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Arrhenius time-scaled least squares: a simple, robust approach to accelerated stability data analysis for bioproducts.
J Pharm Sci. 2014 Aug; 103(8):2278-86.JP

Abstract

Defining a suitable product presentation with an acceptable stability profile over its intended shelf-life is one of the principal challenges in bioproduct development. Accelerated stability studies are routinely used as a tool to better understand long-term stability. Data analysis often employs an overall mass action kinetics description for the degradation and the Arrhenius relationship to capture the temperature dependence of the observed rate constant. To improve predictive accuracy and precision, the current work proposes a least-squares estimation approach with a single nonlinear covariate and uses a polynomial to describe the change in a product attribute with respect to time. The approach, which will be referred to as Arrhenius time-scaled (ATS) least squares, enables accurate, precise predictions to be achieved for degradation profiles commonly encountered during bioproduct development. A Monte Carlo study is conducted to compare the proposed approach with the common method of least-squares estimation on the logarithmic form of the Arrhenius equation and nonlinear estimation of a first-order model. The ATS least squares method accommodates a range of degradation profiles, provides a simple and intuitive approach for data presentation, and can be implemented with ease.

Authors+Show Affiliations

inVentiv Health Clinical, Princeton, NJ, 08540.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article

Language

eng

PubMed ID

24974956

Citation

Rauk, Adam P., et al. "Arrhenius Time-scaled Least Squares: a Simple, Robust Approach to Accelerated Stability Data Analysis for Bioproducts." Journal of Pharmaceutical Sciences, vol. 103, no. 8, 2014, pp. 2278-86.
Rauk AP, Guo K, Hu Y, et al. Arrhenius time-scaled least squares: a simple, robust approach to accelerated stability data analysis for bioproducts. J Pharm Sci. 2014;103(8):2278-86.
Rauk, A. P., Guo, K., Hu, Y., Cahya, S., & Weiss, W. F. (2014). Arrhenius time-scaled least squares: a simple, robust approach to accelerated stability data analysis for bioproducts. Journal of Pharmaceutical Sciences, 103(8), 2278-86. https://doi.org/10.1002/jps.24063
Rauk AP, et al. Arrhenius Time-scaled Least Squares: a Simple, Robust Approach to Accelerated Stability Data Analysis for Bioproducts. J Pharm Sci. 2014;103(8):2278-86. PubMed PMID: 24974956.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Arrhenius time-scaled least squares: a simple, robust approach to accelerated stability data analysis for bioproducts. AU - Rauk,Adam P, AU - Guo,Kevin, AU - Hu,Yanling, AU - Cahya,Suntara, AU - Weiss,William F,4th Y1 - 2014/06/26/ PY - 2014/05/15/received PY - 2014/06/03/revised PY - 2014/06/04/accepted PY - 2014/7/1/entrez PY - 2014/7/1/pubmed PY - 2015/3/31/medline KW - formulation KW - kinetics KW - monte carlo KW - nonlinear regression KW - protein aggregation KW - stability SP - 2278 EP - 86 JF - Journal of pharmaceutical sciences JO - J Pharm Sci VL - 103 IS - 8 N2 - Defining a suitable product presentation with an acceptable stability profile over its intended shelf-life is one of the principal challenges in bioproduct development. Accelerated stability studies are routinely used as a tool to better understand long-term stability. Data analysis often employs an overall mass action kinetics description for the degradation and the Arrhenius relationship to capture the temperature dependence of the observed rate constant. To improve predictive accuracy and precision, the current work proposes a least-squares estimation approach with a single nonlinear covariate and uses a polynomial to describe the change in a product attribute with respect to time. The approach, which will be referred to as Arrhenius time-scaled (ATS) least squares, enables accurate, precise predictions to be achieved for degradation profiles commonly encountered during bioproduct development. A Monte Carlo study is conducted to compare the proposed approach with the common method of least-squares estimation on the logarithmic form of the Arrhenius equation and nonlinear estimation of a first-order model. The ATS least squares method accommodates a range of degradation profiles, provides a simple and intuitive approach for data presentation, and can be implemented with ease. SN - 1520-6017 UR - https://www.unboundmedicine.com/medline/citation/24974956/Arrhenius_time_scaled_least_squares:_a_simple_robust_approach_to_accelerated_stability_data_analysis_for_bioproducts_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0022-3549(15)30479-2 DB - PRIME DP - Unbound Medicine ER -