Stage 3 Collect data

In collecting data for assessing the strengths and weaknesses of PSM systems, the auditor can also make an initial judgment about the maturity of the program. The levels of system or program maturity can be broken down into three stages. 

The speed with which the data need to be compressed depends on the stage of data acquisition at which compression is desired. In intelligent sensors it may be necessary to do some preliminary data compression as the data are collected. Often data are collected for several days or weeks without any compression, and then stored into the company data archives. These data may be retrieved at a later stage for studying various aspects ol the process operation. 

Expert knowledge of the actors, in the organization at which the protocol is applied, is needed. They have to iteratively check the collected data and establish the consequences for the retrieved precursors. For the researcher himself, however, no specific training or skills are required to apply the 7-stages, which are laid down in a structured protocol. 

The second stage is data acquisition. This stage is entered when the operator starts the instrument. The instrument makes the first injection and signals the microcomputer via Intelink. After a delay proportional to the void volume of the column set, data are collected on a time basis (constant flow rate assumed) at the predetermined rate from each of the detectors selected, up to a maximum of three simultaneous detectors. VHien the sample run is complete, the instrument again signals the microcomputer which places the instrument in a hold state while it reads the operational parameters from the instrument for that sample and... 

The next stage of assessment is multidose tolerance (MDT) study. The objective of this study is to assess pharmacodynamic and pharmacokinetic effects and to collect data for any adverse event observed. For this assessment, a range of doses is administered with placebocontrol to healthy volunteers for 7-14 days. The intention of these studies is to assess any potential saturation of metabolism. 

At this step, validation of the process serves as the means of setting and/or evaluating control parameters as established during experimentation, development activities, and scale-up. The purpose of validation is to verify or authenticate that the process is capable of reproduction with results within specified parameters. Part of this validation is to collect data over the various processing stages. The validation protocol should be based upon data and information collected during the development activities of the product s life cycle. 

Particle bounce. When particles bounce off the collection surface, they may be carried to subsequent stages, where they may stick or again bounce off. The result is that subsequent stages collect more mass than is appropriate, and the inferred particle-size distribution is biased towards the smaller particles. Apparently, because of increasing velocity, particles that bounce off one stage continue to bounce off the subsequent stages and are finally collected on the afterfilter. As discussed below, such collection can severely limit the utility of afterfilter data. Typically, sticky substances are applied to impaction surfaces to reduce particle bounce. Compounds that can be "wicked" by the collected particles tend to be the most effective. 

In the process improvement study, what was actually done in the first stage of data collection was to gather information from one-half of a full 24 factorial (a 24 1 fractional factorial) augmented by four observations at the center of the experimental region (thereby providing both some coverage of the interior of the region, in addition to a view of some of its comers, and important replication as well). 

Today, a number of pharmaceutical companies dealing with HTS reach a turnover of more than 15 different assay systems a year, in which 300,000 samples or even more are tested. This confronts the scientist with more than 5,000,000 data points which point to the need for efficient automation at all stages of HTS, even in data collection, data quality control and analysis. Robots, especially large systems integrated with multiple peripheral devices, are prominent at present. 

The importance of defining mill categories adequately leads to the next hurdle in data collection. At what stage of processing should data be collected There are clear benefits from collecting data at the level of each unit process rather than for an entire manufacturing facility that is made up of many unit processes. One benefit of collecting data at the unit process level is that it becomes possible to examine... 

Collect data at the stages of the operation which will enable the organization to optimize and reach its goals and objectives from the computer processed information. 

It has been said that no science is established on a firm basis unless its generalizations can be expressed in terms of number, and it is the special province of mathematics to assist the investigator in finding numerical relations between phenomena. After experiment, then mathematics. While a science is in the experimental or observational stage, there is little scope for discerning numerical relations. It is only after the different workers have collected data that the mathematician is able to deduce the required generalization. Thus a Maxwell followed Faraday, and a Newton completed Kepler. 

The X-ray analysis system for the EMA is a wavelength dispersive spectrometer with gas proportional counter detectors. In the SEM, an energy dispersive X-ray spectrometer with a Si(Li) detector is used. The entire electron and X-ray optical systems are operated under a vacuum of about 10 torr. Modem systems are completely automated with computer control of the instmment parameters, specimen stage movement, data collection and data processing. 

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