◆ Data Integrity – two new documents from PIC/S and EMA (11-Aug-16 ECA)
In the last two years, national competent authorities from all over the world have focused more and more on Data Integrity. Many draft guidances from different authorities were published in 2016. In April 2016, the American FDA issued a first draft Guidance for Industry – “New FDA Draft Guidance Data Integrity and Compliance with cGMP” – and in July 2016, the British MHRA issued a third draft – ” MHRA GxP Data Integrity Definitions and Guidance for Industry – Draft version for consultation”. On 10 August 2016, the PIC/S followed with a first draft “Good Practices for Data Management and Integrity in regulated GMP/GDP environments” and simultaneously the European Medicines Agency (EMA) extended their ‘Questions and answers: Good Manufacturing Practices’ webpage by 23 answers on Data Integrity questions.
PIC/S 041-1 “Good Practices for Data Management and Integrity in regulated GMP/GDP environments”
The current PIC/S draft document PI 041-1 contains 41 pages of detailed information. The document was written to provide guidance for inspectorates. The comment period for PIC/S Participating Authorities will end on 28 February 2017. The following activities have not been defined yet.
The introduction referred to the fact that the effectiveness of inspection processes is determined by the veracity of the evidence provided to the inspector and ultimately the integrity of the underlying data. Furthermore it is critical to the inspection process that inspectors can determine and, fully rely on the accuracy and completeness of evidence and records presented to them. Therefore Good Data Management practices influence the integrity of all data generated and recorded by a manufacturer and these practices should ensure that data is accurate, complete and reliable.
EMA Questions and answers: Good Manufacturing Practice
For many years, the European Medicines Agency (EMA) has been publishing a list of answers to frequently asked questions regarding Good Manufacturing Practice. The answers were discussed and agreed by the ‘Good Manufacturing Practice (GMP) / Good Distribution Practice (GDP) Inspectors Working Group. Therefore the answers could be interpreted as an official EU statement to open GMP questions. Basically the answers are given to questions in relation to different chapters and annexes of the EU GMP guide. Furthermore there will be answers to topics like ‘general GMP’, ‘GMP certificates’ and ‘inspection coordination’. On 10 August 2016, the EMA extended the list by detailed answers on 23 questions to Data Integrity, Data Lifecycle and related topics.
PIC/S PI 041-1 “Good Practices for Data Management and Integrity in regulated GMP/GDP environments”
EMA Questions and answers: Good Manufacturing Practice
◆ GDP: MHRA concerned about Qualification of Customers (08-Aug-16 ECA)
In a first blog, the U.K. Medicines and Healthcare Products Regulatory Agency (MHRA) reminded companies to properly qualify their suppliers. In a recent blog just published it is pointed out that it is equally important to deliver medicines only to authorised organisations and qualified prescribers, like wholesalers or persons entitled to supply or administer medicines receive medicinal products.
Especially (but not only) products with a potential for misuse are in the focus. MHRA reports that “certain medicines subject to abuse, commonly diazepam, nitrazepam, zopiclone, tramadol and zolipdem have been leaking from the regulated supply chain and made available for sale in the black market and on illegal websites”.
This does mean that in the distribution chain not only suppliers have to be qualified but also recipients. The respective “checks that should be made are similar to the qualification of suppliers” (as described in the previous blog). For supplies to pharmacies, hospitals and clinics it is “particularly important that the usage pattern is considered when fulfilling orders”. MHRA is reporting that the inspectorate has seen “pharmacies ordering up to a 2000 packs of these products monthly. In the blog it is recommended that there should be a “procedure in place that sets defined limits to the size of routine orders that can be placed by customers that alert the company Responsible Person to investigate if excessive amounts are ordered.”
Please also see the MHRA Inspectorate Blog “Qualification of customers, what wholesalers need to know”.
◆ Analytical Lifecycle: USP <1210> “Statistical Tools”, Analytical Target Profile and Analytical Control Strategy (14-Sep-16 ECA)
Following the recently announced elaboration of a new general chapter <1220> “The Analytical Procedure Lifecycle” the United States pharmacopeia (USP) is now proceeding in its approach for a comprehensive analytical lifecycle concept. A further step towards this approach is the draft of a new USP General Chapter <1210> Statistical Tools for Procedure Validation which has been published in Pharmacopeial Forum (PF) 42(5) in September 2016. Comment deadline is November 30, 2016.
Additionally, two Stimuli Articles regarding “Analytical Control Strategy” and “Analytical Target Profile: Structure and Application Throughout The Analytical Lifecycle” appeared in the same issue of the PF.
In the draft chapter <1210> Statistical Tools for Procedure Validation, the USP Statistics Expert Committee presents a revision to the proposal of <1210> published in PF 40(5) [Sept.–Oct. 2014]. On the basis of the comments and feedback given by stakeholders, the committee has addressed their concerns about the narrow scope and details on methodology to be used. The chapter is proposed as a companion to general chapter <1225> Validation of Compendial Procedures with the purpose of providing statistical methods that can be used in the validation of analytical procedures. A revision of general chapter <1225>, including a new section on Lifecycle Management of Analytical Procedures, has been published for comment in PF 42(2) in March 2016.
Specifically, the revision clarifies the accuracy and precision calculations while removing specific linearity requirements. Linearity may be inferred from accuracy or other statistical methods as deemed appropriate. The chapter discusses all of the following analytical performance characteristics from a statistical perspective:
- detection limit,
- quantitation limit,
- and linearity.
Additional related topics that are discussed in the draft include statistical power, two one-sided tests of statistical equivalence, tolerance intervals, and prediction intervals.
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