Best of the Week: Bioprocess Monitoring, Rewriting Atomic Spectroscopy

A new hybrid calibration strategy for real-time bioprocess monitoring using Raman spectroscopy was recently evaluated. We go over the results of this peer-reviewed study here. Also, a new “Chemometrics in Spectroscopy” column examined a solution to repack variation in diffuse-reflection measurements, and a new Q&A highlights the latest trends and advancements in laser-induced breakdown spectroscopy (LIBS).

This is the Best of the Week.

A new peer-reviewed article examined a hybrid calibration strategy for real-time bioprocess monitoring. In the study, researchers combined Uniform Design laboratory data with a limited number of in-process samples to build multivariate models that cover a wider range of concentrations without requiring a ton of extra experimental runs.¹ The approach held up well when quantifying analytes like monoclonal antibodies and nucleotides during ultrafiltration, diafiltration, and in vitro transcription processes, even when spectral overlaps came into play.¹

Next, this month's “Chemometrics in Spectroscopy” column tackles repack variation in diffuse-reflection measurements. The method pairs Lagrange's method of undetermined multipliers with clutter suppression, using repack replicates to estimate a clutter covariance matrix and whiten calibration spectra before correction.² The payoff is that it can handle multiple, non-proportional sources of spectral variability at once, and since whitening happens as a preprocessing step, it plays nicely with multiple linear regression (MLR), polymerase chain reaction (PCR), and partial least squares (PLS) alike.²

Third, we turn to atomic spectroscopy, where instrumentation is evolving fast. Single-particle inductively coupled plasma–time of flight–mass spectrometry (ICP-TOF-MS) is enabling particle-level elemental and isotopic analysis, multi-collector ICP-MS is expanding isotope applications, and LIBS is pushing into biomedical and pharmaceutical territory.³ AI is playing a growing role too by handling interference correction, anomaly detection, and chemometric modeling to boost performance across the board.³

And finally, we published a Q&A article about LIBS. Recent work highlights its use in forensic anthropology for re-associating bone remains, plus applications in aluminum alloy analysis, PVC hardness testing, and agricultural smoke tracing, with machine learning (ML) helping sharpen accuracy along the way.⁴

That's your Best of the Week. Thanks for watching, thanks for reading, and we'll see you next time.

References

1. Khadka, N.; Zhang, L. Uniform Design-Augmented Process Data for Multivariate Raman Calibration in Bioprocess Monitoring. Spectrosc. 2026, 41 (wp8). Available at: https://www.spectroscopyonline.com/view/uniform-design-augmented-process-data-for-multivariate-raman-calibration-in-bioprocess-monitoring
2. Mark, H.; Workman, Jr., J. Whitened Repack Invariance: A Generalized Least-Squares Extension of the Lagrangian Repack-Correction Algorithm for Diffuse Reflection Clutter Suppression in NIR Calibration. Spectroscopy 2026, ASAP. Available at: https://www.spectroscopyonline.com/view/whitened-repack-invariance-a-generalized-least-squares-extension-of-the-lagrangian-repack-correction-algorithm-for-diffuse-reflection-clutter-suppression-in-nir-calibration
3. Workman, Jr., J. Smarter, Smaller, Sharper: The New Machines Rewriting Atomic Spectroscopy. Spectroscopy 2026, ASAP. Available at: https://www.spectroscopyonline.com/view/smarter-smaller-sharper-the-new-machines-rewriting-atomic-spectroscopy
4. Wetzel, W. The Latest Advancements and Applications of Laser-Induced Breakdown Spectroscopy. Spectroscopy Online, 2026. https://www.spectroscopyonline.com/view/the-latest-advancements-and-applications-of-laser-induced-breakdown-spectroscopy (accessed August 27, 2026).