Study design adaptive designs

Annex XI also emphasizes that study designs may be adapted provided that they are adequate for the purpose of classification and labelling and/or risk assessment. This may be taken to include previous studies conducted to other guidelines, including guidelines that have been superseded. 

In the case study, the adaptive model-based approach is designed on the basis of a reduced model of the phenol-formaldehyde reaction introduced in the Chap. 2. Noticeably, the results show that the model-based control scheme achieves very good performance even when a strongly simplified mathematical model of the reactive system is adopted for the design. 

This chapter introduces basic concepts in statistical analysis that are of relevance to describing and analyzing the data that are collected in clinical trials, the hallmark of new drug development. (Statistical analysis in nonclinical studies was addressed earlier in Chapter 4.) This chapter therefore sets the scene for more detailed discussion of the determination of statistical significance via the process of hypothesis testing in Chapter 7, evaluation of clinical significance via the calculation of confidence intervals in Chapter 8, and discussions of adaptive designs and of noninferiority/equivalence trials in Chapter 11. 

Three comments are appropriate here. First, consideration of the traditional clinical trial design that has been the focus of attention up until this chapter is extremely worthwhile and instructive It has facilitated the introduction of fundamental design, methodology, and statistical concepts, and it will be an influential player in pharmaceutical drug development for many years to come. Second, the simple observation that the adaptive design may seem different does not in itself make it less valid, less valuable, or less important. Third, statistical approaches that are suitable for adaptive designs are, as yet, less well developed than they are for other study designs. 

Flexibility and adaptability The ability to adapt to changes in research study parameters and timelines is important to understanding the dynamic nature of the drug discovery and development process. A CSO needs to be able to interact effectively with a client to modify a study design or an ongoing research study. 

The success of a liquid-liquid extraction process depends on the selection of the most appropriate solvent (Lo et al., 1983). This case study examines the design of a solvent for the extraction of acetic acid from water. Lo et al. s (1983) procedure for solvent selection was adapted for interactive design use. 

J. M. Heyd and B. P. Carlin, Adaptive design improvements in the continual reassessment method for phase I studies. Stat Med 18 1307-1321 (1999). 

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