Quality Management Model for Phase I Clinical Drug Trials:A Structural Equation Model

This study aimed to construct a quality management model for phase I clinical drug trials.A cross-sectional survey was conducted and data were collected from 604 respondents at 69 institutions in China engaged in phase I clinical drug trials.Exploratory and confirmatory factor analyses were used to develop the survey tool.Structural equation modeling was used to construct a quality management model for phase I clinical drug trials.The results showed that the final survey tool had good reliability and validity(Cronbach’sα=0.938,root mean square error of approximation=0.074,comparative fit index=0.962,and Tucker—Lewis index=0.955).The model included five dimensions:government regulation,industry management,medical institution management,research team management,and contract research organization(CRO)management.In total,22 measurement items were obtained.The structural equation model indicated government regulation,industry management,medical institution management,and CRO management significantly affected the quality of phase I clinical drug trials(β=0.195,β=0.331,β=0.279,andβ=−0.267,respectively;P<0.05).Research team management had no effect on the quality of trials(β=0.041,P=0.610).In conclusion,the model is valuable for identifying factors influencing phase I clinical drug trials and guiding quality management practices.

Stepwise Method Based on Confidence Bound and Information Incorporation for Identifying the Maximum Tolerable Dose

The primary goal of a phase I clinical trial is to find the maximum tolerable dose of a treatment. In this paper, we propose a new stepwise method based on confidence bound and information incorporation to determine the maximum tolerable dose among given dose levels. On the one hand, in order to avoid severe even fatal toxicity to occur and reduce the experimental subjects, the new method is executed from the lowest dose level, and then goes on in a stepwise fashion. On the other hand, in order to improve the accuracy of the recommendation, the final recommendation of the maximum tolerable dose is accomplished through the information incorporation of an additional experimental cohort at the same dose level. Furthermore, empirical simulation results show that the new method has some real advantages in comparison with the modified continual reassessment method.

A system for determining maximum tolerated dose in clinical trial

Toxicity study,especially in determining the maximum tolerated dose(MTD)in phase I clinical trial,is an important step in developing new life-saving drugs.In practice,toxicity levels may be categorised as binary grades,multiple grades,or in a more generalised case,continuous grades.In this study,we propose an overall MTD framework that includes all the aforementioned cases for a single toxicity outcome(response).The mechanism of determining MTD involves a function that is predetermined by user.Analytic properties of such a system are investigated and simu-lation studies are performed for various scenarios.The concept of the continual reassessment method(CRM)is also implied in the framework and Bayesian analysis,including Markov chain Monte Carlo(MCMC)methods are used in estimating the model parameters.