Date of Award

2021

Document Type

Dissertation

Degree Name

Doctor of Pharmaceutical Sciences

Department

Pharmaceutical Sciences

First Advisor

Rahul Haware

Committee Chair and Members

Rahul Haware, Chair

Kenneth Morris

Katherine Chu

David Taft

Qing Cai

Keywords

Dissolution, Fiber-optic dissolution, Multivariate analysis, Partial least square regression, Principal component regression, UV-visible spectroscopy

Abstract

The advancement and automation in analytical techniques is a current thrust of the pharmaceutical industry. It has been over 30 years since unconventional semi or fully automatic methods have begun to be developed to achieve the measurement in-situ in the dissolution test apparatus. The current study focuses on the fiber optic dissolution system (FODS), its challenges, and solutions to the challenges. The inaccuracy in dissolution profile predictions due to some limitations associated with the FODS makes it difficult to adopt this advanced automated technology for various purposes. The traditional dissolution methods are still widely used even though they are time-consuming and have other major drawbacks. The reason preventing wider adoption may be the perceived challenges in the method's reliability which is largely due to the lack of availability of proper guidelines and protocols to validate the analytical methods.

A successful validation scheme/protocol was developed for the dissolution testing using the FODS for CPM IR tablets. The protocol can be easily applicable to the other drug products compatible with the FODS analysis. The possible challenges associated with the FODS were identified during this study, and potential solutions were discussed thoroughly with individual examples. The overall scheme and illustration of the solution to the common problems related to the FODS could be very beneficial in building confidence to adopt the FODS widely in various applications of dissolution testing.

The problem of inaccurate dissolution profile predictions due to UV signal saturation associated with high dose formulations did not resolve by simple solutions explained in troubleshooting. Another challenge with FODS was its limitation to resolve strong overlapping UV signals during dissolution testing of multiple component drug products. A further in-depth study was required to develop an enduring solution that can be applied to other compounds showing similar issues with the FODS. Therefore, In the present work, an approach combining appropriate multivariate calibration methods with the UV spectral information from FODS was established to resolve the challenges associated with FODS, ultimately to predict accurate dissolution profiles. The PCR and PLS multivariate calibration models were developed with the calibration set consisting of full UV spectra and validated with the external data set. For the challenges associated to the UV signal saturation, the selection of different spectral regions and incorporation of quadratic terms were also explored. The conventional dissolution testing followed by HPLC analysis was used as a reference method to evaluate computed multivariate models' accuracy with the 'built-in' Opt-Diss model.

The proposed approach showed promising results and was comparable to traditional dissolution method. The method was able to accurately predict dissolution profiles of model drug products resolving the challenges associated with FODS. Further, both PCR and PLS models showed statistically equivalent results despite their fundamental differences in the basic principles and methodologies.

The approach developed in this thesis enables the use of FODS for the dissolution testing of drug products posing challenges due to UV signal saturation and band overlap, as an improved alternative to the commonly preferred method of HPLC analysis. The method is quick, simple, and economical in the long run compared to traditional dissolution followed by HPLC analysis with its many associated source of error. Thus, the approach presented is a significant step forward toward the advancement in the automation of dissolution testing of pharmaceutical drug products.

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