YY/T 1737-2020Analytical method for bioburden control level of medical device (English PDF)

3.1 colony forming unit; CFU

The microbial colony formed by the reproduction of one or several microorganisms after microbial culture, abbreviated as CFU, and usually expressed in number.

3.2 Correction factor

Used to compensate for data that cannot be fully collected from product and/or microbial culture.

3.3 Alert level

The microbial content level set by the user for products that require microbial control.

When the test results exceed this level, a monitoring program shall be initiated to track the microbial contamination of the product.

3.4 Acting level

The microbial content level set by the user for products that require microbial control.

When the test results exceed this level, an investigation procedure shall be initiated to investigate the microbial contamination of the product.

5.1 Risks associated with the sterilization method of the product

5.1.1 If the product is sterilized by overkill, from the perspective of sterilization, as long as the bioburden of the product does not exceed the spore count on the biological indicator (BI) for sterilization and the resistance does not exceed the D value of the BI, it can be effectively killed.

5.1.2 When a combined bioburden and biological indicator sterilization method is used, the bioburden shall not exceed the predetermined limit and the resistance shall not exceed the D value of the BI.

Among them, surface contact device is divided as per. skin contact, mucosal contact and damaged surface contact; external access device is divided as per. indirect blood contact, tissue/bone/dentin contact, circulating blood contact; implantable device is divided as per. tissue/bone contact and blood contact.

6.1 Documents

Manufacturers shall establish product bioburden monitoring documents.

6.2 Monitoring frequency

Sampling and bioburden testing can be performed at regular intervals or according to production frequency. The selection of bioburden monitoring frequency may take into account factors such as product material characteristics, production process characteristics, production frequency, seasonal and environmental changes, and sterilization methods.

6.3 Sampling

6.3.1 Select a representative product (or equivalent product) from the product family for bioburden testing. If the product is not available (e.g., not produced during the specified testing period), an acceptable alternative product (equivalent product) for the product family shall be defined in the documentation to represent the normal production process for testing.

6.3.2 Routine monitoring of bioburden levels typically uses 3 ~ 10 samples. The production and treatment of samples shall be representative of normal production.

Note. Samples may be selected from products rejected due to other production quality issues, provided that the rejected samples are representative of the regular products and have no impact on the bioburden test results, and the samples are initially packaged according to the regular production process for bioburden testing.

6.4 Test

Follow relevant provisions of GB/T 19973.1.

6.5 Microbial culture (medium selection and culture conditions)

Follow relevant provisions of GB/T 19973.1.

6.6 Microbial identification

Microbiological identification should be considered during initial validation and when the bioburden exceeds the acting level and/or the alert level. The identification of microorganisms in bioburden shall first consider the identification of genus and species, and shall be carried out in accordance with the relevant provisions of GB/T 19973.1.

6.7 Test report

6.7.1 The bioburden test report should include the following.

a) date of testing;

b) product description; c) correction factor.

6.7.2 The final result of the bioburden test is the average of all the tested products in the same batch (after introducing the correction factor for bioburden).

6.8 Analysis

6.8.1 Alert level and acting level should be specified for each product or product family.

Commonly used statistical methods include standard deviation method, percentile method, probability chart method and control chart (range) method. Appendix A provides examples of statistical methods for alert level and acting level.

6.8.2 Alert level and acting level should be based on historical data.

6.8.3 In the absence of historical data, Appendix B provides examples of establishing alert level and acting level in the absence of historical data.

A.1 Standard deviation method

The standard deviation method has always been a traditional method for data analysis. Table A.1 gives examples of using this method.

A.2 Percentile method

Percentile calculation is an alternative method for establishing alert level and acting level. Percentile calculation makes no distributional assumptions about the underlying data set and can be used for both normally and non-normally distributed data. It can be used directly in most spreadsheet software programs (for example. the function "Percentile.EXC" in EXCEL).

A.3 Probability graph method

A probability graph can be regarded as a graphical depiction of the percentile calculation. The X-axis of the probability graph represents the original observation, and the Y-axis represents its corresponding percentage. Traditionally, the probability graph is used to check the normality of data, but it can also be used to establish the alert level and the acting level using the 95th and 99th percentiles.

Figure A.1 - Probability graph obtained from the data in Table A.2 Calculations. The probability graph can be prepared manually using probability graph paper or by computer using a statistical software program. Figure A.1 shows an example of the probability graph. This graph is created using the data set in Table A.2.The alert level and the acting level are established at the 95% and 99% points in the graph. In this example, the alert level is approximately 94.1 CFU/device and the acting level is approximately 112.7 CFU/device.

Advantages and disadvantages. In addition to being based on process data, probability graph provides a graphical visualization of data, allowing the analyst to determine the distribution of data. Probability graph can be found in most statistical software programs. Probability graph has limitations in data analysis. When the data are clustered at a few points, the probability graph should not be used.

A.4 Control chart (range) method

The use of drawing techniques offers several advantages in the analysis of monitoring data. They are prepared either manually or using statistical software. Most charts are individual value control charts that present time versus each test value. The test value can be expressed in CFU/device. The control chart includes individual value, average value, alert level and acting level. Graphs used for bioburden monitoring data differ from conventional control charts in that the lower limit of the test value is fixed at zero, and graphs used for bioburden monitoring data do not need to be specifically displayed.

Control chart uses process data to calculate the average value and control limits for the process. Therefore, the values displayed on the control chart reflect the actual process performance, and by viewing the data based on these values, analysts can easily identify process variations that may require further investigation.