Storing all metadata might be the smartest decision you'll make in your lab. Here’s the story behind this finding:
Not long ago, we worked with a client on a challenging process optimization project. Out of nowhere, they experienced a sudden drop in reaction performance - a mystery we couldn't immediately explain.We dug deeper to better understand what was going on.
Finally, we uncovered the culprit: one of the several chemicals slowly started to decompose after opening the raw material bottle.
For sensitive chemicals, like n-Butyllithium (n-BuLi), even slight exposure to oxygen or moisture can trigger unexpected reactivity changes. A small detail with a massive impact.
Had the lot number and the opening date been recorded, this could have been found faster.This experience highlighted a critical truth:
In process optimization, it’s not just about better algorithms, smarter designs, or faster equipment.
It’s about data integrity, and that starts with capturing comprehensive metadata such as:
- Lot numbers of chemicals used
- Opening dates and exposure durations
- Calibration settings for analysis
- Time stamps and raw sensor readings
- Cooling/heating rates and reagent addition times
- Sequence of addition and experimental procedures
- And several moreWhy does this matter?
Because when something goes wrong - and it will - metadata is your map.
Without it, you're left guessing.
Collecting metadata manually is a good start and often the only way, but can be inconsistent or skipped in fast-paced environments.Understandable. Labs are busy, experiments are complex, and small details can feel non-urgent.Until they’re not.
Modern labs that use Process Analytical Technologies (PAT) - inline sensors, probes, and real-time analyzers - are able to capture critical metadata automatically.
The result? Faster troubleshooting, consistent reproducibility, and machine learning models trained with more detailed context.
Automatic metadata capture isn’t just good practice. It’s a competitive advantage.