Implementing Quality by Design approach in Analytical RP-HPLC Method Development and Validation for the Determination of Fedratinib
Abstract
A novel, accurate, precise, specific, sensitive and robust RP-HPLC method was developed and validated for the determination of Fedratinib using Analytical Quality by Design (AQbD) approach which was mentioned in ICH Q8 (R2) guidelines. By implementing QbD in HPLC methods, ruggedness and robustness will be verified early in the stage of method development to ensure performance of the method over the life time of the product. Design Expert® (12.0.12.0) modelling software (Stat-Ease Inc., Minneapolis, MN, USA) was used for Response surface methodology (RSM). Plackett-Burman design was employed for the factor screening studies to identify the critical method parameters (CMP) affecting the critical quality attributes (CQA). The selected CMP’s were systematically optimized using Central-composite design (CCD). Statistical analysis of the responses was done by applying analysis of variance. Chromatographic separation was accomplished on Agilent C18 (150×4.6 mm, 5 µm) column and PDA-UV detection was set at 268 nm. The optimized and predicted data from Design Expert software consisted of mobile phase Acetonitrile: 0.1% OPA buffer pH 4.18 (43: 57 % v/v), pumped at a flow rate of 0.967 mL /min gave the highest desirability of 1. The developed chromatographic method was validated as per ICH Q2 (R1) guidelines and found to be linear over concentration range of 15-90 µg/mL with correlation coefficient of 0.999. Degradation studies were performed by exposing the drug to various stress conditions as per ICH Q1A (R2) guidelines and significant degradation was found in acidic condition.
Keywords:
AQbD, CCD, Desirability, Fedratinib, Forced degradationDOI
https://doi.org/10.25004/IJPSDR.2021.130303References
Blair HA. Fedratinib: First Approval. Drugs. 2019; 79: 1719–1725.
Talpaz M, Kiladjian JJ. Fedratinib, a newly approved treatment for patients with myeloproliferative neoplasm-associated myelofibrosis. Leukemia (2020). https://doi.org/10.1038/s41375-020-0954-2.
Jamieson C, Hasserjian R, Gotlib J, Cortes J, Stone R, Talpaz M et al. Effect of treatment with a JAK2-selective inhibitor, fedratinib, on bone marrow fibrosis in patients with myelofibrosis. J Transl Med. 2015; 13:294.
Pardanani A, Harrison C, Cortes JE. Safety and efficacy of fedratinib in patients with primary or secondary myelofibrosis: a randomized clinical trial. JAMA Oncol. 2015; 1(5):643–651.
Celgene Corporation. U.S. FDA approves INREBIC® (fedratinib) as first new treatment in nearly a decade for patients with myelofibrosis [media release]; 16 Aug 2019. http://ir.celgene.com.
Ayesha Begum K, Shiva Kumar G, Sandhya P, Bhikshapathi DVRN. A Highly Sensitive LC–MS/MS Method Development and Validation of Fedratinib in Human Plasma and Pharmacokinetic Evaluation in Healthy Rabbits. Curr. Pharm. Anal. 2020; 16: 1. https://doi.org/10.2174/1573412916999200512121023.
Pardanani A, Tefferi A, Jamieson C, Gabrail NY, Lebedinsky C, Gao G et al. A phase 2 randomized dose-ranging study of the JAK2-selective inhibitor fedratinib (SAR302503) in patients with myelofibrosis. Blood Cancer Journal 5, e335 (2015). https://doi.org/10.1038/bcj.2015.63.
Zhang M, Xu CR, Shamiyeh E, Feng Liu, Jian YY, Smith WB et al. A randomized, placebo-controlled study of the pharmacokinetics, pharmacodynamics, and tolerability of the oral JAK2 inhibitor fedratinib (SAR302503) in healthy volunteers. J Clin Pharmacol. 2014; 54(4):415–421.
Harrison CN, Schaap N, Vannucchi AM, Kiladjian JJ, Ramon VT, Zachee P et al. Janus kinase-2 inhibitor fedratinib in patients with myelofibrosis previously treated with ruxolitinib (JAKARTA-2): a single-arm, open-label, non-randomised, phase 2, multicentre study. Lancet Haematol. 2017; 4(7):e317–324.
Nishendu PN, Rakshit VK, Vidhi NK, Patel PB. Quality by Design: A complete review. Int J Pharm Sci Res. 2012; 17(2):20-28.
Sahu PK, Ramisetti NR, Cecchi T, Swain S, Patro CS, Panda J. An Overview of Experimental Designs in HPLC Method Development and Validation. J Pharm Biomed Anal. 2018; 147: 590−611.
Politis SN, Colombo P, Colombo G, Rekkas DM. Design of experiments (DoE) in pharmaceutical development. Drug Develop Ind Pharm. 2017; 43(6):889-901.
Candioti LV, De Zan MM, Camara MS, Goichoechea HC. Experimental design and multiple response optimization. Using the desirability function in analytical methods development. Talanta. 2014; 124:123-138.
ICH Harmonised Tripartite Guideline: Validation of Analytical Procedures: Text and Methodology Q2 (R1), current Step 4 version; International Conference on Harmonisation: Geneva, 2005.
ICH Harmonised Tripartite Guideline: Stability Testing of New Drug Substances and Products Q1A (R2), current Step 4 version; International Conference on Harmonisation: Geneva, 2003.
ICH Harmonised Tripartite Guideline: Photostability testing of New Drug Substances and Products Q1B, current Step 4 version; International Conference on Harmonisation: Geneva, 2003.
Suhkbir Singh, Yash Paul Singla, Sandeep Arora. Statistical, Diagnostic and Response surface analysis of Nefopam Hydrochloride Nanospheres using 35 Box-Behnken design. Int J Pharm Pharm Sci. 2015; 7(10): 89-101.
Montgomery DC. Design and analysis of experiments. Edn 7, John Wiley and Sons, New York, 2008, pp. 387-389.
Geoff Vining. Technical advice: Residual plots to check assumptions. Quality Engineering. 2011; 23(1):105–110.
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