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Related Concept Videos

Instrument Calibration01:12

Instrument Calibration

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Instrument calibration is essential for ensuring that instruments produce accurate and consistent results. It is vital in manufacturing, healthcare, testing laboratories, and scientific research. Calibration processes are specific to each instrument and help enhance data accuracy. Each instrument has a unique calibration process tailored to its design and function to improve data accuracy.
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...
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Raman Spectroscopy Instrumentation: Overview01:26

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A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
The monochromatic laser source, typically using visible or near-infrared radiation, generates a highly focused beam of light. This light interacts with the molecules of the sample, scattering some of the light. Liquid and gaseous samples are usually tested in ordinary glass capillaries, while solids can be analyzed as powders packed in capillaries or as potassium...
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Raman Spectroscopy: Overview01:20

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The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
However, a small fraction of the scattered light exhibits a frequency shift due to the exchange of energy between the incident photons and...
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Calibration Curves: Linear Least Squares01:20

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A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
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Calibration Transfer Across Instrument Vendors for Bioprocess Raman Monitoring.

Nathaniel M Myers1, Beibei Gao1, Daniel Amchin1

  • 1Johnson and Johnson Innovative Medicine, Welsh and McKean Roads Spring House, Spring House, Pennsylvania, 19477, U.S.A.

The AAPS Journal
|October 24, 2025
PubMed
Summary

Vendor-specific Raman spectroscopy hardware and software create challenges for biopharmaceutical manufacturing. This study demonstrates Piecewise Direct Standardization (PDS) and Spectral Subspace Transformation (SST) effectively transfer chemometric models between different Raman systems, improving agility.

Keywords:
Process Analytical Technology (PAT)calibration transferchemometric modelingpharmaceutical manufacturingraman spectroscopy

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Area of Science:

  • Biopharmaceutical Manufacturing
  • Process Analytical Technology (PAT)
  • Spectroscopy

Background:

  • Raman spectroscopy is a key Process Analytical Technology (PAT) for monitoring mammalian cell cultures in biopharmaceutical manufacturing.
  • Vendor-specific hardware and software in Raman systems create unique spectral signatures, leading to chemometric models that are not transferable between different vendors.
  • This vendor specificity complicates method validation, transfer between sites, and equipment upgrades, hindering the adoption of Raman spectroscopy.

Purpose of the Study:

  • To evaluate and compare two calibration transfer methods, Piecewise Direct Standardization (PDS) and Spectral Subspace Transformation (SST), for addressing vendor-to-vendor spectral variation in Raman spectroscopy.
  • To demonstrate the feasibility of transferring chemometric models between different Raman spectroscopy vendors without extensive re-development or re-validation.

Main Methods:

  • Comparison of PDS and SST methods for reducing spectral response variation between different Raman systems (Parent and Child).
  • Testing calibration transfer efficacy using offline samples and an established validation approach with paired spectra.
  • Investigation of calibration transfer parameter influence, including training set size, preprocessing position, and window size for PDS and SST.

Main Results:

  • Both PDS and SST methods successfully reduced spectral response variations between the Parent and Child Raman systems.
  • Calibration transfer results validated through offline samples and paired spectra demonstrated the effectiveness of both methods.
  • The study explored the impact of key parameters like training set size and window size on PDS and SST performance.

Conclusions:

  • PDS and SST are effective chemometric methods for transferring Raman spectroscopy models between different vendors, overcoming vendor-specific spectral signatures.
  • This vendor-to-vendor calibration transfer approach enhances the agility of chemometric model deployment across supply chains in the biopharmaceutical industry.
  • The successful transfer bolsters Raman spectroscopy's role as a versatile PAT tool for advanced biopharmaceutical manufacturing.