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ISSN (Print): 2210-299X
ISSN (Online): 2210-3007

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Research Article

Early Prediction of the Chemical Stability of Drug Substances and Drug Products during the Development Phase

Author(s): Trupti Tol, Swapnil Mhamunkar, Harshad Tawde and Gautam Samanta*

Volume 1, 2023

Published on: 08 November, 2023

Article ID: e2210299X258686 Pages: 17

DOI: 10.2174/012210299X258686231026051150

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Abstract

Background: Traditional approach to shelf-life prediction claims a substantial amount of product development time, leading to significant delays.

Objective: The capability of the unconventional Accelerated Stability Assessment Program (ASAP) to decode chemical stability and expedite shelf-life prediction is discussed in the manuscript.

Methods: As per the ASAP approach, shelf-life limiting attributes for two APIs’ and a formulation were identified based on the isoconversion ratio. Isoconversion times at varying accelerated conditions were obtained and the degradation kinetics were modeled using the humidity-modified Arrhenius equation. R2 and Q2 values were derived to assure model predictability. Temperature and humidity sensitivity of the attributes were determined from the activation energy; Ea, and humidity sensitivity factor, B, respectively. Degradation plots demonstrated the dynamics of degradation with time. The predicted values were verified by the available real-time data.

Results: The degradation rate was modeled for impurities that exhibited conversion substantiated by an isoconversion ratio between 0.25-2.0. The Ea and B data provided valuable details regarding the sensitivity of the products. Predicted shelf-life of less than a year for the finished product instigated redevelopment. In the case of the APIs’, the existing storage conditions were found unsuitable for shelf-life stability, and alternate conducive conditions were identified.

Conclusion: The study provided cognizance regarding the distinct degradation pattern of an API and its formulation and the contradictory storage requirement for APIs’ of two different molecules. While the traditional approach claims 3-6 months to predict shelf-life, the ASAP approach provides the same with enhanced accuracy in just 3-4 weeks.

[1]
Suresh, P.; Basu, P.K. Improving pharmaceutical product development and manufacturing: Impact on cost of drug development and cost of goods sold of pharmaceuticals. J. Pharm. Innov., 2008, 3(3), 175-187.
[http://dx.doi.org/10.1007/s12247-008-9043-1]
[2]
Stability testing of new drug substances and products, ICH Q1A (R2), Ver. 04 https://database.ich.org/sites/default/files/Q1A%28R2%29%20Guideline.pdf2003.
[3]
Yang, M.; Byrn, S.R.; Clase, K.L. An analytic investigation of the drug formulation-based recalls in the usa: See more beyond the literal. AAPS PharmSciTech, 2020, 21(5), 198.
[http://dx.doi.org/10.1208/s12249-020-01726-9] [PMID: 32676955]
[4]
Kerstiens, E.A.; Byrn, S.R.; Clase, K.L. The identification of quality risk factors for non-biological complex drugs and epilepsy drugs using statistical analysis of formulation-based recalls in the USA. AAPS PharmSciTech, 2022, 23(1), 19.
[http://dx.doi.org/10.1208/s12249-021-02165-w] [PMID: 34904204]
[5]
Li, Q.C.; Qiu, F.; Cohen, K.; Tougas, T.; Li, J.; McCaffrey, J.; Purdue, T.; Song, J.J.; Swanek, F.; Abelaira, S. Best practices for drug substance stress and stability studies during early-stage development part I—conducting drug substance solid stress to support phase Ia clinical trials. J. Pharm. Innov., 2012, 7(3-4), 214-224.
[http://dx.doi.org/10.1007/s12247-012-9136-8]
[6]
Clancy, D.; Hodnett, N.; Orr, R.; Owen, M.; Peterson, J. Kinetic model development for accelerated stability studies. AAPS PharmSciTech, 2017, 18(4), 1158-1176.
[http://dx.doi.org/10.1208/s12249-016-0565-4] [PMID: 27422651]
[7]
Oliva, A.; Llabrés, M.; Fariña, J.B. Data analysis of kinetic modelling used in drug stability studies: Isothermal versus nonisothermal assays. Pharm. Res., 2006, 23(11), 2595-2602.
[http://dx.doi.org/10.1007/s11095-006-9096-0] [PMID: 16969699]
[8]
Campa, C.; Pronce, T.; Paludi, M.; Weusten, J.; Conway, L.; Savery, J.; Richards, C.; Clénet, D. Use of stability modeling to support accelerated vaccine development and supply. Vaccines., 2021, 9(10), 1114.
[http://dx.doi.org/10.3390/vaccines9101114] [PMID: 34696222]
[9]
Evers, A.; Clénet, D.; Pfeiffer-Marek, S. Long-term stability prediction for developability assessment of biopharmaceutics using advanced kinetic modeling. Pharmaceutics, 2022, 14(2), 375.
[http://dx.doi.org/10.3390/pharmaceutics14020375] [PMID: 35214107]
[10]
Fu, M.; Perlman, M.; Lu, Q.; Varga, C. Pharmaceutical solid-state kinetic stability investigation by using moisture-modified Arrhenius equation and JMP statistical software. J. Pharm. Biomed. Anal., 2015, 107, 370-377.
[http://dx.doi.org/10.1016/j.jpba.2015.01.014] [PMID: 25656488]
[11]
Rodante, F.; Vecchio, S.; Tomassetti, M. Kinetic analysis of thermal decomposition for penicillin sodium salts. J. Pharm. Biomed. Anal., 2002, 29(6), 1031-1043.
[http://dx.doi.org/10.1016/S0731-7085(02)00144-9] [PMID: 12110388]
[12]
Vyazovkin, S.; Wight, C.A. Kinetics in solids. Annu. Rev. Phys. Chem., 1997, 48(1), 125-149.
[http://dx.doi.org/10.1146/annurev.physchem.48.1.125] [PMID: 15012442]
[13]
Scrivens, G.; Clancy, D.; Gerst, P. Theory and Fundamentals of Accelerated Predictive Stability (APS) Studies, Accelerated Predictive Stability (APS) studies; Elsevier: Netherlands, 2018, pp. 33-73.
[http://dx.doi.org/10.1016/B978-0-12-802786-8.00003-6]
[14]
Waterman, K.C.; Carella, A.J.; Gumkowski, M.J.; Lukulay, P.; MacDonald, B.C.; Roy, M.C.; Shamblin, S.L. Improved protocol and data analysis for accelerated shelf-life estimation of solid dosage forms. Pharm. Res., 2007, 24(4), 780-790.
[http://dx.doi.org/10.1007/s11095-006-9201-4] [PMID: 17372701]
[15]
Waterman, K.C. The application of the Accelerated Stability Assessment Program (ASAP) to quality by design (QbD) for drug product stability. AAPS PharmSciTech, 2011, 12(3), 932-937.
[http://dx.doi.org/10.1208/s12249-011-9657-3] [PMID: 21748541]
[16]
Waterman, K.C.; Swanson, J.T.; Lippold, B.L. A scientific and statistical analysis of accelerated aging for pharmaceuticals. Part 1: accuracy of fitting methods. J. Pharm. Sci., 2014, 103(10), 3000-3006.
[http://dx.doi.org/10.1002/jps.24075] [PMID: 25043838]
[17]
Williams, H.E.; Bright, J.; Roddy, E.; Poulton, A.; Cosgrove, S.D.; Turner, F.; Harrison, P.; Brookes, A.; MacDougall, E.; Abbott, A.; Gordon, C. A comparison of drug substance predicted chemical stability with ICH compliant stability studies. Drug Dev. Ind. Pharm., 2018, 0362, 9045.
[http://dx.doi.org/10.1080/03639045.2018.1542707] [PMID: 30395722]
[18]
Blessy, M.; Patel, R.D.; Prajapati, P.N.; Agrawal, Y.K. Development of forced degradation and stability indicating studies of drugs—A review. J. Pharm. Anal., 2014, 4(3), 159-165.
[http://dx.doi.org/10.1016/j.jpha.2013.09.003] [PMID: 29403878]
[19]
Snape, T.J.; Astles, A.; Davies, J. Understanding the chemical basis of drug stability and degradation. Pharm. J., 2010, 1-7.
[http://dx.doi.org/10.1211/PJ.2021.1.7642]
[20]
Greenspan, L. Humidity fixed points of binary saturated aqueous solutions. J. Res. Natl. Bur. Stand., A Phys. Chem., 1977, 81A(1), 89-96.
[http://dx.doi.org/10.6028/jres.081A.011]
[21]
Malcolm, L. Accelerated Stability Assessment Program (ASAP) Applications in a Postapproval Environment. In: Accelerated Predictive Stability Fundamentals and Pharmaceutical Industry Practices; , 2018; pp. 287-304.
[http://dx.doi.org/10.1016/B978-0-12-802786-8.00012-7]
[22]
Genton, D.; Kesselring, U.W. Effect of temperature and relative humidity on nitrazepam stability in solid state. J. Pharm. Sci., 1977, 66(5), 676-680.
[http://dx.doi.org/10.1002/jps.2600660517] [PMID: 874750]
[23]
Šimon, P. Isoconversional methods. J. Therm. Anal. Calorim., 2004, 76(1), 123-132.
[http://dx.doi.org/10.1023/B:JTAN.0000027811.80036.6c]
[24]
Tol, T.; Tawde, H.; Gorad, S.; Jagdale, A.; Kulkarni, A.; Kasbale, A.; Desai, A.; Samanta, G. Optimization of a liquid chromatography method for the analysis of related substances in daclatasvir tablets using design of experiments integrated with the steepest ascent method and Monte Carlo simulation. J. Pharm. Biomed. Anal., 2020, 178, 112943.
[http://dx.doi.org/10.1016/j.jpba.2019.112943] [PMID: 31677954]
[25]
Benstock, D.; Cegla, F. Extreme value analysis (EVA) of inspection data and its uncertainties. NDT Int., 2017, 87, 68-77.
[http://dx.doi.org/10.1016/j.ndteint.2017.01.008]
[26]
Humidity control in refrigeration systems. Available from: http://plumbingandhvac.ca/humidity-control-in-refrigeration-systems/ (Accessed on: 18 May 2022).

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