294
B. Igne et al.
References
1. P. Borman, P. Nethercote, M. Chatfield, D. Thompson, K. Truman, The application of quality
by design to analytical methods (2007)
2. G.L. Reid, J. Morgado, K. Barnett, B. Harrington, J. Wang, J. Harwood, D. Fortin, Analytical
Quality by Design (AQbD) in Pharmaceutical Development. American Pharmaceutical Review
(2013)
3. S. Wold, M. Sjöström, L. Eriksson, PLS-regression: a basic tool of chemometrics. Chemometr.
Intell. Lab. Syst. 58(2), 109–130 (2001)
4. E.V. Thomas, D.M. Haaland, Comparison of multivariate calibration methods for quantitative
spectral analysis. Anal. Chem. 62(10), 1091–1099 (1990)
5. F. Chauchard, R. Cogdill, S. Roussel, J.M. Roger, V. Bellon-Maurel, Application of LS-SVM
to non-linear phenomena in NIR spectroscopy: Development of a robust and portable sensor
for acidity prediction in grapes. Chemometr. Intell. Lab. Syst. 71(2), 141–150 (2004)
6. ICH, Pharmaceutical Development Q8(R2) (2009)
7. ICH, Validation of Analytical Procedures Q2(R1) (1996)
8. USFDA, Development and Submission of Near Infrared Analytical Procedures (2015)
9. European Medicine Agency, Guideline on the Use of Near Infrared Spectroscopy by the
Pharmaceutical Industry and the Data Requirements for New Submissions and Variations
(2014)
10. ASTM, Standard Guide for Multivariate Data Analysis in Pharmaceutical Development and
Manufacturing Applications, in E2891–13, ASTM International: West Conshohocken, PA
(2013)
11. ASTM, Standard Practice for Validation of the Performance of Multivariate Online, At-Line,
and Laboratory Infrared Spectrophotometer Based Analyzer Systems, in D6122-19b, ASTM
International: West Conshohocken, PA (2019)
12. W.S. Cleveland, S.J. Devlin, Locally weighted regression: An approach to regression analysis
by local fitting. J. American Stat. Assoc. 83(403), 596–610 (1988)
13. R.W. Kennard, L.A. Stone, Computer aided design of experiments. Technometrics 11(1), 137–
148 (1969)
14. R.W. Bondi Jr., B. Igne, J.K. Drennen Iii, C.A. Anderson, Effect of experimental design on
the prediction performance of calibration models based on near-infrared spectroscopy for
pharmaceutical applications. Appl. Spectrosc. 66(12), 1442–1453 (2012)
15. O. Scheibelhofer, B. Grabner, R.W. Bondi, B. Igne, S. Sacher, J.G. Khinast, Designed blending
for near infrared calibration. J. Pharm. Sci. 104(7), 2312–2322 (2015)
16. S. Mohan, W. Momose, J.M. Katz, M.N. Hossain, N. Velez, J.K. Drennen, C.A. Anderson, A
robust quantitative near infrared modeling approach for blend monitoring. J. Pharm. Biomed.
Anal. 148, 51–57 (2018)
17. R.J. Barnes, M.S. Dhanoa, S.J. Lister, Standard normal variate transformation and de-trending
of near-infrared diffuse reflectance spectra. Appl. Spectrosc. 43(5), 772–777 (1989)
18. P. Geladi, D. MacDougall, H. Martens, Linearization and scatter-correction for near-infrared
reflectance spectra of meat. Appl. Spectrosc. 39(3), 491–500 (1985)
19. H. Mark, R. Rubinovitz, D. Heaps, P. Gemperline, D. Dahm, K. Dahm, Comparison of the
use of volume fractions with other measures of concentration for quantitative spectroscopic
calibration using the classical least squares method. Appl. Spectrosc. 64(9), 995–1006 (2010)
20. ASTM, Standard Guide for Risk-Based Validation of Analytical Methods for PAT Applications.
In E2898–14 (2014)
21. J.J. Workman Jr., A review of calibration transfer practices and instrument differences in
spectroscopy. Appl. Spectrosc. 72(3), 340–365 (2018)
B. Igne et al.
References
1. P. Borman, P. Nethercote, M. Chatfield, D. Thompson, K. Truman, The application of quality
by design to analytical methods (2007)
2. G.L. Reid, J. Morgado, K. Barnett, B. Harrington, J. Wang, J. Harwood, D. Fortin, Analytical
Quality by Design (AQbD) in Pharmaceutical Development. American Pharmaceutical Review
(2013)
3. S. Wold, M. Sjöström, L. Eriksson, PLS-regression: a basic tool of chemometrics. Chemometr.
Intell. Lab. Syst. 58(2), 109–130 (2001)
4. E.V. Thomas, D.M. Haaland, Comparison of multivariate calibration methods for quantitative
spectral analysis. Anal. Chem. 62(10), 1091–1099 (1990)
5. F. Chauchard, R. Cogdill, S. Roussel, J.M. Roger, V. Bellon-Maurel, Application of LS-SVM
to non-linear phenomena in NIR spectroscopy: Development of a robust and portable sensor
for acidity prediction in grapes. Chemometr. Intell. Lab. Syst. 71(2), 141–150 (2004)
6. ICH, Pharmaceutical Development Q8(R2) (2009)
7. ICH, Validation of Analytical Procedures Q2(R1) (1996)
8. USFDA, Development and Submission of Near Infrared Analytical Procedures (2015)
9. European Medicine Agency, Guideline on the Use of Near Infrared Spectroscopy by the
Pharmaceutical Industry and the Data Requirements for New Submissions and Variations
(2014)
10. ASTM, Standard Guide for Multivariate Data Analysis in Pharmaceutical Development and
Manufacturing Applications, in E2891–13, ASTM International: West Conshohocken, PA
(2013)
11. ASTM, Standard Practice for Validation of the Performance of Multivariate Online, At-Line,
and Laboratory Infrared Spectrophotometer Based Analyzer Systems, in D6122-19b, ASTM
International: West Conshohocken, PA (2019)
12. W.S. Cleveland, S.J. Devlin, Locally weighted regression: An approach to regression analysis
by local fitting. J. American Stat. Assoc. 83(403), 596–610 (1988)
13. R.W. Kennard, L.A. Stone, Computer aided design of experiments. Technometrics 11(1), 137–
148 (1969)
14. R.W. Bondi Jr., B. Igne, J.K. Drennen Iii, C.A. Anderson, Effect of experimental design on
the prediction performance of calibration models based on near-infrared spectroscopy for
pharmaceutical applications. Appl. Spectrosc. 66(12), 1442–1453 (2012)
15. O. Scheibelhofer, B. Grabner, R.W. Bondi, B. Igne, S. Sacher, J.G. Khinast, Designed blending
for near infrared calibration. J. Pharm. Sci. 104(7), 2312–2322 (2015)
16. S. Mohan, W. Momose, J.M. Katz, M.N. Hossain, N. Velez, J.K. Drennen, C.A. Anderson, A
robust quantitative near infrared modeling approach for blend monitoring. J. Pharm. Biomed.
Anal. 148, 51–57 (2018)
17. R.J. Barnes, M.S. Dhanoa, S.J. Lister, Standard normal variate transformation and de-trending
of near-infrared diffuse reflectance spectra. Appl. Spectrosc. 43(5), 772–777 (1989)
18. P. Geladi, D. MacDougall, H. Martens, Linearization and scatter-correction for near-infrared
reflectance spectra of meat. Appl. Spectrosc. 39(3), 491–500 (1985)
19. H. Mark, R. Rubinovitz, D. Heaps, P. Gemperline, D. Dahm, K. Dahm, Comparison of the
use of volume fractions with other measures of concentration for quantitative spectroscopic
calibration using the classical least squares method. Appl. Spectrosc. 64(9), 995–1006 (2010)
20. ASTM, Standard Guide for Risk-Based Validation of Analytical Methods for PAT Applications.
In E2898–14 (2014)
21. J.J. Workman Jr., A review of calibration transfer practices and instrument differences in
spectroscopy. Appl. Spectrosc. 72(3), 340–365 (2018)