AAPS Workshop: accelerating pharmaceutical development through predictive stability approaches, April 4–5, 2016

Abstract

There has been significant growth in the use of modeling tools to accelerate development and enhance pharmaceutical quality. Among these are empirical and semi-empirical modeling of accelerated stability studies which can be used to predict product shelf-life (Waterman, Pharm Res 24:780-790, 2007; (Wu et al., AAPS Pharm Sci Tech,16:986-991, 2016

Prediction of the Long-Term Dissolution Performance of an Immediate-Release Tablet Using Accelerated Stability Studies

“…In general, scenario 2 leads to a predicted result slightly lower than the measured result as shown in Table 4 where, for example, the predicted %dissolution after 15 min is on average 2.11% lower than the measured result; this bias is much less with scenario 1 where the % dissolution after 15 min is on average only 0.23% lower than the measured result. The residual range shows that all predicted values are within ±4% of the measured value for all 552 dissolution results (for scenario 1); the average discrepancy between the measured and predicted value is indicated by the root mean square error, which is 1.26% (%dissolution) for scenario 1 All data in this table have units "%dissolution" and residuals are difference between the measured and predicted results, with negative numbers indicating that the predicted result is less than the measured result. RMSE, root mean square error.…”

“…The prediction and modeling of long-term stability behavior through the use of short-term accelerated studies is being increasingly applied in the pharmaceutical industry to accelerate development and improve pharmaceutical quality. 1,2 Accelerated predictive stability studies use elevated temperatures and a range of humidity conditions to build a temperature-humidity model of stability performance; they are mainly used to predict long-term chemical stability because the rates of chemical degradation reactions are generally accelerated by increased temperatures and humidity levels according to a humidity-modified Arrhenius relationship. 2 The applicability of humidity-modified Arrhenius models to various physical stability processes is much less certain; therefore, the prediction of the long-term dissolution performance, which may be affected by either chemical or physical processes, has not been reported widely in the literature.…”

Screening Autoxidation Propensities of Drugs in the Solid-State Using PVP and in the Solution State Using N-Methyl Pyrrolidone

“…Considerable time and effort are invested in the process of generating the stability data [ 1 ]. This data forms a part of the chemistry, manufacturing, and controls (CMC) dossier required for regulatory submissions, which is of importance for the licensing and approval of the finished product [ 2 ]. Potential instabilities (such as drug degradation) either in the drug substance or in the finished drug product may lead to shortcomings such as delays in the regulatory approval process, and if identified at late stages, may have undesirable consequences (e.g., market withdrawal/recall) with a potential waste of the time and efforts [ 3 ].…”

Long-Term Stability Prediction for Developability Assessment of Biopharmaceutics Using Advanced Kinetic Modeling

“…Several approaches have been described that predict the shelf life of liquid dosage forms of biopharmaceutics based on accelerated stability studies [22][23][24][25][26][27][28][29][30]. These are generally performed at elevated temperatures (e.g., 25 and 40 • C), whereas the recommended temperature for long-term storage is usually between 2 and 8 • C for injectable biopharmaceutics.…”