Journal of Pharmaceutical and BioTech Industry

Dry eye disease (DED) is a multifactorial ocular surface disorder that significantly affects vision and quality of life. While artificial tears are the standard first-line therapy, their effectiveness is limited by the complex pathophysiology of DED. This study evaluated DayDrop^® Triple Action, a novel formulation combining hyaluronic acid (HA), ectoine, and carboxymethylcellulose (CMC), designed to enhance tear film stability and ocular surface protection. Physicochemical and rheological properties were assessed, including viscosity, pseudoplasticity, and viscoelastic behaviour under dynamic conditions, along with ectoine release over 24 h. An in vitro allergic conjunctivitis model using conjunctival fibroblasts exposed to a pro-allergic cytokine cocktail was employed to examine immunomodulatory effects. DayDrop^® Triple Action demonstrated high viscosity with pronounced pseudoplasticity and stable viscoelasticity, supporting improved mucoadhesion. The formulation provided sustained ectoine release and exhibited a positive immunomodulatory effect, likely linked to ectoine’s preferential hydration mechanism, which stabilizes membranes and reduces inflammatory signalling. These findings suggest that DayDrop^® Triple Action integrates viscoelastic optimization, osmoprotection, and targeted anti-inflammatory action, offering a promising non-pharmacological strategy for managing DED and allergic ocular surface disorders.

The growing threat of Antimicrobial Resistance (AMR) demands innovative drug discovery, yet conventional 2D cell cultures fail to accurately mimic in vivo conditions, leading to high failure rates in preclinical studies. This review addresses the critical need for more physiologically relevant platforms by exploring recent advancements in bioengineered 3D tissue models for studying bacterial pathogenesis and antimicrobial drug discovery. We conducted a systematic search of peer-reviewed articles from 2015 to 2025 across PubMed, Scopus, and Web of Science, focusing on studies that used 3D models to investigate host–pathogen interactions or antimicrobial screening. Data on model types, biomaterials, fabrication techniques, and key findings were systematically charted to provide a comprehensive overview. Our findings reveal that a diverse range of biomaterials, including biopolymers and synthetic polymers, combined with advanced techniques like 3D bioprinting, are effectively used to create sophisticated tissue scaffolds. While these 3D models demonstrate clear superiority in mimicking biofilm properties and complex host–pathogen dynamics, our analysis identified a significant research gap: very few studies directly integrate these advanced bioengineered 3D models for high-throughput antimicrobial drug discovery. In conclusion, this review highlights the urgent need to bridge this disparity through increased research, standardization, and scalability in this critical interdisciplinary field, with the ultimate goal of accelerating the development of new therapeutics to combat AMR.

Evaluating power consumption in stirred media mills over a wide range of process parameters is crucial for analyzing breakage kinetics and milling efficiency. Despite considerable research efforts, existing models predominantly rely on power-law approaches and fail to provide a holistic understanding of the relationship between process parameters and power consumption. The aim of this study is to introduce a new mathematical model that accurately captures this relationship, across all bead filling ratios (φ), using dimensionless numbers including power number (Ne) and Reynolds number (Re). First, we considered experimental data from literature and discriminated various models to correlate either Ne or Re separately for each φ (Class 1 models) or Ne to Re–φ simultaneously (Class 2 models). The best performing model (Model 2.6 with SSR = 36.71, RMSE = 0.591, R² = 0.99) was subsequently applied to a new set of experimental data, confirming that this model is highly robust and reliable across various conditions. To the best of our knowledge, in stirred media mill research, this work is the first to show that a simple four-parameter nonlinear model provides a robust fit for Ne data across varying rotor Re (200 to 1 × 10⁶) and bead filling ratios (0.35–0.90).