{"doi":"10.1126/sciadv.abb6594","title":"Modeling, design, and machine learning-based framework for optimal injectability of microparticle-based drug formulations","abstract":"Inefficient injection of microparticles through conventional hypodermic needles can impose serious challenges on clinical translation of biopharmaceutical drugs and microparticle-based drug formulations. This study aims to determine the important factors affecting microparticle injectability and establish a predictive framework using computational fluid dynamics, design of experiments, and machine learning. A numerical multiphysics model was developed to examine microparticle flow and needle blockage in a syringe-needle system. Using experimental data, a simple empirical mathematical model was introduced. Results from injection experiments were subsequently incorporated into an artificial neural network to establish a predictive framework for injectability. Last, simulations and experimental results contributed to the design of a syringe that maximizes injectability in vitro and in vivo. The custom injection system enabled a sixfold increase in injectability of large microparticles compared to a commercial syringe. This study highlights the importance of the proposed framework for optimal injection of microparticle-based drugs by parenteral routes.","journal":"Science Advances","year":2020,"id":58857,"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":70,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9555,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":310052,"name":"Adam M. Behrens","orcid":null,"position":1,"is_corresponding":false},{"id":308811,"name":"Kevin J. McHugh","orcid":"0000-0001-6801-4431","position":2,"is_corresponding":false},{"id":308812,"name":"Hannah T. M. Contreras","orcid":"0000-0002-9429-3750","position":3,"is_corresponding":false},{"id":308813,"name":"Zachary L. Tochka","orcid":"0000-0002-9626-6190","position":4,"is_corresponding":false},{"id":308814,"name":"Xueguang Lu","orcid":"0000-0002-1069-7265","position":5,"is_corresponding":false},{"id":40706,"name":"Robert Langer","orcid":"0000-0003-4255-0492","position":6,"is_corresponding":false},{"id":308815,"name":"Ana Jaklenec","orcid":"0000-0001-6096-0538","position":7,"is_corresponding":false},{"id":308810,"name":"Morteza Sarmadi","orcid":"0000-0001-9018-4066","position":0,"is_corresponding":true}],"reference_count":49,"raw_metadata":null,"created_at":"2026-07-18T21:07:33.416320Z","pmid":"32923598","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":[]}