DDI predictions, including PBPK models of perpetrators, such as mefenamic acid and atazanavir, and sensitive UGT substrates, such as dapagliflozin and raltegravir.

Although NSAIDs possess notable therapeutic and pharmaceutical qualities, it's essential to acknowledge that excessive doses can result in toxicity within the human body. Moreover, the importance lies in identifying and measuring their trace amounts. Due to their existence within intricate matrices, the creation of novel electrospun nanofibers as sorbents for electrically-assisted solidphase microextraction (EA-SPME) becomes vital. This innovation caters to the requirement for the effective pre-treatment of NSAID samples, providing a strategic approach to managing the complexities associated with trace quantities found in various matrices.

First, polyvinylalcohol/casein/tannic acid/polyaniline/titanium dioxide nanoparticles (PVA/CAS/TA/PANI/TiO₂ NPs) electrospun nanofibers were prepared for EA-SPME on pewter rode and then, trace amounts of six NSAIDs (Acetaminophen, Caffeine, Naproxen, Celecoxib, Ibuprofen and mefenamic acid) were adsorbed chemically on these nanofibers. In the next step, the desorption of six NSAIDs was electrochemically done from prepared electrospun nanofibers on a pewter rod which was as working electrode at three electrodes system. Finally, these drugs were quantified from different human plasma samples with HPLC-UV. The synthesis of electrospun nanofibers was confirmed through a series of analytical techniques including field emission-scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy with elemental mapping analysis (EDX-Mapping), X-ray diffraction (XRD), and Fourier transform-infrared (FT-IR). The optimal percentage of additive compounds to PVA/CAS for electrospinning, as well as the factors influencing adsorption and desorption processes, were determined through both of Design Expert software and MATLAB programming language.

Under optimum conditions, the wide linear range was 27-8000 ng mL^-1 with R²≥ 0.9897, low detection limits were ranged from 8 to 27.3 ng mL^-1 based on S/N = 3 and significant enrichment factors were acquired. The intra-day and inter-day RSDs% were obtained within the 4.51% - 5.68% and 4.28%-5.45%, respectively. Finally, The effectiveness of the EA-SPME-HPLC-UV method was assessed for determining NSAIDs in plasma samples, demonstrating good recoveries ranging from 90.2% to 105.2%.