{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T06:56:46Z","timestamp":1790751406348,"version":"4.1.0"},"reference-count":132,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T00:00:00Z","timestamp":1790726400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Pharmacol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>\n                      Mast cell stabilizers (MCS) have the potential to address unmet therapeutic need in allergy and inflammation management. MCS chronically suppress all arms of the pro-inflammatory mast cell response to stimulation (e.g., histamine, protease, lipid mediators, cytokines and chemokines). They may therefore outperform approaches such as H1, H2 and H4 inhibitors (antihistamines), which block only the acute histamine release by mast cells and leave the rest of the functional response untouched. Despite their potential, current MCS (e.g., cromolyn sodium, tranilast, nedocromil) in clinical use are hindered by poor bioavailability, frequent dosing, long lags to onset of relief, and enigmatic mechanisms of action. MCS have their origins in phytomedicine: cromolyn sodium is the longest standing drug in the class and is a derivatized form of khellin from\n                      <jats:italic>Ammi visnaga,<\/jats:italic>\n                      used as an anti-inflammatory. Other plant-based pharmacopeias may offer candidate \u2018next-generation\u2019 MCS (ngMCS) and in this study we hypothesized that a coupled pharmacoanalytic and\n                      <jats:italic>in vitro<\/jats:italic>\n                      pharmacology approach could be used to identify, prioritize and derisk additional candidate MCS from phytomedical sources for later preclinical and clinical evaluation.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We report a novel data analytics workflow starting with a newly developed plant-based pharmacopeia data platform with &amp;gt;3.5B linkage pathways (country \u2192 medical system \u2192 formulation \u2192 indication \u2192 ingredient organism \u2192 chemical component \u2192 other parameters), covering 22\u00a0M sq. miles of biogeography and historical and contemporary timeframes. Additional data layers include druggability indices, target and pathway analyses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The current study validates a subset of candidate phytomedical ngMCS using\n                      <jats:italic>in silico<\/jats:italic>\n                      workflow and\n                      <jats:italic>in vitro<\/jats:italic>\n                      pharmacology, and develops a new harmonic mean-based \u2018MCS score\u2019 for further streamlining of the candidate prioritization process.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>This proof-of-concept study may have particular relevance for complex presentations such as Mast Cell Activation Syndrome (MCAS) where ngMCS may outperform current management approaches.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fphar.2026.1718501","type":"journal-article","created":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T06:06:10Z","timestamp":1790748370000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A pathway to next-generation mast cell stabilizers identified through the novel Phytomedical Analytics for Research Optimization at scale data platform"],"prefix":"10.3389","volume":"17","author":[{"given":"C.","family":"Jansen","sequence":"first","affiliation":[{"name":"Laboratory of Pharmacology and Analytics, School of Natural Sciences and Mathematics, Chaminade University","place":["Honolulu, HI, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"B. 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