Journal of Korean Society for Quality Management (품질경영학회지)

Korean Society for Quality Management (한국품질경영학회)
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Development of a New Similarity Index to Compare Time-series Profile Data for Animal and Human Experiments

동물 및 임상 시험의 시계열 프로파일 데이터 비교를 위한 유사성 지수 개발

  • Lee, Ye Gyoung (Department of Industiral & Management Systems Engineering, Dong-A University) ;
  • Lee, Hyun Jeong (Department of Industiral & Management Systems Engineering, Dong-A University) ;
  • Jang, Hyeon Ae (Department of Frontier Convergence Engineering, JEONJU University) ;
  • Shin, Sangmun (Department of Industiral & Management Systems Engineering, Dong-A University)
  • 이예경 (동아대학교 산업경영공학과) ;
  • 이현정 (동아대학교 산업경영공학과) ;
  • 장현애 (전주대학교 미래기술융합공학과) ;
  • 신상문 (동아대학교 산업경영공학과)
  • Received : 2021.02.22
  • Accepted : 2021.05.19
  • Published : 2021.06.30
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Abstract

Purpose: A statistical similarity evaluation to compare pharmacokinetics(PK) profile data between nonclinical and clinical experiments has become a significant issue on many drug development processes. This study proposes a new similarity index by considering important parameters, such as the area under the curve(AUC) and the time-series profile of various PK data. Methods: In this study, a new profile similarity index(PSI) by using the concept of a process capability index(Cp) is proposed in order to investigate the most similar animal PK profile compared to the target(i.e., Human PK profile). The proposed PSI can be calculated geometric and arithmetic means of all short term similarity indices at all time points on time-series both animal and human PK data. Designed simulation approaches are demonstrated for a verification purpose. Results: Two different simulation studies are conducted by considering three variances(i.e., small, medium, and large variances) as well as three different characteristic types(smaller the better, larger the better, nominal the best). By using the proposed PSI, the most similar animal PK profile compare to the target human PK profile can be obtained in the simulation studies. In addition, a case study represents differentiated results compare to existing simple statistical analysis methods(i.e., root mean squared error and quality loss). Conclusion: The proposed PSI can effectively estimate the level of similarity between animal, human PK profiles. By using these PSI results, we can reduce the number of animal experiments because we only focus on the significant animal representing a high PSI value.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) (No. NRF-2019R1F1A1060067).

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