77 Benchling Testimonials

“Benchling has given the Serotiny team a 360˚ degree view into our R&D progress. This has improved collaboration and time to insight, and has enabled us to ask new questions we weren’t previously able to.”

“We benchmarked a lot of different solutions. One of the solutions we started using was a competitor of Benchling, but it was super heavy to put in place, and we weren’t very happy about it; we started using Benchling two years ago."

“It feels good to have something automated with just a single click, where before it took half an hour. As more people are getting familiar with the software, we’re saving even more time."

“At Gilead, we’re committed to creating a healthier world for everyone by discovering, developing and delivering medicines for life-threatening diseases. This work requires managing highly complex, multi-dimensional data and necessitates technology partners that can support the scale and complexity of the data created by high-throughput biology. We selected Benchling as a partner because it’s built for biology. By capturing structured data in Benchling, our scientists are empowered to ask challenging questions and uncover new insights.”

“It’s an enormous benefit transitioning to Benchling because of the wins in operational efficiency. We’re seeing end to end times across our screening funnel that are substantially faster, and we’re seeing significant improvements on accuracy and precision.”

“We’ve increased our Benchling footprint 3x in just 1 year, helping us grow effectively. We’ve been focused on our science and building the team, and we’re thankful to have Benchling as a partner as we scale.”

"Data is everything. The quality, the accessibility, communicating results and then making decisions. Having that all in one place as early-on as possible enables you to do better experiments, ask better questions and solve problems more quickly in a way that gets us more value per experiment.”

“Being able to search through protocols, projects, directories for something that was written back in 2012 and is legible, is amazing.”

“Having all of this automated behind the scenes, and integrating with our own training data sets, expedites our experimentalists' lives. They don’t need to think about managing data; they get to see it in their lab notebook in Benchling, and are able to more readily make interpretations.”

“Our codon optimized sequences get popped right into Benchling, and that's step one of the mRNA process. Those sequences are registered in Benchling, the plasmid development teams then know they have something to work with, and experiments happen, and science happens. For me, that's really where it starts. It's understanding how this data is meant to be leveraged.”

“When we first started training machine learning models, we were standardizing and documenting sample info even as we were assembling training data, and it was a laborious process. But once we standardized the sample ontology for input into Benchling that enabled us to build workflows on the machine learning side that were much more streamlined, pulling from standardized labels automatically so that we could train models that optimize across multiple in vivo properties. This enabled us to scale up machine learning.”

“Our research progresses quickly, every action needs to be traceable and verifiable. Scientists and partners can’t be slowed down by siloed systems or a lack of consistent data. Connecting the lab and automating data capture and sharing through technology is a critical priority. Benchling will provide Zealand with the digital data foundation that helps us safely and confidently scale new use cases and partners.”

"Biology for the longest time has been about writing numbers in a paper notebook. Benchling helps us move towards having a way more reliable data capture. It provides us with a unified basis and uniform language in between the teams to capture the data."

“Data plays a fundamental role for Hoxton Farms, so structuring it well is crucial. We need data sets that are consistent and that aren’t confined to individual experiments, but rather run across experiments so we can iterate quickly and optimize our processes.”

"Just being able to share that same language has been so valuable for all our cross-functional projects and pipelines throughout the entire company."