In silico Modeling for Respiratory Health — CytoSolve’s Modeling of RidgeCrest Herbals ClearLungs®

RidgeCrest Herbals is a nutraceutical company specializing in botanical formulations rooted in traditional Chinese herbal medicine. One of its flagship products, ClearLungs®, combines thirteen traditionally used Chinese herbs designed to support healthy respiratory function. To scientifically validate and mechanistically characterize ClearLungs®’ effects on lung congestion, RidgeCrest Herbals collaborated with CytoSolve to apply computational systems biology modeling to respiratory health pathways.

Challenge

Lung congestion is a complex physiological condition characterized by inflammation, excessive mucus production, and impaired airway smooth muscle relaxation, leading to fluid stagnation and obstructed airflow. While ClearLungs® has been shown to support respiratory health, the mechanistic basis underlying its multi-herb formulation had not been fully elucidated at a molecular systems level. Traditional experimental approaches face limitations in modeling the combined, synergistic effects of multiple bioactive compounds acting across interconnected respiratory pathways.

How CytoSolve Helped

CytoSolve applied its computational systems biology platform to build an integrative in silico model of lung congestion. The approach included:

  • Conducting a systematic literature review to identify molecular pathways involved in lung congestion
  • Translating these pathways into validated mathematical models representing key biological subsystem
  • Identifying three core systems governing lung congestion: inflammation, mucus homeostasis, and smooth muscle cell relaxation
  • Integrating the validated subsystem models using the CytoSolve® platform
  • Simulating the combined effects of all bioactive molecules in ClearLungs® at recommended dose levels

This integrative modeling strategy enabled quantitative assessment of how multiple botanical compounds interact across respiratory pathways simultaneously.

Key Benefits Realized

  • Systems-level mechanistic insight into lung congestion biology
  • Identification of inflammation, mucus production, and smooth muscle relaxation as primary therapeutic targets
  • Quantitative demonstration of synergistic effects among ClearLungs® ingredients
  • Scientific validation of a multi-herb formulation using predictive in silico modeling
  • Reduced reliance on isolated experimental testing for complex botanical combinations

Outcome

CytoSolve’s in silico modeling demonstrated that the combined bioactive ingredients in RidgeCrest Herbals’ ClearLungs® synergistically alleviate lung congestion by acting across multiple biological systems. Simulation results showed reductions in inflammatory signaling, decreased mucin production contributing to mucus buildup, and increased smooth muscle cell relaxation supporting airway openness.

This study provided a robust computational foundation validating the multi-target, systems-level efficacy of ClearLungs® and highlighted the power of in silico modeling to scientifically substantiate complex herbal formulations for respiratory health. These findings provide a robust computational foundation supporting the biological role of D-glucaric acid in liver health and reinforce the value of systems biology modeling in advancing applied food science research. This collaboration demonstrates how CytoSolve’s infrastructure delivers clinically relevant, peer-validated systems architectures—bridging molecular complexity with nutritional science to combat the root causes of chronic disease. Sent from my iPhone This collaboration exemplifies how CytoSolve’s infrastructure delivers peer-validated, mechanistically accurate systems architectures—bridging fluid dynamics and molecular biology to drive breakthroughs in cardiovascular and endothelial research.