AAPS Workshop on the Role of Dissolution in QbD and Drug Product Life Cycle: A Commentary

D’Souza, Susan; Lozano, Ruben; Mayock, Stephen P.; Gray, Vivian A.

doi:10.14227/dt170410p41

Cited by 6 publications

(3 citation statements)

References 3 publications

(1 reference statement)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The experimental data for glyburide had shown that low quality FaSSIF was the best media to establish an in vivo/in vitro correlation (IVIVC) and was, therefore, used in this study only (15,16). In a quality by design (QbD) approach, dissolution should reflect ideally the in vivo product performance (17)(18)(19). Starting out with simulated in vitro dissolution data as an input to an in vivo prediction software such as GastroPlus™ may help to establish IVIVC in the later stages of the drug development process.…”

Section: Percent Of Particles Distributionmentioning

confidence: 99%

Simulation of In Vitro Dissolution Behavior Using DDDPlus™

et al. 2014

View full text Add to dashboard Cite

Abstract. Dissolution testing is a performance test for many dosage forms including tablets and capsules. The objective of this study was to evaluate if computer simulations can predict the in vitro dissolution of two model drugs for which different dissolution data were available. Published montelukast sodium and glyburide dissolution data was used for the simulations. Different pharmacopeial and biorelevant buffers, volumes, and rotations speeds were evaluated. Additionally, a pH change protocol was evaluated using these buffers. DDDPlus™ 3, Beta version (Simulation Plus, Inc.), was used to simulate the in vitro dissolution data. The simulated data were compared with the in vitro data. A regression coefficient between predicted and observed data was used to assess the simulations. The statistical analysis of Montelukast sodium showed that there was a significant correlation between the in vitro release data and the predicted data for all cases except for one buffer. For glyburide, there was also a significant correlation between the experimental data and the predicted data using single pH conditions. Using the dynamic pH protocol, a correlation was significant for one biorelevant media. The simulations showed that both in vitro drug releases were sensitive to solubility effects which confirmed their BCS class II category. Computer simulations of the in vitro release using DDDPlus™ have the potential to estimate the in vivo dissolution at an early stage in the drug development process. This might be used to choose the most appropriate dissolution condition to establish IVIVC and to develop biorelevant in vitro performance tests to capture critical product attributes for quality control procedures in quality by design environments.

show abstract

Section: Percent Of Particles Distributionmentioning

confidence: 99%

Simulation of In Vitro Dissolution Behavior Using DDDPlus™

et al. 2014

View full text Add to dashboard Cite

show abstract

“…With the introduction of QbD by the Food and Drug Administration in 2004, pharmaceutical companies intensified their efforts to reach real-time release of industrial batches, thus reducing postprocessing quality control delays, the goal being to guarantee finished product quality and reduce product costs (International Conference on Harmonisation: Guidance on Q8, 2009). Obviously, the replacement of this test by a less resource-intensive technique through a QbD approach would be beneficial to the pharmaceutical industry (Tong and Lozano, 2009;D'Souza and Lozano, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…It is well-known that certain material attributes as well as manufacturing process parameters affect the results of dissolution tests performed on finished products. For example, several studies conclude that API dissolution and disintegration are linked: indeed the presence of disintegrants in tablets determines release rates and, consequently, physiological API availability (D'Souza and Lozano, 2010).…”

Section: Introductionmentioning

confidence: 99%