Overview
Excelra applied a multi-omics analysis and scientific informatics approach to explore the therapeutic potential of probiotics for Autism Spectrum Disorder (ASD). Using comprehensive data integration across microbiome, gene expression, metabolomics, lipidomics, and clinical trial data, we identified high-confidence indications and generated actionable hypotheses. Leveraging our bioinformatics and computational biology services, the project provided a scientifically backed roadmap for future clinical development and therapeutic repositioning. For deeper insights into our computational strategies, see our computational biology services.
Our client
A UK-based CRO specialized in the microbiome domain had a growing portfolio of probiotics and was seeking to strategically diversify its assets. With a focus on evidence-backed expansion into neuro-gastroenterology, the client aimed to align new therapeutic areas with unmet medical needs and strong biological plausibility. By leveraging scientific informatics and scientific data management solutions
, the client explored new therapeutic possibilities.
Client’s challenge
A contract research organization (CRO) was aiming to expand its probiotic therapeutic portfolio. The client was particularly interested in exploring new indications for one of their probiotic assets, already known for its gut health benefits. Their challenge was to investigate its potential relevance in treating both behavioural and gastrointestinal (GI) symptoms of ASD—a complex condition with emerging links to microbiome health. Leveraging data curation and integrative analysis was critical to uncover meaningful insights.
Client’s goals
The client wanted to strategically expand their probiotic applications into neuro-gastroenterology. By leveraging scientific informatics and advanced analytics, their goal was to:
- Identify new indications for probiotics
- Generate clinically actionable hypotheses
- Accelerate the clinical development and validation process
- Apply insights from multi-omics analysis to make data-driven decisions
To support these goals, the client relied on Excelra’s bioinformatics services for comprehensive data-driven strategies.
Our approach
Excelra designed a multi-omics analysis–driven, integrative strategy to investigate the cross-functional therapeutic value of the client asset:
Systematic Analysis Across Omics Layers-
Comprehensive review of microbiome, gene expression, clinical trials, metabolomics, and lipidomics data.
Prioritization Framework
Ranked diseases based on consistency of positive indications across multiple omics layers, narrowing down to high-confidence candidates.
Alignment with Client’s Therapeutic Interests-
Shortlisted indications filtered based on strategic and commercial feasibility.
Hypothesis Generation-
Generated hypotheses for potential mechanisms of action using deep-dive analysis supported by our bioinformatics services.
Our solution
We identified that probiotics demonstrated promising support for therapeutic relevance in ASD, particularly addressing:
- Behavioural manifestations
- Gastrointestinal dysfunctions
This led to:
- Expansion of indications for an existing probiotic asset
- A scientifically backed therapeutic repositioning strategy powered by scientific informatics
- A roadmap for future clinical development and validation
Conclusion
Through a multi-omics analysis and data triangulation approach, Excelra identified ASD as a high-confidence indication for the client’s probiotic asset, based on consistent biological signals across five omics layers. The project resulted in:
- A 50% reduction in exploratory research timelines through focused analysis and hypothesis generation
- A clinically actionable roadmap for repurposing the selected strain in neuro-gastroenterological contexts
- Accelerated asset differentiation and progress toward clinical validation in a high-growth therapeutic area
By leveraging scientific informatics and advanced bioinformatics services, Excelra delivered a competitive advantage to the client in the microbiome space. For related data-driven insights, see our case study on structured and analysis-ready data for AI/ML-based drug discovery
