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Global Biopharma Leader Case Study: Increasing scientists’ satisfaction with data capture by 3X

Increase process efficiency and data integrity in order to shorten development timelines for the treatment of rare blood disorders

The blood disorders R&D department at a top-10 global biopharmaceutical company develops life-changing treatments for genetic diseases such as hemophilia and sickle cell anemia. Their work includes screening early-stage candidates, optimizing leads through in vitro and in vivo assays, and conducting IND submissions. By replacing their complex set of software tools with Benchling’s data-driven driven platform, the company now has a unified, cloud-based solution that standardizes data collection and automatically organizes and interlinks samples and results data. This has dramatically increased data integrity while reducing the time scientists spend searching for information and sharing it with colleagues. This also sets them up to gain more value out of their captured data through analytic and machine learning initiatives.


# of employees: 100,000+

Industry: Biopharma

Location: Massachusetts


Wasted time
Each scientist spent over 11 hours each week on manual and logistical tasks related to data collection, cleanup, and hand-offs, drastically slowing the pace of research.

Fragmented data capture
Disjointed software tools made it difficult to organize and standardize data collection, hindered scientists’ ability to trace samples through their workflows, and impeded their ability to derive insights from their experiments.

Poor data quality and tracing
A slow, clunky legacy ELN diminished data quality and led to challenges with regulatory compliance. This led to time-consuming reworking of data related to regulatory submissions.

  • 80%
    decrease in time spent searching for data
  • $1.04M
    reduction in estimated FTE cost annually*
  • 67%
    increase in confidence in data quality

*ROI calculation leverages Benchling’s ROI calculator. Assumptions include $150K average FTE scientist cost (payroll costs only) annualized across 42 total scientist users

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