4.6 Article

Tackling quantitative polymorphic analysis through fixed-dose combination tablets production. Pyrazinamide polymorphic assessment

Journal

Publisher

ELSEVIER
DOI: 10.1016/j.jpba.2020.113786

Keywords

Pyrazinamide (PZA); Polymorphism; Fixed-dose combination (FDC); Near infrared spectroscopy (NIR); Partial least squares (PLS); Process analytical technology (PAT)

Funding

  1. National Scientific and Technical Research Council (CONICET), PUE IQUIR
  2. Secretary of Science and Technology of UNR (SECyT-UNR) [BIO498, BIO572]
  3. CONICET

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This study developed a comprehensive strategy using near infrared spectroscopy (NIR) coupled with partial least squares regression (PLS) to quantify Form a of PZA in both drug substance and PZA/RIF/ISH-FDC tablets. The NIR-PLS models were optimized using radial optimization and showed satisfactory results in validation.
Pyrazinamide (PZA), Rifampicin (RIF), Isoniazid (ISH) and Ethambutol (ETB) form the core for the treatment of Tuberculosis, today a devastating disease in low-income populations around the world. These drugs are usually administrated by fixed-dose combination (FDC) products, to favour the patient compliance and prevent bacterial resistance. PZA exists in four enantiotropically-related polymorphs (Forms alpha, delta, beta and gamma), but only Form a is considered suitable for pharmaceutical products due to its stability and bioavailability properties. The classical approaches to address solid-state (microscopy, X-ray diffraction and calorimetry) shows limitations for quantification of polymorphs in the presence of excipients and other active components, as in the case of FDC tablets. In this work, an overall strategy was developed using near infrared spectroscopy (NIR) coupled to partial least squares regression (PLS) to quantify Form a of PZA in drug substance (raw material) and PZA/RIF/ISH-FDC tablets. For this purpose, two PLS models were constructed, one for drug substance preparing training (n = 30) and validation (n = 18) samples with a ternary composition (Form alpha/Form delta/Form gamma), and other for FDC drug products, also including the appropriate amount of RIF, ISH and the matrix of excipients in order to simulate the environment of PZA/RIF/ISH association. The NIR-PLS models were optimized using a novel smart approach based on radial optimization (full range, 3 L V and MSC-D' and SNV-D' as pre-treatment, for raw material and FDC tablets, respectively). During the validation step, both methods showed no bias or systematic errors and yielded satisfactory recoveries (102.5 +/- 3.1 % for drug substance and 98.7 +/- 1.5 % for FDC tablets). When commercial drug substance was tested, NIR-PLS was able to predict the content of Form alpha (0.98 +/- 0.01 w/w). The model for FDC tablets allowed estimating polymorphic purity in intact (0.984 +/- 0.003 w/w), sectioned (0.986 +/- 0.002 w/w), and powered (0.985 +/- 0.004 w/w) tablets, showing the methodology could be applied to a different stage of the process (i.e premixed-powders or granulates). The suitability of the method was also verified when Form a was satisfactorily analysed in FDC fortified with Form S and Form gamma to reach 0.78, 0.88 and 0.98 w/w, Form alpha. This strategy results in an excellent alternative to ensure the polymorphic purity of PZA throughout the overall pharmaceutical manufacturing process. (C) 2020 Elsevier B.V. All rights reserved.

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