RESUMO
This review describes different trials to model and predict drug payload in lipid and polymeric nanocarriers. It traces the evolution of the field from the earliest attempts when numerous solubility and Flory-Huggins models were applied, to the emergence of molecular dynamic simulations and docking studies, until the exciting practically successful era of artificial intelligence and machine learning. Going through matching and poorly matching studies with the wet lab-dry lab results, many key aspects were reviewed and addressed in the form of sequential examples that highlighted both cases.
RESUMO
Poly(lactic-co-glycolic acid) (PLGA) is the most commonly described biocompatible copolymer used in biomedical applications. In this work, a green synthetic approach based on the biocompatible zinc proline complex, as an initiator for PLGA synthesis, is reported for the first time for the synthesis of methoxy-poly(ethylene glycol)-block-poly(l-lactic-co-glycolic acid) (mPEG-PLGA). mPEG-PLGA with controlled molecular weight and narrow polydispersity was synthesised. Its potential for delivery of irinotecan (Ir), a poorly water-soluble chemotherapeutic drug used for the treatment of colon and pancreatic cancer, was studied. Nanoparticles of controlled size (140-160 nm), surface charge (â¼-10 mV), release properties and cytotoxicity against CT-26 (colon) and BxPC-3 (pancreatic) cancer cells, were prepared. Tumor accumulation was confirmed by optical imaging of fluorescently labelled nanoparticles. Unlike Tween® 80 coated NP-Ir, the Pluronic® F-127 coated NP-Ir exhibits significant tumor growth delay compared to untreated and blank formulation treated groups in the CT-26 subcutaneous tumor model, after 4 treatments of 30 mg irinotecan per kg dose. Overall, this proof-of-concept study demonstrates that the newly synthesized copolymer, via a green route, is proven to be nontoxic, requires fewer purification steps and has potential applications in drug delivery.
