Planning a multi-site chemometric model rollout
A multi-site rollout is not one deployment repeated N times. Five upstream decisions - governance, transfer, validation, change control, data flow - determine whether site N behaves like site one.
Tag
#chemometrics
22 articles tagged chemometrics.
Field notes: regulatory inspectors and PAT
A composite of practitioner conversations on FDA and EU inspections that put process analytical technology and chemometric models in scope. Inspectors read the lifecycle records, not the qualification protocols.
Open-source spectroscopy tools compared, 2026 edition
A side-by-side ranking of the open-source software stack practitioners actually use for Raman, IR, and NIR processing in 2026 - what each does best, where it stops short, and which combinations work in production.
Field notes: data scientists discovering chemometrics
Synthesised observations from PAT-adjacent engagements where data scientists from web-product backgrounds collide with chemometricians steeped in PLS, ASTM E1655, and calibration transfer.
PITTCON 2026 and analytica 2026: process analytics on the agenda
Recap of process analytical talks, awards and sessions from PITTCON 2026 in San Antonio and the analytica conference 2026 in Munich, with verified program details from both organizers.
Open-source spectroscopy tools in academia: the 2026 state of play
The open-source stack that academic spectroscopy groups now teach with - mdatools, Quasar, pyMCR, rampy, pybaselines - has matured into something an industry hire arrives knowing. A field snapshot.
Comparing FDA, EMA, and PMDA approaches to chemometric model lifecycle
FDA, EMA, and PMDA all build on ICH Q2(R2) and Q14, but their expectations for routine chemometric model upkeep, post-approval changes, and reference-method failures diverge in ways that shape submission strategy.
Notable arXiv physics.chem-ph preprints, mid-May 2026
Four mid-May physics.chem-ph preprints worth a PAT reader's time: vibrational eigenstate computation, polaritonic spectroscopy reliability, ML for photochemical decay, and DFT-accuracy ML force fields.
Calibration transfer between instruments: a working protocol
A partial least squares model rarely survives the move to a second instrument unchanged. A working protocol covers transfer set design, the standardisation method, and the acceptance criteria.
Multivariate SPC for process spectroscopy: T-squared and Q-residual
Univariate SPC watches one number. A spectroscopic analyser produces a thousand. Multivariate SPC condenses them into two statistics that have been the standard since the early 1990s.
Peer-reviewed PAT validation work, late 2025 to spring 2026
Six recent peer-reviewed PAT papers worth a read: lean chemometrics for spectroscopic models, simpler bioprocess Raman regressions, at-line terahertz for crystallinity, and PAT-with-machine-learning past the bioreactor.
Planning a calibration set for chemometric models: a working checklist
A calibration set defines what a chemometric model can predict, and where it will fail. Five planning decisions made up front determine whether validation later passes or unravels.
Calibration transfer between spectrometers: what the 2025-2026 papers changed
Three recent papers shift the calibration-transfer conversation: a low-rank fine-tuning method for deep Raman models, a vendor-to-vendor PDS/SST study, and single-compound shortcuts that sidestep paired transfer sets.
ACS Analytical Chemistry: three 2026 papers that matter for process analytics
March-May 2026 in ACS Analytical Chemistry: three threads for process analytics - close-focus Raman probes for turbid streams, deep-learning chemometrics, and open-source spectroscopy tooling.
What is process analytical technology (PAT)?
A primer on PAT - the FDA-driven framework for measuring chemistry where it happens, why pharmaceutical and chemical manufacturers adopt it, and the tools that make it practical.
Hyperspectral imaging in process analytics: what the 2025-2026 reviews say
Six recent reviews map where hyperspectral imaging now sits as a process-analytics tool in pharma, food, recycling, and beyond - and where chemometrics, data hunger, and standards still hold it back.
Deep-learning chemometrics for process Raman: where the 2026 literature has landed
Five recent papers sketch where deep-learning chemometrics sits versus PLS for process Raman: a public bioprocess benchmark, two classifier benchmarks, self-supervised pre-training, and an explainability tool for GMP.
Open-source chemometric libraries: what's actually usable in production
scikit-learn, pyChemometrics, ChemometricsLib, and the rest. A practitioner's review of what works for inline spectroscopy, what doesn't, and where the gaps still are.
Chemometrics 101: the math that turns spectra into decisions
Spectra are not answers. The bridge between a 1,000-channel spectrum and a number you can act on is chemometrics - a small toolbox of multivariate methods, used the same way for forty years.
PCA vs PLS: when to use each in chemometric work
Both methods take a 1,000-channel spectrum and compress it into a handful of latent variables. They are not interchangeable. PCA describes; PLS predicts. The decision is older than most of the software.
Validating a chemometric model for GMP: a working checklist
ICH Q14 sets the framework. ASTM E1655 sets the practice. The intersection - what an inspector actually wants to see in a chemometric validation file - is a short, specific list.
Field notes: why chemometricians and process engineers talk past each other
A composite of observations from PAT projects where the model team and the line team had everything they needed except a shared vocabulary. What both sides actually mean by the words they use.