{"doi":"10.3390/pharmaceutics17040452","title":"Microfluidics-Assisted Formulation of Polymeric Oxytocin Nanoparticles for Targeted Brain Delivery","abstract":"Background: The neuropeptide oxytocin has been identified as a potential therapeutic molecule. However, the therapeutic potential of this molecule is limited due to the challenges faced in oxytocin delivery to the brain. Scientific innovation has led to the breakthrough discovery of many modalities to encapsulate molecules for targeted drug delivery, which can enhance oxytocin delivery to the brain. This research aimed to explore a microfluidics-based system that optimizes the formulation of cross-linked bovine serum albumin (BSA) nanoparticles encapsulating oxytocin. Methods: First, the formulation parameters were optimized using a design of experiments (DOE) by evaluating the effect of flow rate, polymer concentration, and the binary solvent mixture polarity on the nanoparticle size. Drug encapsulation efficiency, release, and kinetics profile were characterized. These oxytocin nanoparticles were conjugated to rabies virus glycoprotein (RVG), a brain-targeting ligand, and the conjugation efficiency was determined. Results: The sizes of the nanoparticles were between 50 nm and 75 nm with a <0.4 polydispersity index. The encapsulation efficiency was >80%. Approximately 58% of oxytocin was released from the nanoparticles within the first six hours, showing an initial burst that is ideal for seizure control and thereafter exhibiting the Korsmeyer–Peppas release kinetics. Conclusions: For the first time, we demonstrated the microfluidics method of formulating nanoparticles with particle size of less than 100 nm, with improved encapsulation efficiency and optimal release profile for oxytocin brain delivery.","journal":"Pharmaceutics","year":2025,"id":519306,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9527,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1075042,"name":"Sharon Vijayanand","orcid":"0000-0002-4365-4157","position":1,"is_corresponding":false},{"id":1075043,"name":"Akanksha Kale","orcid":"0000-0003-2314-3867","position":2,"is_corresponding":false},{"id":1388231,"name":"Mahek Gulani","orcid":null,"position":3,"is_corresponding":false},{"id":472751,"name":"Jennifer C. Wong","orcid":"0000-0003-0602-6351","position":4,"is_corresponding":false},{"id":383896,"name":"Andrew Escayg","orcid":"0000-0001-7158-2878","position":5,"is_corresponding":false},{"id":452889,"name":"Kevin S. Murnane","orcid":"0000-0002-8143-0541","position":6,"is_corresponding":false},{"id":382126,"name":"Martin J. D’Souza","orcid":null,"position":7,"is_corresponding":false},{"id":1360396,"name":"Emmanuel Adediran","orcid":"0000-0003-4395-2485","position":0,"is_corresponding":true}],"reference_count":61,"raw_metadata":null,"created_at":"2026-07-19T02:49:18.751199Z","pmid":"40284447","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}