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Pathway-Based Similarity Measurement to Quantify Transcriptomics Similarity Between Human Tissues and Preclinical
Paarth Parekh1, Jason Sherfey1, Begum Alaybeyoglu1
1Javelin Biotech, Inc., Woburn, Massachusetts, USA.
Clinical Pharmacology and Therapeutics
|October 8, 2024
Summary
A new pathway-based similarity measurement (PBSM) quantifies preclinical model relevance to human tissues. This method aids drug development by improving model selection and reducing translation gaps.
Area of Science:
- Biotechnology and Biomedical Engineering
- Translational Medicine
- Genomics and Transcriptomics
Background:
- Clinical translation of preclinical research faces challenges due to species differences and heterogeneity.
- Microphysiological systems (MPS) offer improved recapitulation of human physiology but lack quantitative similarity assessment.
- A need exists for methods to evaluate preclinical model relevance for specific contexts of use (CoU).
Purpose of the Study:
- To develop and validate a quantitative method, pathway-based similarity measurement (PBSM), for assessing preclinical model similarity to human systems.
- To leverage RNA-sequencing (RNA-seq) data and pathway information for evaluating human relevance in drug development models.
- To demonstrate PBSM's utility in selecting and validating preclinical models for specific CoU.
Main Methods:
- Development of pathway-based similarity measurement (PBSM) integrating RNA-seq data with pathway information.
- Application of PBSM to assess transcriptomic similarity between preclinical models and human tissues (liver and cardiac).
- Evaluation of PBSM's capability to support CoU selection, analyze gene set impacts, and differentiate model types.
Main Results:
- PBSM provides a quantitative method to compare transcriptomic similarity between preclinical models and human tissues.
- Proof-of-concept demonstrated for liver and cardiac tissues, enabling improved model selection and validation.
- PBSM successfully supports CoU selection, assesses gene set influence, and differentiates in vitro and in vivo models.
Conclusions:
- PBSM significantly reduces the translational gap in drug development by quantitatively evaluating preclinical model similarity to human systems.
- Facilitates informed model selection and enhances understanding of context-specific applications for preclinical models.
- Provides a foundation for improving the physiological relevance of in vitro models and advancing therapeutic interventions.
