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Despite their success, LNPs are predominantly liver\u2010targeted which limits their broader application. To expand the therapeutic potential of LNPs, this work implements a data\u2010driven approach that combines design of experiments (DoE), high throughput screening (HTS), and machine learning (ML) to tailor LNP formulations for preferential immune cell targeting. This methodology involves the generation of 180 LNP formulations, with varying lipid molar ratios and lipid chemistries, to explore a diverse design space. This work aims to identify LNP properties that enhance immune cell specificity while reducing hepatic uptake. The in vitro screening of these LNPs provided a rich dataset for ML analysis, leading to the identification of promising candidates with improved immune cellular selectivity profiles. These findings are validated in vivo where it is demonstrated that selected LNPs achieved preferential spleen expression with a successful redirection of LNP tropism beyond hepatic cells. This workflow highlights the importance of tailoring LNP compositions for the development of LNPs with selective cellular tropism.<\/jats:p>","DOI":"10.1002\/adhm.202500383","type":"journal-article","created":{"date-parts":[[2025,5,6]],"date-time":"2025-05-06T03:40:31Z","timestamp":1746502831000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Advancing Cellular\u2010Specific Delivery: Machine Learning Insights into Lipid Nanoparticles Design and Cellular Tropism"],"prefix":"10.1002","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5356-8458","authenticated-orcid":false,"given":"Belal I.","family":"Hanafy","sequence":"first","affiliation":[{"name":"Advanced Drug Delivery, Pharmaceutical Sciences Biopharmaceuticals R&amp;D AstraZeneca Cambridge CB2 0AA United\u00a0Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael 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