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Team Talk

Collect Real-Time Data During Cell-Based Assays

Célia Gasselin
Célia Gasselin August 11, 2020

Recent progresses in AI-powered drug discovery bring a considerable number of potential drug candidates to the primary assay stage. However, only 10% will go through to clinical trials. It is therefore essential to quickly and accurately screen drug candidates, discard toxic or ineffective compounds and select the best candidates to move through development.

With the emergence of high-throughput technologies, pharmaceutical companies can screen a library of one million compounds in less than three months. In this fast-paced environment, scientists run a multitude of cell-based assays in parallel over weeks, generating a colossal amount of data.

Cell-based assays are performed on cell cultures in sterile conditions. Collecting data without increasing contamination risk is a real challenge and often requires interrupting the experiment, moving away from the sterile zone, removing gloves and grabbing a pen or computer keyboard. This data-experiment disconnect means researchers can forget to record key details, impacting experiment reproducibility.

Unlike standard electronic lab notebooks (ELNs), LabTwin fixes this broken dataflow between the lab bench and digital storage by directly connecting scientists with their data. LabTwin’s voice-powered digital lab assistant allows scientists to capture real-time digital data, and access information, at the bench, even in sterile conditions. LabTwin automatically digitizes data, sorts it by experiment and stores it in one centralized, secure platform. The digital lab assistant also helps scientists keep track of parallel assays and note any protocol changes or deviations.

“Before LabTwin, it took me two days to collect the information from my last experiment spread over weeks and several instruments.” LabTwin User, Scientist at Top Ten Pharma Company


Download this report to learn more about how pharma scientists use LabTwin to perform real-time documentation in sterile environments, improve reproducibility and lower error rates.


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