Frontiers in PharmacologyImmunologyPeer-reviewed journal article
A pathway to next-generation mast cell stabilizers identified through the novel Phytomedical Analytics for Research Optimization at Scale data platform.
C. JanseniD, B. G. RiceiD, Billy Troy WootoniD, J. HowardiD, S. ElmasriiD, T. RiveraiD, Lori M. N. Shimoda, A. J. StokesiD, Chaker N. AdraiD, A. L. Small-HowardiD, H. TurneriD
Abstract
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 Ammi visnaga, 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 in vitro 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 in silico workflow and in vitro 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.
- organism: plant (other)
- assay: metagenomics
- research focus: drug response / drug discovery
- approach: deep learning
- approach: statistical model
- Citations
- 1
- FWCI
- 2.68
- Field percentile
- top 7%
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