We collected a prospective dataset comprising at least 100 HPLC experiments per instrument from eight systems equipped with UV-vis detectors (see Methods). Kernel density estimation of the air bubble class probabilities revealed a noticeable shift for instrument #8 (Figure ), which led to the identification of malfunctioning check valves. These valves, critical for preventing backflow and maintaining pressure stability, were subsequently replaced on the HPLC pump module, restoring normal performance (Figure ). This approach appears to be more sensitive than the qualification experiments in detecting air bubble-associated issues (e.g. pump malfunctions). Incorporating this model into the instrument quality control pipeline will further enhance overall Cloud Lab performance. This enabled us to "flag" all affected HPLC experiments that had bubbles in the lines, not just those that had obvious noticeable negative impacts on the sample elution data. Overall, this will have a few positive impacts for the lab: Increase reproducibility of elution times and peak widths (2) extend column lifetimes, especially of gel columns (3) Improve troubleshooting turnaround time for HPLC.