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Spotlight on Trends for API Warning Letters from October 2015 – June 2017

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Spotlight on Trends for API Warning Letters from October 2015 – June 2017

Spotlight on Trends for API Warning Letters from October 2015 – June 2017
October 24
11:56 2017

API Warning Letters

Each spring, the FDA publishes data on its website related to Form 483 inspection observations and warning letters issued by the Centre for Drug Evaluation and Research (CDER) during the previous fiscal year. By analysing this annual data and comparing it to that of other recent fiscal years pharmaceutical and biopharmaceutical manufacturers can gain a clearer picture of FDA enforcement trends and their potential impact on business and the industry as a whole.

In this article, we look at API results from fiscal year 2016 (Oct. 15-Sept. 16) and the nine months of fiscal year 2017 (Oct. 16-Jun. 17).

Increasing Trend over the last three years 

The increase in the number of warning letters addressed to API (Active Pharmaceutical Ingredient) manufacturers over the past three years is noteworthy. In 2015 10 manufacturers of active substances received the FDA warning letter. There were 22 letters issued in FY 2016. There have been 21 letters issued so far for the nine months of fiscal year (Oct 16- Jun 17). The share of production sites located in India or China which received a warning letter is high in the considered periods.

Deficiency Category Trend Fiscal Year 2016

The most commonly seen deficiencies in FY2016 refer to chapter 5 Process Equipment and subsection 5.4 Computerized Systems, paragraph 5.43 of guideline ICH Q7 which states

“Computerized systems should have sufficient controls to prevent unauthorized access or changes to data. There should be controls to prevent omissions in data (e.g. system turned off and data not captured). There should be a record of any data change made, the previous entry, who made the change, and when the change was made.”

Typical examples were referring to the unregulated access to raw electronic data are as follows:

  • deleting of “bad” analyses (HPLC) after choosing the ones with specification compliant results
  • manipulation of metadata in audit trail
  • changing the date of analyses

Quality management deficiencies, relating to the ICH Q7 chapter 2 Quality Management, were the second most commonly seen deficiencies in FY2016. In total, there were 6 citations where violations of the requirement for prompt and contemporaneous recording of quality relevant activities as stated in paragraph 2.15 were seen. The paragraph states:

“All quality related activities should be recorded at the time they are performed”. Results should be recorded contemporaneously. Date and time stamps should flow in order of execution for the data to be credible. Data should never be back dated.

Typical Examples seen were

  • incompletely filled-in batch protocols
  • later transfer of measured values from memos to the official protocol

Deficiency Category Trend Fiscal Year 2017

 The most commonly seen deficiencies in FY2017 refer to chapter 2 Quality Management and chapter 5 Process Equipment. There were only 5 citations relating to unauthorised data access as per subsection 5.4 Computerized Systems, paragraph 5.43. This is a notable decrease on the number of similar findings relating to section 5.4 in FY2016.

Overall, the warning letters described 12 GMP violations of the principles of quality assurance and relating to the areas of responsibility in Quality Units (subsection 2.1 Principles, 2.2 Responsibilities of the Quality Unit(s) and 2.3 Responsibilities for Production Activities).

Example of issues seen were

  • lack of a Quality Unit
  • lack of fundamental GMP documents

A similarly high number of deficiencies were found in the area quality control and laboratory. The incomplete or absence of a full investigation into the reasons for OOS results were the source of FDA inspectors citations in some of the warning letters.

The Outlook

2017 to date is showing a trend away from violations relating to unregulated access to raw electronic data and towards Quality Management issues. An analysis of warning letters at the end of the year will show if this trend continues.


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