Reproducibility in Science

The reproducibility crisis in science stems from unclear methods sections rather than unethical practices, impacting research efficiency. Cloud labs offer solutions by using precise code for reproducible experiments, fostering better outcomes.
By now, we’ve heard plenty about the “reproducibility crisis” in science. A lot of the stories we hear are about unscrupulous or desperate scientists who publish data that they have, to put it one way, tweaked. But despite the challenges inherent to manual lab work, the vast majority of scientists are in it for the right reasons. Therefore, the reproducibility crisis is not an issue of ethics. It is about something far more systemic in the way information is recorded and shared. In short, it is about the lack of reproducibility that no one knows is there, not even the authors of the papers where the offending data is published. It’s not about fraudulent or manipulated data, but the nature of data production which makes it unreproducible all the same.

Cloud Case: Pragma Bio X Emerald Cloud Lab

How a biotech startup is changing the research game with cloud lab technology
As a startup operating in the natural product space, the obvious challenge for Pragma was finding access to a diverse array of equipment that could keep up with a very wide range of potential discovery avenues. With analytical chemistry at the forefront of these needs, the requirements for instrumentation were not only broad but expensive—a truth which left Pragma with two potential pathways forward for their R&D: Cloud Lab or Contract Research Organization (CRO). 

Cloud Labs + AI : The New Digital Workflow

Helping Accelerate Scientific Progress Like Never Before
The convergence of highly automated cloud labs and AI represents a new frontier in modern research and will dramatically accelerate scientific innovation by helping researchers maximize the potential of their work. The synergy created by a new digital workflow where researchers utilize a single computer interface to design, run and analyze experiments in cloud lab environments with the aid of large language models will allow researchers to spend more time developing novel approaches to experiment design and analyzing results, and less time on manual, time-intensive tasks in the lab. The new digital workflow will serve as the ultimate research companion for today’s modern scientists, and the impact of this transition will be powerful by helping reduce the time it takes to develop new medicines and decrease the costs of developing new drugs.

Laboratory Startup Costs: Incubator vs Cloud Lab

What does it cost to get started?
The ECL provides significant value over the path of performing experiments through a mix of outsourcing and incubator benches / shared equipment on a per experiment basis, lowering barriers to entry by reducing operating costs, requiring no capital purchases and enabling startups to get experiments running in under a week.