Designing a calibration set in spectral space for efficient development of an NIR method for tablet analysis

Alam, Anik; Drennen, James K.; Anderson, Carl A.

doi:10.1016/j.jpba.2017.06.012

Cited by 14 publications

(7 citation statements)

References 29 publications

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“…The RMSEP was separated into bias and standard error of prediction (SEP) using Eqs. 3 and 4, respectively, and compared using a 95% t confidence interval following a method outlined previously 18,41,42 bias ¼ 1 n…”

Section: Model Comparisonmentioning

confidence: 99%

Chemometrics and Experimental Design for the Quantification of Nitrate Salts in Nitric Acid: Near-Infrared Spectroscopy Absorption Analysis

et al. 2021

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Implementing remote, real-time spectroscopic monitoring of radiochemical processing streams in hot cell environments requires efficiency and simplicity. The success of optical spectroscopy for the quantification of species in chemical systems highly depends on representative training sets and suitable validation sets. Selecting a training set (i.e., calibration standards) to build multivariate regression models is both time- and resource-consuming using standard one-factor-at-a-time approaches. This study describes the use of experimental design to generate spectral training sets and a validation set for the quantification of sodium nitrate (0–1 M) and nitric acid (0.1–10 M) using the near-infrared water band centered at 1440 nm. Partial least squares regression models were built from training sets generated by both D- and I-optimal experimental designs and a one-factor-at-a-time approach. The prediction performance of each model was evaluated by comparing the bias and standard error of prediction for statistical significance. D- and I-optimal designs reduced the number of samples required to build regression models compared with one-factor-at-a-time while also improving performance. Models must be confirmed against a validation sample set when minimizing the number of samples in the training set. The D-optimal design performed the best when considering both performance and efficiency by improving predictive capability and reducing number of samples in the training set by 64% compared with the one-factor-at-a-time approach. The experimental design approach objectively selects calibration and validation spectral data sets based on statistical criterion to optimize performance and minimize resources.

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Section: Model Comparisonmentioning

confidence: 99%

Chemometrics and Experimental Design for the Quantification of Nitrate Salts in Nitric Acid: Near-Infrared Spectroscopy Absorption Analysis

et al. 2021

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“…While spectroscopic PAT can be used to advantage, it also carries disadvantages for a number of technical and industryspecific reasons, including (1) challenges to develop and implement and (2) a high degree of overhead and resources to maintain [12]. In order to ensure that spectroscopic PAT models can predict attributes of interest over the desired manufacturing ranges and across the multiple excipient and API lots used in commercial life cycle, using the most commonly employed regression-based techniques, spectroscopic calibration sets are designed to incorporate as much of this variation upfront as possible [13]. Therefore, to best anticipate how to keep models robust to future variation, a significant number of manufacturing runs, process, and material variations are required for inclusion or at least evaluation, in the calibration model.…”

Section: Challenges For Pat Development Implementation and Maintenancementioning

confidence: 99%

Process Control of Drug Product Continuous Manufacturing Operations—a Study in Operational Simplification and Continuous Improvement

et al. 2020

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Purpose The purpose of this manuscript is to demonstrate that implementation of gravimetric measurements provides the same assurance of product quality and process control as spectroscopic measurements (1) for control of drug content in a fixed-dose combination (FDC) tablet and (2) for identification of non-conforming material. Methods A wet granulation continuous tableting line was used to make the FDC drug product batches. Comparative data was generated for ten batches using near-infrared (NIR) spectroscopy for core tablets, and gravimetric in-process control measurements (IPCs) applied to the ratio control of intra- and extra-granular blend (IG and EG). HPLC reference data were collected to further demonstrate uniformity at each stage of the production process, including IG, final blend, and core tablets. All possible sources of variation not directly detectable by the gravimetric measurements were considered and quantified. Results The two IPC measurement techniques showed excellent agreement where both were within 2% of the target drug concentrations and within 2% of each other for the ten comparative batches. The NIR was more sensitive to material and process variations than the gravimetric IPCs; thus, it was more variable within and across batches. Gravimetric IPCs were demonstrated as an effective replacement for spectroscopic measurements for continuous tableting operations, capable of ensuring on target manufacturing and detection of non-conforming material. Conclusions As pharmaceutical companies continue to push toward operational simplicity and sustainable manufacturing processes, soft-sensor and gravimetric controls as alternatives to their spectroscopic counterparts will be applied more broadly for process monitoring and control.

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“…The model tablet score represents the score of the spectra recorded on a target formulation projected onto the orthonormal basis vector of the pure components spectra. After designing the spectral space calibration set, the composition of each spectra is retrieved by mathematical means [37].…”

Section: Design Of Experiments Strategymentioning

confidence: 99%

Multivariate Calibration for the Development of Vibrational Spectroscopic Methods

Tomuță¹,

Porfire²,

Casian³

et al. 2018

Calibration and Validation of Analytical Methods - A Sampling of Current Approaches

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Vibrational spectroscopy, namely near infrared (NIR) and Raman spectroscopy, is based on the interaction between the electromagnetic radiation and matter. The technique is sensitive to chemical and physical properties and delivers a wide range of information about the analyzed sample, but in order to extract the information, multivariate calibration of the spectral data is required. The main goal of this work will be to present in detail the available multivariate calibration strategy for development of NIR and Raman spectroscopic methods, which was successfully applied in pharmaceutics.

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Designing a calibration set in spectral space for efficient development of an NIR method for tablet analysis

Cited by 14 publications

References 29 publications

Chemometrics and Experimental Design for the Quantification of Nitrate Salts in Nitric Acid: Near-Infrared Spectroscopy Absorption Analysis

Chemometrics and Experimental Design for the Quantification of Nitrate Salts in Nitric Acid: Near-Infrared Spectroscopy Absorption Analysis

Process Control of Drug Product Continuous Manufacturing Operations—a Study in Operational Simplification and Continuous Improvement

Multivariate Calibration for the Development of Vibrational Spectroscopic Methods

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