CytoSolve® Systems Architecture Enables In Silico Screening of Relaxation Pathways for British American Tobacco Research Innovation and Harm Reduction Science

British American Tobacco
British American Tobacco (BAT) is a global organization with advanced research and development capabilities focused on understanding biological mechanisms relevant to consumer products and harm-reduction science. BAT’s R&D group applies rigorous analytical, biological, and computational methods to study complex physiological systems, supporting evidence-based innovation and scientific transparency.

Challenge

BAT sought a deeper mechanistic understanding of how multiple bioactive ingredients influence biological systems associated with relaxation and stress modulation. These systems span highly interconnected molecular pathways, including neurotransmitter signaling, hormonal regulation, immune responses, and neuromodulatory feedback loops. Traditional experimental approaches are limited in their ability to efficiently assess non-linear interactions, combinatorial effects, and system-wide responses across multiple pathways. A scalable, quantitative, and mechanistic framework was required to evaluate both individual ingredients and their combinations without relying exclusively on extensive in vitro or in vivo experimentation.

How CytoSolve Helped

CytoSolve applied its distributed systems biology platform to perform in silico combination screening based on peer-reviewed scientific literature. Six core molecular pathway systems governing relaxation biology were identified: gut microbiome–neuroinflammation signaling, hypothalamic–pituitary–adrenal (HPA) axis signaling, brain-derived neurotrophic factor (BDNF) signaling, neurotransmitter pathways involving GABA and serotonin, catecholamine signaling via dopamine, and endocannabinoid signaling centered on anandamide (AEA).

Each pathway was independently translated into a validated mathematical model using ordinary differential equations and encoded in SBML format. CytoSolve® dynamically integrated these pathway models into a unified quantitative systems architecture, preserving individual pathway identities while enabling real-time interaction across the full relaxation network. Six shortlisted bioactive ingredients were simulated across physiologically relevant dose ranges to assess their mechanistic effects on key biomarkers, both individually and within the integrated system. The architecture was designed to support future optimization of multi-ingredient combinations based on defined biological objectives.

Key Benefits Realized

  • Systems-level quantification of ingredient effects across interconnected relaxation pathways
  • Mechanistic clarity into modulation of inflammation, cortisol dynamics, neurotransmission, and neurotrophic signaling
  • Rapid, scalable screening of multiple ingredients across six molecular systems
  • Combination-ready computational framework supporting formulation optimization
  • Reduced dependence on early-stage animal and cell-based experimental studies

Outcome

The CytoSolve® Systems Architecture delivered a comprehensive, mechanistic assessment of bioactive ingredients acting on molecular systems underlying relaxation for British American Tobacco. By integrating multiple biological pathways into a single in silico framework, the collaboration enabled data-driven ingredient prioritization and established a scalable foundation for future combination optimization. This case study demonstrates the value of systems architecture–based computational screening as a rigorous approach for investigating complex biological phenomena within modern, science-driven R&D programs.