您當前的位置：檢測資訊 > 科研開發
嘉峪檢測網 2025-04-29 17:59
本期文章討論了滿足歐洲數據可靠性要求的實踐。
A HPLC laboratory for pharmaceutical quality control is used as an example in which data for the batch release of a finished medicinal product is generated. A schematic representation of the underlying process is shown in Figure 1.
以用于藥品質量控制的HPLC實驗室為例子，其中產生了藥品的批次放行數據。底層流程的示意圖如圖1所示。
Figure 1 Quality control and batch release
圖1 質量控制和批放行
What types of data (in accordance with the WHO guidance) are collected in a chromatography laboratory? The most important types are listed below:
色譜實驗室需要收集哪些類型的數據（根據WHO指南）？最重要的類型如下：
● data from the tested batch and data on personnel who carry out and control the testing process
● 測試批次的數據以及執行和控制測試過程的人員的數據
● sampling and sample storage data, records and observations
● 取樣和樣品儲存數據、記錄和觀察
● weighing and sample preparation, standards and reagents used
● 稱重和樣品制備，使用的標準品和試劑
● qualification and calibration data for the pipettes and balances used
● 所使用的移液器和天平的確認和校準數據
● qualification data for all of the devices used
● 所有使用的設備的確認數據
● instrument control data (detector wavelength range, flow, temperature, etc.)
● 儀器控制數據（檢測器波長范圍、流量、溫度等）
● sequence data in full
● 序列數據完整
● data to be recorded (e. g. data rate, integration parameters, etc.)
● 要記錄的數據(例如：數據速率、積分參數等)
● chromatography testing data (initial electronic data, peak areas)
● 色譜檢測數據（初始電子數據、峰面積）
● processed data from chromatography testing (processed electronic data)
● 從色譜測試中處理的數據（處理的電子數據）
● measuring process and device-specific calibrations
● 測量過程和設備特定的校準
● device-specific calculations
● 特定于設備的計算
● peak areas after integration
● 積分后的峰面積
● HPLC calibration data
● HPLC校準數據
● calculation data (software-based or completed manually)
● 計算數據（基于軟件或手工完成）
● trend analyses
● 趨勢分析
● all system suitability test results
● 所有系統適用性測試結果
● reports generated from electronic data (sample-list printouts, chromatograms, etc.)
● 從電子數據生成的報告（樣本列表打印輸出、色譜圖等）
● audit trail data and all deviations and changes
● 審計追蹤數據和所有偏差和變更
● documented observations
● 記錄到的觀察
● if applicable, calculations carried out using external software (LIMS, Excel) = derived data, results (reportable result), evaluation (with OOS, OOE, OOT)
● 如果適用，使用外部軟件（LIMS, Excel）進行計算=導出的數據、結果（可報告的結果）、評估（使用OOS、OOE、OOT）
All of this data should comply with the ALCOA principles – and, in an ideal situation, the ALCOA plus principles
所有這些數據都應符合ALCOA原則——在理想情況下，還應符合ALCOA+原則
Figure 2 ALCOA principles of data integrity
圖2 ALCOA數據可靠性原則
A number of these requirements are already contained in the EUGMP Guidelines, i.e. they were introduced before the recent publication of data integrity specifications.
其中一些要求已經包含在歐盟GMP指南中，即它們是在最近發布數據可靠性規范之前提出的。
Key aspects of data integrity during the generation of data are examined below. It will be shown that the definition of data is of major importance for a project. The difference between raw data and metadata is not discussed here because the differentiation is difficult. The general term data is used instead. This approach is also taken by the FDA.
下面將研究數據生成過程中數據可靠性的關鍵方面。這表明，數據的定義對于一個項目是非常重要的。這里不討論原始數據和元數據之間的區別，因為很難區分。取而代之的是通用術語數據。FDA也采用了這種方法。
A number of conflict situations that often arise in relation to data integrity requirements are examined below.
下面將審查與數據可靠性要求有關的一些經常出現的沖突情況。
● Access to the key functions of the control and evaluation software (e.g. switching off the audit trail, changing the system time) must be restricted, e.g. limited to IT personnel.
● 必須限制訪問控制和評估軟件的關鍵功能（如關閉審計跟蹤、更改系統時間），如僅限于IT人員。
● Access to control and evaluation software must be based on individual login accounts. Group access or anonymous logins should not be possible. User privileges should be limited to the individual job profile.
● 訪問控制和評估軟件必須基于個人登錄帳戶。組訪問或匿名登錄應該避免。用戶權限應該僅限于單個崗位職責。
● A complete qualification and validation of all computers and the control and evaluation systems is absolutely essential.
● 所有計算機、控制和評估系統的完全確認和驗證是絕對必要的。
● A review of audit trails should be carried out before data-based decisions are made. This must be completed before the project is concluded and/or the collected data is used for batch release. Actions must be defined and/or put in place for deviations so that an appropriate investigation can be initiated and completed.
● 在做出基于數據的決策之前，應進行審計追蹤的審查。這必須在項目結束和/或收集的數據用于批次放行之前完成。必須定義和/或對偏差采取行動，以便啟動和完成適當的調查。
● Test runs and the generation of data for testing purposes are not permitted during testing prior to batch or raw material release if these processes are not carried out in accordance with defined protocols during qualification, validation or the system suitability test.
● 如果在確認、驗證或系統適用性測試期間，這些過程沒有按照規定的方案進行，則在批次或原料放行前的測試期間，不允許測試運行和測試數據的生成。
● There has to be a reason for every subsequent modification, and the reason must be completely and transparently documented. This applies in particular to reintegration and generally to manual integration and changes to manual data entries such as calculation factors, weights and quantities.
● 每一個后續的修改都必須有一個原因，并且這個原因必須被完整且透明地記錄下來。這特別適用于重新積分，一般適用于手動積分和手動數據條目的更改，如計算因子、重量和數量。
● There has to be a reason for every repeated analysis, and the reason must be completely and transparently documented. This type of situation is limited to the investigation of OOS, OOE and OOT results as well as deviations, e.g. failed injections. Repeats can also be indicated when a root cause analysis is carried out. For all repeats, prospectively defined processes must be in place and documentation must be mandatory.
● 每一個重復的分析都必須有一個原因，并且原因必須完整和透明地記錄下來。這種情況僅限于對OOS、OOE和OOT結果以及偏差的調查，例如進樣失敗。當執行根本原因分析時，還可以進行重復。對于所有重復，預先定義的過程必須到位，文檔必須是強制性的。
● If data lacks robustness and accuracy, e.g. due to an incomplete, unsuitable or old validation or calibration, it may not be used. This can be the case when response factors are used that represent device-specific values, but have not been established as such, or when response factors are not checked and corrected when a device is replaced.
● 如果數據缺乏穩健性和準確性，例如，由于不完整、不合適或舊的驗證或校準，它可能不被使用。這種情況可能發生在響應因子被用來表示設備特定的值，但還沒有建立成這樣的情況下，或者當設備被替換時響應因子沒有被檢查和校正。
來源：GMP干貨
