Lab of the Future is now

Team Talk

How LabTwin accelerates Method Development for Protein Expression

Célia Gasselin
Célia Gasselin May 5, 2020

Bringing a new drug on the market is a long and expensive process. Biopharmaceutical companies spend around $1 billion in R&D per therapeutic product and the recent pandemics have highlighted the necessity of accelerating the deployment of new targeted drugs.

Developing a new drug starts with finding the optimum procedure for generating each protein candidate. This requires many iterations and adjustments of multiple parameters until the best result is obtained and a tailored protocol established. 


Documenting each parameter change and consequent observation is crucial for reducing the number of iterations, facilitating troubleshooting and finally defining the standard protocol for expressing the new protein. 

Therefore, scientists are often either interrupting their workflow to write down their notes or, in case the step is time-sensitive, keeping the information in memory until the end of the current experiment step. This generates an extra cognitive load, potential human errors and generally a  poorer documentation, all of it slowing down the procedure. 

Today, it is manifest that the Lab of the Future will be digital, seamless and connected and many pharmaceutical companies need to undertake digital initiatives to stay at the forefront of Drug Discovery and Development

LabTwin provides a unique solution by introducing hands-free voice-powered lab documentation at the point of experimentation.

“Before LabTwin, I was relying on my memory.” – Scientist at a Top Ten Pharma Company

In this report, we examine in detail the typical workflow for method development of protein expression, from cell culture to mass spectrometry. For each step, we address the specific challenges faced by the scientist and describe how LabTwin helps to overcome them.  

Download this report now to find out how pharma scientists develop new methods for protein expression, employ the world’s first AI and voice-powered digital lab assistant in their workflows and save time by reducing the number of unsuccessful experiments and improving reproducibility. 

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