Issue link: https://www.e-digitaleditions.com/i/1287521
48 September 2020 Tablets & Capsules NIR model external validation The ibuprofen and caffeine calibration models were performed with external samples prepared at laboratory scale as well as samples from the final product, taking into account that these models present good linearity with an R 2 close to 1 (Table 2). It was important to ana- lyze this internal validation because it allowed for assess- ment of the appropriate parameters via identification and quantification of error and uncertainty. Thus, an exter- nal validation was essential to verify that the calibration models were accurate, precise, and lineal [8]. T&C References 1. Ryan Kershner, Mike Kayat, Gary Ritchie, Sig- rid Pieters, Chris Heil, Rick Cox, George Reid, and Mark Mabry, "Raman/NIR roundtable," American Phar- maceutical Review, October 2012, https://www.american pharmaceuticalreview.com/Featured- Articles/122433- Raman- NIR-Roundtable/. 2. Jerome Workman, "Interpretive spectroscopy for near infrared," Applied Spectroscopy Review, 1996, Vol. 31, No. 3, pages 251-320, doi: 10.1080/05704929608000571. 3. Rampurna Prasad Gullapalli, "Soft gelatin capsules (Softgels)," Journal of Pharmaceutical Sciences, 2010, Vol. 99, No. 10, doi.org/10.1002/jps.22151. 4. Procaps, "Softgels," 2017, www.procapslaboratorios. com/softgels?lang=en-us. 5. Michal Douša et al., "Esterification of ibuprofen in soft gelatin capsules formulations identification, synthesis and liquid chromatography separation of the degradation products," Journal of Chromatographic Science, 2017, Vol. 55, No. 8, pages 790-797, 2017, doi: 10.1093/chromsci/ bmx036. 6. Xiaoliang Wang, Qiang Fu, Jinfang Sheng, Xin Yang, Jianzhong Jia, and Wei Du, "Construction of a uni- versal quantitative model for ibuprofen sustained-release capsules from different manufacturers using near-infrared diffuse reflection spectroscopy," Vibrational Spectroscopy, 2010, Vol. 53, No. 2, pages 214-217, doi: 10.1016/j. vibspec.2010.03.002. 7. Marcelo Blanco and Anna Peguero, "Influence of physical factors on the accuracy of calibration models for NIR spectroscopy," Journal of Pharmaceutical and Bio- medical Analysis, 2010, Vol. 52, No. 1, pages 59-65, doi: 10.1016/j.jpba.2009.12.009. 8. European Medicines Agency, "Guideline on the use of Near Infrared Spectroscopy (NIRS) by the pharmaceu- tical industry and the data requirements for new submis- sions and variations," January 2014, www.ema.europa.eu/ en/use-near-infrared-spectroscopy-nirs-pharmaceutical- industry-data-requirements-new-submissions. Jose Acosta (jacosta@procaps.com.co) is director of research and development, Sofia Pareja (spareja@procaps.com.co) is analyst II, Dahgna Paez (analistaid2@procaps.com.co) is analyst I, Jefferson Castro (jecastro@procaps.com.co) is ana- lyst II, and Freddy Barrios (fbarrios@procaps.com.co) is quality coordinator II at Procaps (575 371 9000, www.softi- gel.com). Jorge Ropero (jorgeropero@mail.uniatlantico.edu.co) is an associate professor in the Department of Chemistry at Universidad del Atlántico in Barranquilla, Colombia. Table 2 External validation with external samples prepared at laboratory scale as well as samples from final product Sample Ibuprofen (%) Caffeine (%) Reference Predicted Reference Predicted 110% Ibu + 110% Caf R1 110 108.9 110 111.5 110% Ibu + 110% Caf R2 110 111.1 110 108.4 100% Ibu + 100% Caf R1 100 99.3 100 104.3 100% Ibu + 100% Caf R2 100 99.4 100 104.4 90% Ibu + 90% Caf R1 90 92.6 90 86.7 90% Ibu + 90% Caf R2 90 92.5 90 86.5 Final product R1 100 100.1 100 105.5 Final product R2 100 100.3 100 103.5 Final product R3 100 100.0 100 102.4 Final product R4 100 99.9 100 104.1 Final product R5 100 99.2 100 105.3 Final product R6 100 100.3 100 101.4 Final product R7 100 100.2 100 102.1 Final product R8 100 100.2 100 99.0 Final Product R9 100 99.9 100 100.3 Standard error 0.86 0.82