The first ELNs were designed to capture intellectual property and small molecule chemistry. Many times, chemists used an ELN while the biologists were still working on paper or had a rudimentary paper-on-glass ELN. The market evolved, and several companies produced bio-oriented ELNs.
The time taken to document work is a critical step in R&D organizations, ensuring it will get secondary and tertiary use out of all that data and information. The right level of process rigor and metadata contextualization is imperative to produce model quality data, defined as data of sufficient breadth, resolution, and fidelity to confidently drive scientific understanding to higher levels of abstraction, informing burgeoning artificial intelligence and machine learning approaches capable of uncovering breakthrough insights.
Download the white paper to learn more about BioELNs, courtesy of PerkinElmer.