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A Dynamic Model for GMP Compliance and Regulatory Science
  • Purpose To propose a dynamic model designed to investigate the underlying principles of regulatory science and assess the effectiveness of pharmaceutical GMP regulation. Methods A dynamic model for the state of compliance of a pharmaceutical manufacturing firm is constructed by using a generalized Ornstein-Uhlenbeck equation. The model is based on quantitative characterization of principles of proportionality, transparency and consistency, and regulatory effectiveness as measured by efficiency, cost and quality. The dynamic model is solved by numerical simulation. Results The dynamic model is capable of characterizing a wide range of compliance behaviors and regulatory actions, including the regression and heightening of compliance vigilance, and the scheduling of frequency and concurrency of regulatory actions. Quantitative relationships are established between the principles of proportionality, transparency and consistency, and the basic measures of regulatory effectiveness in terms of efficiency, cost and quality. Conclusions The compliance behaviors and the regulatory actions can be quantitatively characterized by a dynamic model, and this in turn suggests that proportionality, transparency and consistency can serve as fundamental concepts, and efficiency, cost and quality can serve as basic measures for regulatory science.

A Dynamic Model for GMP Compliance and Regulatory Science

研究领域: Purpose To propose a dynamic model designed to investigate the underlying principles of regulatory science and assess the effectiveness of pharmaceutical GMP regulation. Methods A dynamic model for the state of compliance of a pharmaceutical manufacturing firm is constructed by using a generalized Ornstein-Uhlenbeck equation. The model is based on quantitative characterization of principles of proportionality, transparency and consistency, and regulatory effectiveness as measured by efficiency, cost and quality. The dynamic model is solved by numerical simulation. Results The dynamic model is capable of characterizing a wide range of compliance behaviors and regulatory actions, including the regression and heightening of compliance vigilance, and the scheduling of frequency and concurrency of regulatory actions. Quantitative relationships are established between the principles of proportionality, transparency and consistency, and the basic measures of regulatory effectiveness in terms of efficiency, cost and quality. Conclusions The compliance behaviors and the regulatory actions can be quantitatively characterized by a dynamic model, and this in turn suggests that proportionality, transparency and consistency can serve as fundamental concepts, and efficiency, cost and quality can serve as basic measures for regulatory science.