Quality control of ELISA experiment

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From 1949, the College of American Pathologists (CAP) first began to study the clinical laboratory indoor quality control (QC). American scholars Levery and Jenning published the first article on laboratory indoor Control, the indoor quality control work of the clinical testing laboratory officially kicked off.
By the 1970s, laboratory quality control had entered a new stage—total quality management and the implementation of Good
Laboratory Parctice (GLP for short). In the late 1980s, the unified standard of GLP came into being and developed to the management stage of "certified laboratory".
The purpose of total quality management is to prevent errors. The purpose of statistical quality control in quality control charts is to detect errors.
Statistical laboratory quality control is an important part of total quality management.
This chapter mainly introduces the statistical laboratory quality control method of immunology test. Because ELISA is the most commonly used immunological test method in clinical practice, ELISA test is used as an example to introduce related issues.
The immunological quality control room of the Clinical Laboratory Center of the Ministry of Health has been conducting quality evaluation activities for hepatitis B marker testing nationwide since 1988. It has been using this set of quality evaluation methods and has continued to practice, improve and improve in practice. To develop an effective quality management path that suits China's national conditions.

5.1 Basic concepts

5.1.1 Quality Control (Quaility Control, QC)
Quality control is a management process that monitors the entire process, eliminates errors, prevents changes, and maintains the current status of standardization. This process is carried out through a feedback loop.
1) Determine the object of control;
2) Specify the standard (expected value) of the controlled object;
3) Develop or select control methods and means;
3) Measuring actual data;
4) Compare or compare the difference between the actual data and the expected value, and explain the reason for this difference. If the predetermined error range is exceeded, the alarm system sends a signal and the feedback channel is interrupted.
5) Take action to resolve differences. The means of restoring the original state (original standard state) come into play.
Quality control is mainly carried out using quality control charts. A quality control chart is a chart that compares the performance data of a certain test with the calculated expected "control limits". This performance data is selected in chronological order when it is carried out normally according to the regulations. Its purpose is to detect the "traceable" cause of the variation in the inspection process. The "reversible" error causes refer to other causes than random errors. "Control limit" is calculated by statistics, and we will introduce it in detail later (see
5.3. Indoor quality control procedures).

5.1.2 Errors Experimental errors are divided into three types: systematic errors, random errors and negligent errors.
Systematic error refers to a series of errors with the same tendency as the true value or target value, with obvious regularity, which can be repeated under certain conditions and can be prevented and corrected by quality control.
Random error, also known as accidental error, is an accidental and unpredictable error that is difficult to avoid and correct. The distribution of random errors in the inspection work conforms to the law of normal distribution.
Negligence error is a human responsibility error. It can be avoided by strengthening laboratory management and carrying out quality control.

5.1.3 In the normal distribution and standard deviation ELISA test, when the same sample is tested more than 20 times, you will find that this set of data (referred to as the absorbance value of the measurement result) is distributed on both sides of the mean, most of them are concentrated around the mean. If the measured value is plotted on the abscissa and the frequency of occurrence on the ordinate, a bell-shaped curve can be drawn. As shown in Figure 5-1, the mean is at the top of the bell, and the other values ​​are symmetrically distributed with the mean at the center. This is the normal distribution.

The area under the normal curve is called the probability, which is usually expressed by the mean (X) and standard deviation (SD) of the sample

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