Quality testing is the most important checkpoint of any protein production process. By testing quality, you’ll know if your sample is functional and stable, which is critical to ensure that your experiments are reproducible.
There is no denying that quality control is important, but it can mean different things to different researchers, especially if they just focus on specific steps within a purification or characterization workflow process. However, working with good-quality data across the board will benefit the decision-making, credibility, and productivity of your entire team.
How good quality data can benefit your entire team
Decision-making: With better the data, you’ll be more confident with the results and have a lower risk of making wrong decisions based on them.
Credibility: Precise and reproducible data increases the credibility of your results, allowing other scientists to rely on them. It also builds trust among users and customers.
Productivity: Good-quality data prevents you from spending time validating results and fixing errors, thus stimulating research and increasing productivity.
How you can start monitoring quality
The Tycho NT.6 system from NanoTemper Technologies can examine protein quality in just minutes, with a high level of precision and repeatability unmatched by any current technology.
In this application note, Tycho was used to monitor the effect of storage time on the quality of Herceptin (Trastuzumab). The robust repeatability of the measurements generated by this technology increases the value of the results and allows for a better evaluation of the quality of therapeutic antibodies as well as any other protein.