Drug Development: Preclinical Research


Preclinical studies must generate the comprehensive data needed for a therapeutic candidate to begin in-human clinical studies. The quality of the information collected from these animal and cell line models is vital for FDA submission and approval. Azenta Life Science Systems offers consulting services that identify the appropriate testing, sample processing, and data analysis methodologies for preclinical studies. We also provide support for the collection, processing, and analysis of those samples, plus storage for archival purposes. As the challenges in preclinical research become increasingly complex, Azenta Life Sciences’ straightforward solutions simplify these problems to ensure the quality of your FDA submissions.

Typical Pathway


Azenta Life Sciences Solutions
Experimental Design

Pathway 1.jpg    Experimental Design

  • Study design is reviewed and clinical assessment is made.
  • Experiment goals are aligned with sample collection and analysis strategies.
  • Sample processing plan is reviewed and technology is selected. 

Pathway 2.jpg    Sample Collection

  • GCP sample collection kits are produced with training materials, and samples are sourced.
  • Samples are transported to processing lab.
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Pathway 3.jpg    Sample Processing

  • Researchers identify appropriate molecular, pathological, and cellular analyses for models.
  • Proper technology is selected and sample processing is developed and validated.
  • Integrated analytical and functional quality control is established.
  • Animal or cell line samples are processed and tracked.
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Pathway 4.jpg    Data Generation

  • Analyses are performed in CLIA environment.
  • Discovery vs. targeted analyses are conducted.
  • Technology tool selection is made.
  • Assay sensitivity and specificity are determined.
  • Control samples are assessed and data is tracked.
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Pathway 5.jpg    Data Analysis

  • Open source and proprietary analytical pipelines are identified.
  • Sample data is functionally interpreted and correlated with other data sources.
  • Data is visualized, formatted, and securely transferred to storage.
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Pathway 6.jpg    Sample Storage

  • Sample storage environment is validated.
  • Proper storage tubes/plates and seals are selected.
  • Samples are stored in automated or manual systems.
  • QC metrics are established over time.
  • Sample distribution for additional analyses as needed.
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