QbD-driven RP-HPLC method for novel chemo-herbal combination, in-silico, force degradation studies, and characterization of dual drug-loaded polymeric and lipidic nanocarriers

Background In cancer therapies, chemo-herbal combinations are receiving increased attention. A multiple tyrosine kinase inhibitor, lenvatinib (LTB) is beneficial in treating thyroid, lung, endometrial, and liver cancers. An isoflavone called biochanin A (BCA) is well known for its diverse biological properties that have been studied to potentiate the anti-cancer potential and lower the normal cell toxicities of other therapeutics. LTB and BCA can be combined for cancer treatment and may increase their therapeutic potential at lower doses. In brief, the quality by design (QbD)-driven RP-HPLC method was developed, validated, and utilized for applications employing the study of forced degradants and the successful development of LTB and BCA co-loaded nanocarriers. Results The RP-HPLC method employed Box–Behnken design with peak resolution 6.70 ± 0.006, tailing factor 1.06 ± 0.05 for BCA and 1.17 ± 0.021 for LTB, and theoretical plates number > 2000. RP-HPLC applications utilized the investigation of a total of 41.17% and 70.58% degradants for LTB and BCA in contrast to in-silico predicted studies using Zeneth software. The poly (lactic-co-glycolic acid) nanoparticles (PLGA NPs) were formed with particle size 185.3 ± 12.3 nm, zeta potential − 13.3 ± 0.35 mV, and percentage entrapment efficiency () for the LTB and BCA 53.64 ± 4.81% and 61.29 ± 4.67%, respectively. However, the developed Cubosomes (CBs) exhibited 182.4 ± 16.3 nm aerodynamic particle size, − 10.8 ± 0.39 mV zeta potential, and % EE for LTB and BCA 55.62 ± 7.73% and 72.88 ± 5.52%, respectively. The percentage drug loading (%DL) of LTB and BCA from PLGA NPs was found to be 3.7 ± 0.46% and 4.63 ± 0.48%, whereas CBs exhibited higher % DL for BCA (5.42 ± 1.10%) and LTB (4.43 ± 0.77%). Conclusion The RP-HPLC method was developed and validated according to ICH and USP guidelines. In-vitro and in-silico forced degradation studies are evident to quantify the type of degradant and its exact mechanism of degradation. In-silico toxicity assessment for ...