Process Model Development

Modeling of absorption process of apomine. A simple Lrst-onder absorption model might not be applicable in this case. Thus, several absorption models were tested during model development process, including... 

Some factors or covariates may cause deviations from the population typical value generated from system models so that each individual patient may have different PK/PD/disease progression profiles. The relevant covariate effects on drug/disease model parameters are identified in the model development process. Clinical trial simulations should make use of input/output models incorporating... 

To compare and evaluate different kinds of models created during the model development process graphical and statistical methods should be applied. A good description of the model building process can be found elsewhere [14]. 

Finally, Model Development Process Objects [248] describes the (work) process of model development, introducing concepts for the description of activities, goals, and decisions. 

It has proven useful to abstract these proprietary models into a neutral model representation (cf. Fig. 5.21) to allow functionality to be developed without the need to consider the specific tools with which these models have been built. This neutral model representation is used as a substitute for the incompatible native model implementations in the sense of metadata. Such metadata are described by an object model and cover the structure of the model (e.g., blocks and their connectivity) as well as its behavior (e.g., variables denoting process properties and equations representing relations among properties). It should be noted, that this neutral representation is an abstraction and not a complete translation. The actual model development process as well as the step of computing a model is still based on the original implementation of the model rather than on its abstraction stored in ROME. Otherwise, it would not be possible to reuse the evaluation or solution functionality of the original model that is provided by the respective process modeling environment. 

The modeling toolkit ModKit aims at simplifying the model development process by providing reusable model building blocks [52]. Further, ModKit provides interactive support for the user during the assembly phase of the model building blocks. 

There are a lot of tool results to be found in this book and the tool construction knowledge, presented here, is rather comprehensive. Tool construction is the second global goal of IMPROVE, besides modeling development processes. As we have seen, these two global aspects even do interact. 

Obviously, one of the key tasks of a pharmacometrics service is the development of pharmacokinetic and pharmacodynamic models that serve as a mathematical representation of physiologic or pharmacologic phenomena. This is also one of the main activities that create a mockery of cost and schedule estimates. The complexity and scope of a pharmacometric model are limited only by the imagination, literature access, and computer resources of the pharmacometrician. Consequently, an effective model development process is one in which the extent of achievable... 

Simulation has emerged as an important tool for extrapolating from scenarios that generated the data for model development activities into scenarios of potential interest for the drug development program (15). Similar to the model development process, effectiveness in the case of simulations is the correspondence between the model and reality. Efficiency hinges on the applicability of the results as the target scenarios step outside the boundaries of the initial model. Here we need to ask about the extensibility of the simulation results and how broadly applicable the results are. 

Models are not static—they change over time as more data and experience with the drug are accumulated. Basic assumptions made about a model may later be shown to be inaccurate. Hence, a more comprehensive model development process is ... 

One goal of population pharmacokinetic models is to relate subject-specific characteristics or covariates, e.g., age, weight, or race, to individual pharmacokinetic parameters, such as clearance. There are many different methods to determine whether such a relationship exists, some of which were discussed previously in the chapter, and they can be characterized as either manual or automated in nature. With manual methods, the user controls the model development process. In contrast, automated methods proceed based on an algorithm defined by the user a priori and a computer, not the user, controls the model development process. Consequently, the automated methods are generally considered somewhat less subjective than manual procedures. The advantage of the automated method is its supposed lack of bias and ability to rapidly test many different models. The advantage of the manual method is that the user... 

Today, good modeling practices dictate that a data analysis plan (DAP) be written prior to any modeling being conducted and prior to any unblinding of the data. The reason being that model credibility is increased to outside reviewers when there is impartiality in the model development process. The DAP essentially provides a blueprint for the analysis. It should provide details... 

In summary, tobramycin pharmacokinetics were best characterized with a 2-compartment model where CL was proportional to CrCL and VI was proportional to body weight. BSV in CL was 29% with 13% variability across occasions. Residual variability was small, 14%, which compares well to assay variability of <7.5%. The model was robust to estimation algorithm and was shown to accurately predict an internally derived validation data set not used in the model development process. 

Chapter 1 closely reviews the model development process. After a formal foundation of bond graphs, principles and fundamental concepts of port-based physical systems modelling in terms of bond graphs are pointed out and are discussed in a clarifying way that may help avoid model developers to fall into traps, to overlook assumptions and the context dependency of models, or to mix concepts which may give rise to confusions, e.g. with regard to ideal concepts and physical components. A key issue of Chapter 1 is that it emphasises the distinction between configuration structure, physical stiucture, and conceptual structure. 

Fig. 1. Right side of the V-model development process focused on safety...

In support of thorough and auditable testing of the models, a Test Plan was developed. Firstly, as part of the models development process, all models were reviewed by domain experts at different stages of the project. 

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