EVALUATION OF ML-ASSISTED COFORMER SCREENING FOR CO-CRYSTAL DESIGN OF ANTI CANCER AND IMMUNOMODULATORY DRUG

A stable multicomponent crystalline phase involving an anti-cancer agent (5-Fluorouracil, 5-FU) and an immunomodulator (Levamisole, LM) was developed through a systematic descriptor-guided screening workflow. Binary 5-FU/LM combinations failed to yield new solid phases, as assessed by Fourier Transform Infrared Spectroscopy (FTIR), a finding rooted in the complete absence of hydrogen bond donor functionality (HBD = 0) in levamisole. A composite descriptor-based coformer ranking algorithm, implemented in Python using RDKit, evaluated nine pharmacopoeially acceptable coformers against hydrogen bond donor-acceptor complementarity, topological polar surface area (TPSA), and LogP compatibility. Citric acid (CA) ranked first, driven by its hydrogen bonding capacity (HBD = 4, HBA = 4) and elevated TPSA. Twelve ternary formulations (5-FU/LM/CA) were prepared by solvent evaporation and anti-solvent addition across three molar ratios in water and EtOH:Water co-solvent systems. Quantitative FTIR descriptors served as inputs to a gradient boosting classifier for objective formulation ranking. F11 (1:2:1 molar ratio, anti-solvent addition, EtOH:Water) and F12 (same composition, solvent evaporation) emerged as the highest-ranked systems. New crystalline phases were confirmed in both by Powder X-Ray Diffraction, with diagnostic reflections absent from the physical mixture. Differential Scanning Calorimetry revealed a new endothermic event near 169–170°C in both formulations, with no endotherm attributable to free crystalline 5-FU, confirming complete API incorporation into the new co-crystal lattice.