Integrated experimental, computational and machine learning approaches for the development of Apremilast-Aceclofenac coamorphous systems.

Understanding the molecular mechanisms of drug coamorphization remains a key challenge in solid-state pharmaceutics. This study presents a molecular level strategy for designing drug-drug coamorphous systems (CAMs) of apremilast (APR) and aceclofenac (ACF) to enhance physicochemical, thermodynamic and therapeutic properties. Three monophasic CAMs-AA11, AA12 and AA21- comprising APR and ACF in 1:1, 1:2, and 2:1 molar ratios, respectively, were prepared via melt-quenching. Coamorphization was confirmed by powder X-ray diffraction (PXRD) and differential scanning calorimetry (DSC), as evidenced by halo patterns and single glass transition temperatures (Tg). Fourier transform-infrared (FT-IR) and nuclear magnetic resonance (NMR) spectroscopy revealed dense hydrogen bonding, π-π stacking and halogen interactions between drug functional groups. Density functional theory (DFT) with reduced density gradient (RDG) analysis and molecular dynamics simulations (MDS) elucidated interaction motifs, quantified miscibility and intermolecular distances. For the first time, artificial intelligence/machine learning (AI/ML)-based Tg prediction models were developed for CAMs using interaction-derived descriptors, achieving R2 > 0.90. CAMs demonstrated significantly improved solubility and dissolution, with AA12 achieving 3.6-fold (APR) and 3.2-fold (ACF) solubility increases, and > 90 % (APR) and ∼97 % (ACF) release within 3  h and 1  h, respectively. In vitro assays confirmed excellent cytocompatibility and strong suppression of pro-inflammatory cytokines (TNF-α, IL-17A, IL-23) in LPS-stimulated RAW 264.7 and L929 cells. Accelerated stability testing (40 °C/75 % RH) showed sustained amorphous stability, while forced degradation studies revealed lower degradation rates. This integrative framework provides a predictive, mechanistic basis for CAMs design and offers a broadly applicable strategy for dual-drug delivery in inflammatory disorders such as psoriasis.