Types and sources of data

The safety of medicines is under evaluation throughout the drug development cycle. This process starts before humans are exposed, and continues during the clinical development and post-marketing phases. Broadly, the safety of a medicine is tested in four phases, each of which produces different types of data. These are as follows  

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Table 1 Types and Sources of Target Data Used m the Optimization of Empirical Force Field Parameters...

To properly use failure rate data, the engineer or risk analyst must have an understanding of failure rates, their origin and limitations. This chapter discusses the types and source of failure rate data, the failure model used in computations, the confidence, tolerance and uncertainties in the development of failure rates and taxonomies which can store the data and influence their derivation. 

The system is illustrated in Figure 1. Inputs are a data base including pilot, commercial, and literature sources. The type and extent of data are compatible with plant design objectives. Although the contribution of all data sources is significant, the role of a pilot test facility is central to the development of sound technology. 

HEADER - contains four Digital Object Identifiers (DOIs) for SELF name, property type, original source of data, and chemical system... 

Many of the text-books e.g. ref. 250) and sources of data e.g. ref. 291) listed in earlier sections describe the applications of thermodynamic data, but there are a number of books concerned mainly with physicochemical calculations which also provide examples of the derivation of scientifically and technologically important data by means of thermodynamics. Thus Smith s book Chemical Thermodynamics, A Problems Approach , which is of degree level, relates theory to worked examples, and Guggenheim and Prue s Physicochemical Calculations is of this type. ... 

This article presents the most recent development of the MC-SYM research project at the University of Montreal. MC-SYM is a joint effort between the computer science and biochemistry departments to develop computational methods in RNA three-dimensional structure determination. A first MC-SYM prototype was reported and released in 1991. Since then, the program has been extensively tested and used to determine RNA three-dimensional structures from many different types and sources of structural data. Table 1 shows a list of the main publications " in which the use of MC-SYM was important. The program is available by anonymous FTP and on the WEB. ... 

We would like to provide means of expressing as many different types and pieces of data as possible. For those attributes of molecules which admit numerical values (such as the solubility or the Gibbs energy), how do we handle conflicting data from different literature sources, and how do we keep track of the conditions and necessary qualifications of each datum We can provide the ability to store more than one value for each attribute, in the form of a list of data objects. The role of the datum object is to encapsulate all the bookkeeping and reference information accompanying a numerical value (Table 6). 

A variety of experimental techniques have been employed to research the material of this chapter, many of which we shall not even mention. For example, pressure as well as temperature has been used as an experimental variable to study volume effects. Dielectric constants, indices of refraction, and nuclear magnetic resonsance (NMR) spectra are used, as well as mechanical relaxations, to monitor the onset of the glassy state. X-ray, electron, and neutron diffraction are used to elucidate structure along with electron microscopy. It would take us too far afield to trace all these different techniques and the results obtained from each, so we restrict ourselves to discussing only a few types of experimental data. Our failure to mention all sources of data does not imply that these other techniques have not been employed to good advantage in the study of the topics contained herein. 

This chapter has only scratched the surface of the multitude of databases and data reviews that are now available. For instance, more than 100 materials databases of many kinds are listed by Wawrousek et al. (1989), in an article published by one of the major repositories of such databases. More and more of them are accessible via the internet. The most comprehensive recent overview of Electronic access to factual materials information the state of the art is by Westbrook et al. (1995), This highly informative essay includes a taxonomy of materials information , focusing on the many different property considerations and property types which an investigator can be concerned with. Special attention is paid to mechanical properties. The authors focus also on the quality and relutbility of data, quality of source, reproducibility, evaluation status, etc., all come into this, and alarmingly. 

The study performed by Burns and Roe (BSR) shows that valve failures constitute the component category most responsible for the shutdown of PWR and BWR plants. This Investigation, contracted with SNL for DOE, identified the principal types and causes of valve failures that led to plant trips for the period from 12/72 to 12/78. The primary sources of data for the report were searches of the data base, the monthly Gray Books, Nuclear Power Experience publications, as well as discussions with utilities, valve manufacturers, and suppliers. 

SAIC provided much of the data used in this book from its proprietary files of previously analyzed and selected information. Since these data were primarily from the nuclear power industry, a literature search and industry survey described in Chapter 4 were conducted to locate other sources of data specific to the process equipment types in the CCPS Taxonomy. Candidate data resources identified through this effort were reviewed, and the appropriate ones were selected. Applicable failure rate data were extracted from them for the CCPS Generic Failure Rate Data Base. The resources that provided failure information are listed in Table 5.1 with data reference numbers used in the data tables to show where the data originated. 

Creep modeling A stress-strain diagram is a significant source of data for a material. In metals, for example, most of the needed data for mechanical property considerations are obtained from a stress-strain diagram. In plastic, however, the viscoelasticity causes an initial deformation at a specific load and temperature and is followed by a continuous increase in strain under identical test conditions until the product is either dimensionally out of tolerance or fails in rupture as a result of excessive deformation. This type of an occurrence can be explained with the aid of the Maxwell model shown in Fig. 2-24. 

The application area is so large that no cookbook advice would be useful. Each type of application must have the potential failure evaluated, the economics calculated, the degree of assurance of performance set, the extent of required testing determined, and the product designed and evaluated to meet the criteria established. There are sources of data available on which to base the approaches to the requirements, but the final combination of factors must be determined by the designer. 

Expert opinion is a source, frequently elicited by survey, that is used to obtain information where no or few data are available. For example, in our experience with a multicountry evaluation of health care resource utilization in atrial fibrillation, very few country-specific published data were available on this subject. Thus the decision-analytic model was supplemented with data from a physician expert panel survey to determine initial management approach (rate control vs. cardioversion) first-, second-, and third-line agents doses and durations of therapy type and frequency of studies that would be performed to initiate and monitor therapy type and frequency of adverse events, by body system and the resources used to manage them place of treatment and adverse consequences of lack of atrial fibrillation control and cost of these consequences, for example, stroke, congestive heart failure. This method may also be used in testing the robustness of the analysis [30]. 

Sources of data on costs were discussed in Chapter 6 and materials of construction in Chapter 7. This chapter covers sources of information on manufacturing processes and physical properties and the estimation of physical property data. Information on the types of equipment (unit operations) used in chemical process plants is given in Volume 2, and in the Chapters concerned with equipment selection and design in this Volume, Chapters 10, 11 and 12. 

Facts are the fuel an investigation needs to reach a successful conclusion. This chapter addresses the practical considerations of data-gathering activities. It describes types of data, sources of data, data-gathering tools, and techniques. 

In general, we can speak of two specific types of operations using microcomputers in sensory analysis as data acquisition tools. The first would be in a passive mode, that is the system would be used to collect data as entered after the actual evaluation has taken place and the data has been collected on some other form, for example, a paper ballot. In this case the microcomputer is being used as a secondary source of data acquisition. The primary one being the paper ballot. The second mode of operation would be using the microcomputer as the primary and sole data acquisition medium. We would then be relying upon the computer to handle not only the collation and storage of the data but also the interactive means by which the analyst collects data from the panelists. 

The data and discussion above suggest that differences exist in the organic residues of the Paleozoic Formations of the Mt. Union area as functions of type and amount of source material, rate of deposition, distance from source, and preservative sedimentary conditions. Carbohydrate residues are more abundant in the Silurian and Devonian than in the underlying Ordovician, which may reflect the increase of larger terrestrial and littoral plants in the Silurian and Devonian. 

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