Protocol statistical methods

Satellite pharmacokinetic or special study groups Deviations from original study protocol Statistical methods Observations and times Clinical signs Body weights Food consumption Flematology Clinical chemistry Organ weights... 

Protocol analysis. Protocol analysis is the process of capturing, decoding, and interpreting electronic traffic. The protocol analysis method of network intrusion detection involves the analysis of data captured during transactions between two or more systems or devices, and the evaluation of these data to identify unusual activity and potential problems. Once a problem is isolated and recorded, problems or potential threats can be linked to pieces of hardware or software. Sophisticated protocol analysis will also provide statistics and trend information on the captured traffic. 

Once the design is established, a protocol will be prepared. All the critical design features and the types of observations to be made, and even the statistical methods to be used to analyze results, are specified in advance. Toxicologists, chemists, pathologists, and statisticians are typically involved in drafting the protocol. 

A class of statistical methods frequently used to analyze kinetic and thermodynamic data. Most of these methods require a preliminary estimate of the constants followed by cycles of iterative calculations that converge on a final value(s). Cleland has presented a protocol for the statistical estimation of kinetic data. A nonlinear analysis has also been applied to progress curves. ... 

The date of approval of the protocol by the sponsor and the dated signature of the study director A statement of the proposed statistical methods to be used... 

It is important to describe statistical methods in the protocol. This will avoid suspicions that statistical methods were selected after study data were available and that selection was based on a desired end result. 

It is good practice to pre-specify in the protocol, or certainly in the statistical analysis plan, the statistical method to be used for analysis for each of the endpoints within the confirmatory part of the trial. This avoids the potential for bias at the analysis stage, which could arise if a method were chosen, for example, which maximised the treatment difference. As a consequence changing the method of analysis following unblinding of the study in an unplanned way, even if there seem sound statistical reasons for doing so, is problematic. Such a switch could only be supported if there was a clear algorithm contained within the statistical analysis plan which specified the rules for the switch. An example of this would be as follows ... 

The Statistical Methods section of the protocol sets down the main aspects of both design and analysis. In particular this section should contain ... 

The statistical analysis plan (SAP) is a more detailed elaboration of the statistical methods of analysis contained in the protocol. The SAP is written as the trial... 

The basic criterion for successful validation was that a method should come within 25% of the "true value" at the 95% confidence level. To meet this criterion, the protocol for experimental testing and method validation was established with a firm statistical basis. A statistical protocol provided methods of data analysis that allowed the accuracy criterion to be evaluated with statistical parameters estimated from the laboratory test data. It also gave a means to evaluate precision and bias, independently and in combination, to determine the accuracy of sampling and analytical methods. The substances studied in the second phase of the study are summarized in Table I. 

The FDA guidelines establish, first, that the stabihty study protocol must describe how the stabihty study is designed and carried out and, second, the statistical methods to be used to analyze the data. The design of a stabihty study is aimed at establishing an expiration dating period. The expiration dating period is based on testing on a... 

Optimization techniques may be classified as parametric statistical methods and nonparametric search methods. Parametric statistical methods, usually employed for optimization, are full factorial designs, half factorial designs, simplex designs, and Lagrangian multiple regression analysis [21]. Parametric methods are best suited for formula optimization in the early stages of product development. Constraint analysis, described previously, is used to simplify the testing protocol and the analysis of experimental results. 

We can easily quantify measurement error due to existence of a well-developed approach to analytical methods and laboratory QC protocols. Statistically expressed accuracy and precision of an analytical method are the primary indicators of measurement error. However, no matter how accurate and precise the analysis may be, qualitative factors, such as errors in data interpretation, sample management, and analytical methodology, will increase the overall analytical error or even render results unusable. These qualitative laboratory errors that are usually made due to negligence or lack of information may arise from any of the following actions ... 

The statistical process sets up a sampling protocol that is constructed to provide an unbiased estimate of the summary statistic that defines the standard, say the annual mean or annual 95th percentile. The statistical methods provide an estimate of the standard error about this estimate of the summary statistic. Usually, the sampling regime... 

The FDA s statisticians expect that each clinical protocol submitted will include a description of any planned interim analyses of the data, including the anticipated monitoring procedures, the variables to be analyzed, and the statistical methods to be applied. The latter includes the choice of significance level for each interim analysis, the frequency of analysis, and a declaration of the circumstances under which the study would be terminated before the planned number of patients have been entered into the study. 

Methods for identifying and handling of possible outlier data should be specified in the protocol. Medical or pharmacokinetic explanations for such observations should be sought and discussed. As outliers may be indicative of product failure, post hoc deletion of outlier values is generally discouraged. An approach to dealing with data containing outliers is to apply distribution-free (non-parametric), statistical methods (72). 

If the distribution of log-transformed data is not normal, non-parametric statistical methods can be considered. The justification of the intent to use non-parametric statistical methods should be included a priori in the protocol. 

Results of all measured and calculated pharmacokinetic parameters should be tabulated for each subject-formulation combination together with descriptive statistics. The statistical report should be sufficiently detailed to enable the statistical analyses to be repeated if necessary. If the statistical methods applied deviate from those specified in the trial protocol, the reasons for the deviations should be stated. 

Several crystallization-screening protocols have been developed over the past decade to help identify initial crystallization conditions. These include footprint screening (Sutra et al., 1992), sparse matrix sampling (Jancarik and Kim, 1991), statistical methods (Carter and Carter, 1979), and MON-48 (Shieh et al., 1991). Reagent kits for some of these screens are now commercially available (Hampton Research [www.hamptonresearch.com], Emerald BioStructures [www.emeraldbio-structures.com]) and are commonly used in the laboratory. 

A stability protocol should describe not only how the stability study is to be designed and carried out but also the statistical method to be used in analyzing the data. This section describes an acceptable statistical approach to the analysis of stability data and the specific features of the stability study that are pertinent to the analysis. In general, an expiration dating or retest period should be determined on the basis of statistical analysis of observed long-term data. Limited extrapolation of the real-time data beyond the observed range to extend the expiration dating or retest period at approval time may be considered if it is supported by the statistical analysis of real-time data, satisfactory accelerated data, and other nonprimary stability data. 

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