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Updated: Jul 14, 2026

Cost-Efficient Transcriptomic-Based Drug Screening
Published on: February 23, 2024
The relative transcription index: a gene expression based metric for prioritization of drug candidates
Sujoy Ghosh1, Mike A Watson, Jon L Collins
1GlaxoSmithKline, 5 Moore Drive, Research Triangle Park, NC 27709, USA. sg45653@gsk.com
Abstract:
Efficient compound selection remains a key challenge in drug discovery today. The goal is to identify developable drug candidates early in the screening process while simultaneously flagging compounds with off-target effects indicative of liabilities or alternate indications. This goal overlaps but is distinct from the goal of toxicogenomics which is focused primarily on identifying toxicity signatures of lead candidates in key tissues. We propose a framework where global changes in gene expression levels in response to compounds can be used as an objective metric for early compound prioritization. We call this metric the Relative Transcription Index (RTI). RTI is a measure of the relative activity of compounds as ascertained by their effects on transcription at a genome-wide level. Compounds with a low RTI affect the expression of only a few genes whereas compounds with a high RTI affect the expression of a large number of genes. This information is useful for differentiating compounds that, based on phenotypic assays alone, may appear to be equally efficacious. Since compounds with high RTI are more likely to display off-target effects, the RTI metric, if implemented early in the screening process, can become a valuable tool for compound selection. The utility of the RTI metric is demonstrated by its application to two different gene expression datasets--one involving modulators of the liver X receptor (LXR) and the other concerning antibacterial compounds belonging to diverse mechanistic classes.
Insights
A new Relative Transcription Index (RTI) metric prioritizes drug candidates by analyzing genome-wide gene expression changes. Compounds with low RTI indicate fewer gene effects, suggesting better developability and fewer off-target liabilities for efficient drug discovery.
Area of Science:
- Pharmacology
- Genomics
- Drug Discovery
Background:
- Efficient compound selection is crucial in drug discovery.
- Identifying developable drug candidates early and flagging off-target effects is a key challenge.
- Toxicogenomics focuses on toxicity signatures, distinct from compound prioritization.
Purpose of the Study:
- To propose a framework using global gene expression changes for objective early compound prioritization.
- To introduce the Relative Transcription Index (RTI) as a metric for compound activity.
- To demonstrate the utility of RTI in differentiating compounds and predicting off-target effects.
Main Methods:
- Developing the Relative Transcription Index (RTI) based on genome-wide gene expression.
- Analyzing gene expression data to quantify the number of genes affected by compounds.
- Applying the RTI metric to datasets of liver X receptor (LXR) modulators and antibacterial compounds.
Main Results:
- RTI quantifies compound activity by measuring genome-wide transcriptional effects.
- Low RTI compounds affect fewer genes, indicating potential developability.
- High RTI compounds affect numerous genes, suggesting a higher likelihood of off-target effects.
Conclusions:
- RTI serves as a valuable tool for early compound selection in drug discovery.
- The metric aids in differentiating compounds that may appear similar based on phenotypic assays alone.
- Implementing RTI early can help flag compounds with potential liabilities or alternate indications.
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