Shelf-life prediction

Hansen L D and Hart R M 1978 Shelf-life prediction from Induction period J. Electrochem. Soc. 125 842... 

C. Hebert, M.T. Charles, L. Gauthier, C. WiUemot, S.Khanizadeh and J. Cousineau, Strawberry proanthocyanidins biochemical markers for Botrytis cinerea resistance and shelf-life predictability. Acta Florticult. 567 (2002) 659-662. 

Nakabayashi, K., Shimamoto,T., and Mima, H. (1980), Stability of packaged solid dosage forms. I. shelf-life prediction for packaged tablets liable to moisutre damage, Pharm. Chem. Bull., 28,1090-1098. 

Hansen LD, Eatough DJ, Lewis EA, Bergstrom RG, Degraft-Johnson D, Cassidy-Thompson K. Shelf-life-prediction from induction period calorimetric measurements on materials undergoing autocatalytic decomposition. Can J Chem 1990 68 2111-2114. 

Yoshioka S, Aso Y, Izutsu K, Terao T. Application of accelerated testing to shelf-life prediction of commercial protein preparations. J Pharm Sci 1994 83 454-456. 

Shelf life prediction from accelerated, high temperature storage data. 

Calculations using Arrhenius plots, such as those described above, are carried out in the pharmaceutical industry every day. It should be made clear, however, that they involve a number of assumptions. It is assumed that the linearity of the graph obtained from equation (9.9) extends to room temperature, or, mathematically, that A and E are independent of temperature. If the line cannot be extrapolated to room temperature, shelf-life predictions are invalid. Second, it is assumed that the same chemical reaction is occurring with decomposition at high temperature as at low temperature. This is usually the case, but until proven it remains an assumption in most calculations. 

The acceleration factor. A, is based on the Arrhenius equation. Statistical tests indicated that the use of this equation was appropriate in this case. Shelf life predictions were also verified by real-time stability testing results. 

A product (aseptically produced and filled) in a multidose vial (20 ml) uses a natural rubber stopper through which the volatile preservative system is lost. As a result a 3 year shelf life (predicted and assumed previously) cannot be achieved. An alternative rubber stopper is advised. The supplier recommends a chlorbutyl synthetic rubber stopper. Actions advised are as... 

Packs which are to some degree permeable to moisture (as are most plastics) will lose or gain moisture according to whether they are exposed to a high or low relative humidity respectively. 40°C/75% RH may be particularly severe on a fully exposed blister pack and give an artificially low shelf-life prediction. The same condition may offer little challenge to moisture loss as the vapour pressure inside the pack may virtually be at equilibrium with the external atmosphere (plastic containers). 

TANTCHEV s, ONKOV K, MCKENNA B and NICOLAI B (1997), Correlation between carotene content and colour of fresh carrots , in Shelf life prediction for improved safety and quality of foods, Copernicus project, CIPA-CT94-0120, pp. 131-136. 

Figure 195. Distribution of true shelf life predicted from degradation percentage observed at 40°C. x Percent degraded during 6-month storage at 40°C. Assay error (standard deviation) 2% activation energy 20 kcal/mol. (Reproduced from Ref. 775 with permission.)...

A. K. Kishore and J. B. Nagwekar, Influence of temperature and hydrophobic group-associated icebergs on the activation energy of drug decomposition and its implication in drug shelf-life prediction, Pharm. Res. 7, 730-735 (1990). 

K. Nakabayashi, S. Hanatani, and T. Shimamoto, Stability of packaged solid dosage forms. VI. Shelf-life prediction of packaged prednisolone tablets in relation to dissolution properties, Chem. Pharm. Bull. 29, 2057-2061 (1981). 

For any type of product that gains or loses water, one can measure the moisture content as a function of relative humidity, or water activity, and determine a moisture isotherm. As shown in Fig. 14.14, moisture isotherms are usually sigmoid shaped curves. However, one can sometimes use only the linear portion of the curve for shelf life predictions. 

Let us look at an example of shelf life prediction where the Ap is constant throughout the storage. 

D. Nowak, P.P. Lewicki, and A. Lenart, Stabihty of apples during storage. Proceedings of the Final Workshop Shelf Life Prediction Copernicus Project CIPA-CT94-0120, ATO-DLO Press, Wageningen, the Netherlands, 1997, p. 81. 

Type of food Changes Oxidation Shelf life prediction... 

Marsili, R.T. Shelf-life prediction of processed mUk by solid-phase microextraction, mass spectrometry, and multivariate analysis. J. Agric. Food Chem. 48, 3470-3475 (2000). Mastrocola, D. and Munari, M. Progress of the Maillard reaction and antioxidant action of Maillard reaction products in preheated model systems during storage. J. Agric. Food Chem. 48, 3555-3559 (2000). 

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