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Multi-instrument Calibration with Genetic Regression in UV-Visible Spectroscopy

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Abstract:

The applicability of genetic regression (GR) to multi-instrument calibration was demonstrated by using several UV-visible spectrophotometers. GR is a calibration technique that optimizes linear regression using a genetic algorithm (GA). Sample spectra of ternary and quaternary mixtures of the pharmaceuticals furaltadone (Fd), doxycycline (Dx), sulfadiazine (Sd), and trimethoprim (Tm) were collected on four different UV-visible spectrophotometers, including one single-beam diode array and three double-beam dispersive instruments. Hybrid calibration models (HCMs) were generated by combining the data collected on multiple instruments into one calibration model as if they had all been collected on a single instrument. For comparison, single-instrument calibration models were also generated for each instrument. Both HCMs and single-instrument models were tested by using a validation set measured on all four instruments. Results obtained from single-instrument models were comparable with a previous study in which partial leastsquares (PLS) regression was used for multivariate calibration of these compounds. HCMs for double-instrument cases performed equally well as single-instrument models and slightly worse for the four-instruments models.

Keywords: MULTIVARIATE CALIBRATION MULTI-INSTRUMENT CALIBRATION CALIBRATION TRANSFER GENETIC ALGORITHMS MULTICOMPONENT ANALYSIS PHARMACEUTICAL ANALYSIS

Document Type: Research Article

DOI: http://dx.doi.org/10.1366/0003702991946343

Publication date: February 1, 1999

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