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Evaluation of Analytical and Sampling Errors in the Prediction of the Active Pharmaceutical Ingredient Concentration in Blends From a Continuous Manufacturing Process

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Abstract

Purpose

A near-infrared (NIR) spectroscopic method was developed for real time analysis of the active pharmaceutical ingredient (API) in blends from a continuous manufacturing process. The sampling and analytical errors of these determinations were estimated through variographic analysis.

Methods

Thirty-three calibration blends were prepared in laboratory scale equipment with a concentration range spanning from 70 to 130% of API target concentration. The NIR calibration model was validated using three independent validation sets (prepared in laboratory and pilot plant facilities and in the CM equipment). Real-time NIR spectra were obtained with an interface where three NIR spectrometers monitored the CM process. A variographic study was performed with the NIR predictions of drug concentration in blends.

Results

A total of 1800 NIR spectra were obtained throughout a CM run that lasted 2.5 h. Two NIR spectrometers (M1 and M2) monitored the CM run while located in positions b-1 and b-3 of the sensing interface. These two positions yielded very similar results. The average NIR predictions for blends were 101.67% LC for the first run using spectrometer M1 and 103.60% LC with M2. The second run provided an average NIR prediction of 101.19% LC with M1 and 103.16% LC with M2. The average drug concentration in tablets was 100.63% LC for the first run and 100.42% LC for the second run. Variograms showed a low sill and a flat, stable variogram demonstrating good mixing of the blend.

Conclusion

The CM process provided tablets with excellent content uniformity. The sampling and analytical errors and the true process variation were easily discerned through variographic analysis.

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Acknowledgements

This project was funded by Johnson and Johnson in collaboration with the National Science Foundation Engineering Research Center for Structured Organic Particulate Systems (C-SOPS). The authors thank Kim Esbensen for helpful discussions on the variographic analysis and the Theory of Sampling.

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Authors and Affiliations

  1. Janssen Ortho LLC-Gurabo, Gurabo, Puerto Rico

    Jenny M. Vargas & Eric Sanchez

  2. Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA

    Andres D. Roman-Ospino

  3. Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemistry, University of Puerto Rico Mayaguez Campus, PO Box 9000, Mayaguez, PR, 00681, Puerto Rico

    Rodolfo J. Romañach

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  1. Jenny M. Vargas
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  4. Rodolfo J. Romañach
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Correspondence to Rodolfo J. Romañach.

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Vargas, J.M., Roman-Ospino, A.D., Sanchez, E. et al. Evaluation of Analytical and Sampling Errors in the Prediction of the Active Pharmaceutical Ingredient Concentration in Blends From a Continuous Manufacturing Process. J Pharm Innov 12, 155–167 (2017). https://doi.org/10.1007/s12247-017-9273-1

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