The development of dissolving polymeric microneedles (DPMNs) loaded with drug nanocrystals is an innovative and minimally invasive approach for localized drug administration. In this work, benzocaine, a short-acting local anesthetic, was formulated into nanocrystals (BZ-NCs) and subsequently incorporated into polymeric microneedles. Several formulations of BZ-NCs were formulated via nanoprecipitation technique, utilizing ethanol as a solvent and varying aqueous concentrations of sodium lauryl sulfate (SLS), Polysorbate 80, or Poloxamer 188 as the antisolvent. The optimized formulation of BZ-NCs, which was developed utilizing 0.5% w/v SLS in the antisolvent phase, was assessed employing attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), powder X-ray diffraction (PXRD), and differential scanning calorimetry (DSC). Moreover, the dissolution behavior of BZ-NCs was compared to that of plain benzocaine (BZ). DPMNs loaded with the optimized BZ-NCs formulation were prepared by mixing 25% w/w polyvinyl alcohol (PVA) and 35% w/w polyvinyl pyrrolidone (PVP) at ratios of 1:3, 1:2, or 1:1, respectively. The favorable formulation (1:1) was selected for further evaluation, including dissolution, accelerated stability, histological assessment and dermatokinetic analysis. The optimized nanocrystal formulation (BZ-NCs-3), exhibited a particle size of 291.12 ± 15.31 nm with polydispersity index and zeta potential of 0.261 ± 0.090 and -32.27 ± 1.04, respectively. ATR-FTIR confirmed the chemical structure integrity of benzocaine in BZ-NCs-3, while PXRD and DSC revealed its crystalline nature. Moreover, the dissolution of BZ-NCs-3 was significantly enhanced at pH 5.5 and 7.4 compared to BZ. The optimal microneedle formulation (BZNCs-MN3), having the highest PVA content, demonstrated effective penetration in excised human skin reaching a depth of 394.19 ± 20.402 µm, dissolved within 25 min and showed no significant changes in benzocaine content after accelerated storage. According to the dermatokinetic analysis, delayed and superior deposition of benzocaine in the epidermis and dermis were recorded following the application of BZNCs-MN3. This platform provides promise for improving local anesthesia with higher distribution of benzocaine in skin layers.

In the field of medicinal chemistry, the design of small molecules is acknowledged as an effective strategy. This study may contribute to the global fight against inflammatory diseases by focusing on the synthesis of novel α-aminophosphonate derivatives incorporating para-aminobenzoic acid (PABA) and benzocaine moieties and evaluating their anti-inflammatory and antioxidant activities. Compounds 1a-1i, 2a-2g and 3a-3f were efficiently prepared via a one-pot Kabachnik-Fields reaction in moderate to high yields. Structural characterization was achieved using spectroscopic techniques and single-crystal X-ray diffraction. Antioxidant activity, assessed by ABTS (<0.1 mM) and phenanthroline (<0.5 mM) assays, revealed that several derivatives exhibited significant radical scavenging and reducing power, particularly those bearing electron-donating groups. In vitro anti-inflammatory evaluation using the bovine serum albumin denaturation assay identified compounds 1f, 3f, 2g and 1i as the most active derivatives, with compound 1f (97.63% ± 0.99%) showing activity comparable to that of diclofenac (98.70% ± 0.15%). Toxicity tests on Tenebrio molitor larvae indicated low toxicity at effective concentrations. Compound 1f was only moderately toxic (50% of mortality rate) at the highest concentration tested (4 mM), and no mortality was observed at lower doses. DFT calculations provided insights into the electronic and physicochemical properties of the synthesized compounds. Molecular docking and molecular dynamics simulations generated hypotheses regarding their possible interactions with the COX-2 binding site, while ADMET analyses predicted the potentially acceptable pharmacokinetic profiles of several derivatives. However, these computational findings do not demonstrate direct COX-2 inhibition, target engagement, or selectivity. When considered alongside the preliminary experimental results, they support prioritizing compound 1f for further experimental evaluation.

Predicting the solubility of active pharmaceutical ingredients (APIs) in binary aqueous-organic mixtures is critical for formulation design, yet remains challenging. Physics-based models such as COSMO-RS provide a solid theoretical foundation but often struggle with non-ideal mixing behavior in complex systems. This study asks a practical question: when does machine learning actually add value beyond established theory? We compared COSMO-RS with DOOIT2 (Dual-Objective Optimization with Iterative Feature Pruning), a hybrid COSMO-RS/machine-learning correction workflow, across two complementary datasets: 85 structurally diverse APIs and related formulation-relevant compounds (10,140 data points) and 37 acid-centered solutes (6030 data points). The datasets also incorporate newly measured solubilities of lidocaine, benzocaine, and vanillic acid in aqueous 4-formylmorpholine mixtures. DOOIT2 employs rigorous API-out Structured Group K-Fold validation with fold-specific ensemble models to ensure realistic assessment of generalization to unseen compounds. The obtained results are dataset-dependent. For the homogeneous acid series, COSMO-RS already delivers strong predictive performance (RMSD = 0.321, R[2] = 0.925), and DOOIT2 brings no meaningful improvement (RMSD = 0.310, R[2] = 0.923). In contrast, for the diverse API set, DOOIT2 reduces RMSD from 0.686 to 0.527 and increases R[2] from 0.829 to 0.849. Residual analysis indicates that prediction uncertainty is driven primarily by the low-solubility region rather than by a simple monotonic dependence on molecular weight alone. These findings delineate the practical boundaries of machine-learning assistance in solubility prediction and offer clear guidance for formulation scientists.

Malignant hyperthermia, a pharmacogenetic disorder of skeletal muscle, is a potentially fatal reaction triggered by exposure to volatile anesthetics or succinylcholine. Genetic testing of the three known involved genes (RYR1, CACNA1S, and STAC3) has become the first line of testing for malignant hyperthermia susceptibility. However, genetic testing has sensitivity of only up to 70%. Contracture testing may be used to rule out the disorder for some individuals. This study outlines a stepwise approach, using clinical history and assessment as well as interpretation of genetic variants to balance risks and benefits for individuals at risk of this disorder. This work has received an Affirmation of Value designation from the American Society of Anesthesiologists (Schaumburg, Illinois) and endorsement from the Canadian Anesthesiologists' Society (Toronto, Canada).