Jansen C, Rice B G, Wooton B, Howard J, Elmasri S, Rivera T, Shimoda L M N, Stokes A J, Adra C N, Small-Howard A L, Turner H
Laboratory of Pharmacology and Analytics, School of Natural Sciences and Mathematics, Chaminade University, Honolulu, Hawai'i.
Data Analytics Research Team, UN CIFAL Honolulu, Chaminade University, Honolulu, Hawai'i.
bioRxiv. 2025 Sep 4:2025.08.30.673232. doi: 10.1101/2025.08.30.673232.
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, 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 used as an anti-inflammatory. Other phytopharmacopeias may offer candidate 'next generation' MCS (ngMCS) and in this study we hypothesized that a coupled pharmacoanalytic and pharmacology approach could be used to identify, prioritize and derisk additional candidate MCS from phytomedical sources for later pre-clinical and clinical evaluation. Here, we report a novel data analytics workflow starting with a newly developed phytopharmacopeia data platform with >3.5B linkage pathways (country → medical system → formulation → indication → ingredient organism → chemical component → other parameters), covering 22 M sq. miles of biogeography and historical and contemporary timeframes. Additional data layers include druggability indices, target and pathway analyses. The current study validates a subset of candidate phytomedical ngMCS using workflow and pharmacology, and develops a new harmonic mean-based 'MCS score' for further streamlining of the candidate prioritization process. 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.
肥大细胞稳定剂(MCS)有潜力满足过敏和炎症管理中未被满足的治疗需求。MCS可长期抑制促炎肥大细胞对刺激的所有反应途径(如组胺、蛋白酶、脂质介质、细胞因子、趋化因子)。因此,它们可能比H1、H2和H4抑制剂(抗组胺药)等方法更有效,后者仅能阻断肥大细胞急性组胺释放,而不影响其余功能反应。尽管MCS有潜力,但目前临床使用的MCS(如色甘酸钠、曲尼司特、奈多罗米)存在生物利用度差、给药频繁、缓解起效延迟长以及作用机制不明等问题。MCS起源于植物医学:色甘酸钠是该类药物中使用时间最长的,是用作抗炎药的凯林的衍生形式。其他植物药典可能提供候选的“下一代”MCS(ngMCS),在本研究中,我们假设可以使用联合药物分析和药理学方法从植物医学来源识别、排序并降低其他候选MCS的风险,以便后续进行临床前和临床评估。在此,我们报告了一种新颖的数据分析工作流程,该流程始于一个新开发的植物药典数据平台,该平台具有超过35亿个关联途径(国家→医疗系统→制剂→适应症→成分生物体→化学成分→其他参数),涵盖2200万平方英里的生物地理学以及历史和当代时间框架。其他数据层包括成药指数、靶点和途径分析。本研究使用该工作流程和药理学方法验证了候选植物医学ngMCS的一个子集,并开发了一种基于调和平均数的新“MCS评分”,以进一步简化候选排序过程。这项概念验证研究可能与肥大细胞活化综合征(MCAS)等复杂病症特别相关,在这些病症中,ngMCS可能优于当前的管理方法。