Audit the accuracy and completeness of data reported by the facility for the product. Not every CMC data summary must be audited to accomplish this objective. The inspectional strategy may select key data sets from drug development (e.g., formulation development, Stage 1 of process validation) or randomly select data filed in the application. Generally, data on finished product stability, dissolution, content uniformity, and API impurity are good candidates for this audit.
In addition to summary tables, applicants typically submit additional testing for the finished product’s performance and physicochemical attributes. During the inspection, compare raw data—hardcopy or electronic—such as chromatograms, spectrograms, laboratory analyst notebooks, and additional information from the laboratory with summary data filed in the CMC section. Raw data files should support a conclusion that the data/information reported by the site are complete and accurate. Examples of data integrity concerns include failure to scientifically justify not reporting relevant data, such as aberrant test results or absences in a submitted chromatographic sequence.
When data discrepancies are observed, identify firm personnel involved. Determine which actions or inactions contributed to the data integrity problem and whether corrective actions were or are to be taken. Also determine whether data that should have been reported in the application were not reported. For example, did the firm:
Substitute passing data (i.e., within specification or otherwise favorable) for failing data (i.e., out of specification or unfavorable) without a sufficient investigation and resolution of the discrepancy?
The investigators should clearly indicate in the EIR whether their findings call into question the reliability of the submitted data. Specific data/information filed in the application should be referenced, when possible. It is essential that the ORA division notify OPF of data reliability concerns promptly to trigger an immediate evaluation of the impact on the application. If such situations are observed, thoroughly document the unreliable data (see III.2.B, Completion of the Establishment Inspection Report).
检查员应在EIR中明确指出他们的发现是否会对所提交数据的可靠性产生疑问。应尽可能援引到申请中提交的具体数据/信息。地区办公室应立即通知OPF（工艺和设施办公室）关于数据可靠性的问题，激活对申请真实性影响的即时评估。如果观察到这种情况，应彻底记录不可靠数据（参见III.2.B，企业检查报告的完成情况）。
识林点评：检查中发现了严重的问题，会影响产品批准的进度，数据可靠性通常被视为这类缺陷。
If a pattern of data reliability issues is identified during a PAI, the investigator should consider expanding the coverage to surveillance of marketed products manufactured in the facility using compliance program 7356.002. If data reliability issues are documented for other products during an expanded inspection, this suggests a broader pattern that implicates all products manufactured at the facility. If so, ORA should consider submitting a recommendation that CDER consider invoking the Application Integrity Policy (AIP) or that a for-cause inspection be planned to further define the scope of the data reliability issues. Contact information and procedures for OC’s Office of Manufacturing Quality (OC/OMQ) are on the AIP website.
Related regulations for finished pharmaceuticals: 21 CFR 314.50(d) requires that the CMC section include “data and information in sufficient detail to permit the agency to make a knowledgeable judgment about whether to approve the application.” Several CGMP regulations require laboratory data to be collected and maintained, including 21 CFR 211.160 (General Requirements), 211.165 (Testing and Release for Distribution), 211.166 (Stability Testing), and 211.167 (Special Testing Requirements).
Related guidance for APIs: Several ICH Q7 sections require laboratory data to be collected and maintained, including XI.A (General Controls) through XI.E (Stability Monitoring of APIs).
