Objectives
- To provide a comprehensive, end-to-end workflow—from sample collection to interpretation—in both genomics and transcriptomics.
- Remove current barriers—such as fragmented tools, complexity, and poorly structured data—to free up time for research teams.
- Ensure a robust, repeatable, and high-quality process throughout the entire value chain.
Results
- Faster access to actionable results and reproducible analyses.
- Better-structured data flows and greater autonomy for scientific teams.
- A suite of solutions covering a wide range of applications in research and industry, with an initial focus on the pharmaceutical sector and clinical trials: biomarker identification and validation, translational research and clinical programs, multi-omic analysis, biomanufacturing, and genetic stability monitoring, as well as dermo-cosmetics and life sciences.
Issues
- The volume of genomic and transcriptomic data is growing faster than teams' ability to analyze it.
- The proliferation of tools and the complexity of analyses create a disconnect between the sample and the decision.
- Reproducibility and interoperability remain difficult to ensure throughout the entire process.
ADLIN's role
- Analyze data using its bioinformatics pipeline automation platform to generate scientific results.
- Combine multiple types of data (multi-omics) and provide advanced analysis tools.
- Make the results easily accessible and usable.
