1.0 The majority of GMP regulatory bodies has made it a mandatory for the companies to have a written procedure for the Annual Product Review process and recommends the review of all the batches that are manufactured in the preceding year from January 1st to December 31st. And the batches include both approved as well as rejected batches.
3.0 However, a company should follow a standard template to ensure that all required aspects are evaluated.
4.0 As an APR is an evolving document. It should be of few sections with minimal requirements to an elaborate document with addenda containing information or data relevant to the product.
5.0 An Annual product review report should contain the following chapters
5.1 Finished product and Half finished product testing results.
5.2 Critical in-process controls.
5.4 Deviations and CAPA has taken against each deviation, effectiveness of CAPA on later manufactured batches.
5.5 Review of reprocessed/ reworked batches and the reason for reprocess/ rework of the batches.
5.6 Changes proposed, approved and implemented that are directly or indirectly related to the product, in-case if a change control is raised related to a multi-product facility should be mentioned in the annual product review report of all the products that are manufactured in the facility.
5.7 Validations (Process or Analytical method) if get triggered by the changes made.
5.8 Repacking made
5.9 Regulatory filings made, or updates made in the existing DMF that owed to the changes made
5.10 Stability studies and any OOT result found at any station, its investigation outcome should also be addressed. Details of add-on batches for stability studies.
5.11 Return goods, complaints, recalls, noted for the product.
5.12 Critical equipment qualifications.
5.13 Quality agreements made for the product.
5.14 Effectiveness of CAPA mentioned in the previous year APR.
5.15 Unresolved or open issues of previous year APR.
5.16 Review of starting materials including packaging materials used for the product.
5.17 Retain sample review
5.18 Each numbered sub-section typically should be followed by a comment or observation and finally should have a cumulative summary of the report.
5.19 And the document should finally be reviewed by all the concerned departments, approved by the management and authorized by the quality head.
Related: Importance of APR in Quality Improvements
Related: Importance of APR in Quality Improvements
6.2 The results of all quality parameters should be tabulated against the specifications, and any change made in the specification should be clearly mentioned.
6.3 If a failed batch is considered for trending, then standard deviation between the results (for a particular parameter in the batch failed) increases then eventually, the sigma values also increases, and it further escalates the band between the average and sigma limits.
6.4 Failed batches should be tabulated along with.
6.5 Trending of minimum and maximum of all the results, calculation of the average of the total results of the batches, calculation of the standard deviation between the batches and calculation of sigma limits should be done for all the quantitative quality parameters.
6.6 A graphical representation of quality trends should be made, graphs
Should be drawn against minimum, maximum, average, standard deviation, ± sigma limits and specification limits.
6.7 The will help in dissecting data and detecting adverse trends wherever applicable.
Related: Procedure for Preparation of APR
Related: Procedure for Preparation of APR
If measured the same thing many times and draw a straight line for every result or value then a graph forms with bell shape fixed at the tangible point. Then if the width is compared to the height of the bell-shaped graph, and it is then called a statistical measurement “standard deviation or sigma” Sigma calculation and evaluation of sigma values obtained are explained with sulfated as an example below.
7.1 Calculation of sigma (2sigma, 3sigma, 4 sigma or 6sigma) can be applied to all quantitative quality parameters e.g Assay, LOD, Residue on ignition, impurities etc
7.2 Sigma calculation can be done as follows.
7.2.1 Calculate an average of result of all approved batches (calculation of average illustrated taking sulfated ash as an example)
S.No
|
Batch Number
|
Result
|
Specification limit
|
1
|
XXX12/01
|
0.05
|
NMT 0.25%
|
2
|
XXX12/02
|
0.06
|
|
3
|
XXX12/03
|
0.18
|
|
4
|
XXX12/04
|
0.06
|
|
5
|
XXX12/06
|
0.06
|
|
6
|
XXX12/07
|
0.07
|
|
7
|
XXX12/08
|
0.06
|
|
8
|
XXX12/09
|
0.06
|
|
9
|
XXX12/10
|
0.07
|
|
10
|
XXX12/11
|
0.19
|
|
11
|
XXX12/12
|
0.07
|
|
12
|
XXX12/13
|
0.07
|
|
13
|
XXX12/14
|
0.19
|
|
14
|
XXX12/15
|
0.22
|
|
15
|
XXX12/16
|
0.07
|
|
Assume (XXX) batches are produced and approved
|
|||
Average
|
0.2+0.4+0.1+0.2+0.2+0.5+0.5+0.5+0.8+0.4+0.7+0.8+1.2+0.9+0.4=XX
|
||
XX / XXX= 0.06(Average result)
|
|||
Note:
|
Number of digits after decimal point should be as specified in the standard procedures.
|
||
7.2.2 Calculate the standard deviation for results.
S.No
|
Batch Number
|
Result
|
1
|
XXX12/01
|
0.05
|
2
|
XXX12/02
|
0.06
|
3
|
XXX12/03
|
0.18
|
4
|
XXX12/04
|
0.06
|
5
|
XXX12/06
|
0.06
|
6
|
XXX12/07
|
0.07
|
7
|
XXX12/08
|
0.06
|
8
|
XXX12/09
|
0.06
|
9
|
XXX12/10
|
0.07
|
10
|
XXX12/11
|
0.19
|
11
|
XXX12/12
|
0.07
|
12
|
XXX12/13
|
0.07
|
13
|
XXX12/14
|
0.19
|
14
|
XXX12/15
|
0.22
|
15
|
XXX12/16
|
0.07
|
Assume (XXX) batches are produced and approved
|
||
Std deviation (SD)
|
0.02 (After rounding off)
|
|
7.2.3 Calculate 2 x (Multiplied) STD 0.02= ( value obtained for standard deviation) =0.04 (2SD) like wise, SD is to be multiplied with 3 (for 3Sigma) 4 (4Sigma )etc
7.2.4 Average + 2SD = +2sigma i.e 0.6+ 0.04= 0.1 (+2 sigma value)
7.2.5 Average - 2SD = -2sigma i.e 0.6 - 0.04 = -0.02 (-2 sigma)
7.2.6 Plot a graph for the results obtained, along with ± 2 sigma values.
7.2.7 Following exemplary graph is illustrated against 2,3,4 & 6 sigma values
8.0 The crux of the APR document is the Conclusions and Corrective Actions/ Recommendations section.
8.1 Identify the batches which fall in the zone away from average and cross ± sigma values.
8.2 Evaluate the batches, for all the possible reasons for sulfated ash being more than the regular trend.
8.3 The reasons for the Sulphated ash being more than the regular trend
may be due to many reasons like i.e
· Sulphated ash being carried by key starting materials
· Improper washing
· Equipment failure during washing
· Faulty equipment
· Salts might have formed during reaction etc
8.4 If the key starting materials procured from more than one approved vendor and if the batches having a result more than the regular trend are manufactured with the key starting material obtained from one particular vendor, then it should be further evaluated through the vendor evaluation.
8.5 Likewise, variation in the parameter which impacts sulfated ash content of the product should be compared with the batches with result near to the average.
8.6 It was a conventional thought that high levels of quality cost more in the long run, but the quality is that the best quality does not cost more.
It actually costs less. Cost-of-quality is actually the cost of deviating from quality–paying for things like variations within specified limits or ranges between batches etc and if those variations can be arrested, then the band between the average (regular trend) and ±sigma levels can be made narrow and more consistency within the batches.
9.0 Recommendations: This section should include summaries of each of the prior sections, and the appropriate corrective/preventive measures necessary for each observation made.
Submitted By.
I.L.Bhavani Chandra
E-mail : lakshmibhavani2102@gmail.com
E-mail : lakshmibhavani2102@gmail.com
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hi,
ReplyDeletecan you give me for example about the trends .