Researchers and data scientists spend up to 80 percent of their time cleaning data instead of focusing on the higher-value scientific work needed to bring life-saving medications to market.
When asked what be on their wishlist if they were to build a lab from scratch, scientists asked for seamless integration between software and instruments, connectivity with lab equipment, and data analytics to gain new insights and automatically direct future experiments.
By implementing automation in the lab, this wishlist can become a reality. This white paper by TetraScience describes how automating manual data transformations can speed up processes, increase predictability, and eliminate slow, manual data handling.
Download this white paper to find out:
- How to automate collection, harmonization, processing, and storing of raw experimental data to support the needs of biopharma organizations
- How to connect instruments and software to deliver data to targets reliably and support complex workflows
- How to leverage data analytics to gain new insights to improve decisions and direct future experiments