Pramote Cholayudth previously was the managing director of the Professional Conference Center, Ltd. He currently is a validation consultant to Biolab Co., Ltd., in Thailand. He is the founder and manager of PM consult, cpramote2000@yahoo.com.

Pramote Cholayudth

glove hand Concept of FDA approved. Food and drugs administration. Quality medcine, assurance, organization.| Image Credit: ©everythingpossible - stock.adobe.com

The underlying concept for acceptance value (AV) in <905> Uniformity of Dosage Units (UDU) is based on that of tolerance interval (TI). Its maximum allowed acceptance value (L1) is declared not more than (NMT) 15; therefore, meeting the limit will just imply that the lower the value the higher the degree of quality conformance. Due to the formula for L1 or AV (i.e., , the condition foris not justified, and so, compromising that, the AV results will easily pass the limit of NMT 15 most of the time. If recognized by United States Pharmacopeia, such a compromization will continue for official use in a new proposal on “Batch Release Testing for Ensuring Compliance with Uniformity of Dosage Units”.

One of the solutions for such a compromization issue is to simply implement the TI technique to demonstrate that at least 95% or more of the dosage units in routine batches will fall within the range 85–115% of label claim. The technique will provide useful data for batch releasing rather than depending on AV parameter alone.

Pramote Cholayudth, cpramote2000@yahoo.com, is the founder and manager of PM Consult. He is an industrial pharmacist with more than 40 years of experience. He is a guest speaker on process validation to industrial pharmaceutical scientists organized by Thailand’s FDA.

®
Vol. 48, No. 2
February 2024
Pages: 24-29

When referring to this article, please cite it as Cholayudth, P. Using Tolerance Intervals for Evaluation of Uniformity of Dosage Units Data in Routine Batch Release

Articles

This article introduces that the basic technique for tolerance interval is implemented using the conventional range 85–115% LC where the proposed range in the PF is not taken into account.

Using Tolerance Intervals for Evaluation of Uniformity of Dosage Units Data in Routine Batch Release

United States Pharmacopeia General Chapter

 <905>, “Uniformity of Dosage Units,” describes requirements for oral solid dosage formulations greater than 25mg/25% threshold. This chapter shows that it may be risky to release routine batches using weight variation (WV) instead of the content uniformity (CU) method; although, it is allowed by the monograph. To prevent risk to quality, justification of WV data quality in process validation (PV) batches is necessarily required to ensure that each of the routine batches released by WV meets the monograph requirements. A practical approach to using available statistical techniques for demonstration of interchangeability between CU and WV data in the same PV batches is introduced.

Submitted: Jan. 3, 2023
Accepted: Jan. 25, 2023

When referring to this article, please cite it as Cholayudth, P. Justification of Using Weight Variation Instead of Content Uniformity for Release of Relevant OSD Forms. 

This article discusses the evaluation of paired content uniformity and weight variation data sets using F and T tests to ensure that batches meet compendial requirements.

Justification of Using Weight Variation Instead of Content Uniformity for Release of Relevant OSD Forms

Two typical tests for oral solid dosage forms are dissolution and content uniformity. In continued process verification (CPV), there must be some kind of evaluation such that the validity of the two test data within the same CPV batch is demonstrated. One such evaluation tool is control charting using F data (i.e., F chart) to demonstrate that the consistency between dissolution and CU data is under statistical control.

Submitted: July 25, 2022
Accepted: Aug. 19, 2022


Volume 46, Number 10
October 2022
Pages: 44–47

When referring to this article, please cite it as P. Cholayudth, " Application of F Charts in Continued Process Verification of OSD Forms," 

This article introduces a control chart technique using F statistic for continued process verification of oral solid dosage forms.

Application of F Charts in Continued Process Verification of OSD Forms

Relative standard deviation (RSD) limits were used in content uniformity in the past (before 2007). From a statistical point of view, RSD is one of the only few statistics that describes the term “uniformity” best. In a simulation study conducted by the author, both acceptance value (AV) and RSD distributions have a typical relationship where it was found that AV and RSD charts, when applied for continued process verification (CPV) purpose, can be constructed concurrently on the same chart frame to demonstrate their common overlay view. While RSD calculation is much more simple, RSD charts may also be applied to confirm the validity of AV charts in CPV exercise.

Submitted: May 23, 2022
Accepted: June 8, 2022

When referring to this article, please cite it as P. Cholayudth, “Application of RSD Charts for Content Uniformity Data in Continued Process Verification,” 

This article is focused on introducing a control chart technique using relative standard deviation (RSD) statistics (i.e., RSD chart); in other words, a coefficient of variation chart for continued process verification. 

Application of RSD Charts for Content Uniformity Data in Continued Process Verification

Determining the probability of meeting content uniformity can be done through estimation by using probability vs. lot coverage charts and tables constructed from simulated probability and lot coverage 1 data, as discussed in 

. In this second half, the author introduces a practical approach to determining the best estimate for probability of passing the dissolution test using probability versus lot coverage charts and tables. The charts and tables were constructed using simulated probability and lot coverage data. The “best estimate” concept is to demonstrate that the probability estimates, especially for those very close to 100%, are just slightly deviated from the exact calculated values by not more than the statistically acceptable deviation limits.

Submitted: Aug. 30, 2021
Accepted: March 4, 2022


Vol. 46, No. 4
April 2022
Pages: 40–45

When referring to this article, please cite it as P. Cholayudth, “Determining the Best Estimate of Probability of Passing Multiple Stage Tests: Part 2—Dissolution,” 

The author introduces a practical approach to determining the best estimate of probability for passing multiple stage dissolution tests.

Determining the Best Estimate of Probability of Passing Multiple Stage Tests: Part 2—Dissolution

Submitted: August 24, 2020
Accepted: October 12, 2020

This article introduces a practical approach to determining the best estimate for probability of passing uniformity of dosage units (content uniformity) using probability vs. lot coverage charts and tables constructed using simulated probability and lot coverage (LC1) data. The best estimation concept is to demonstrate that the probability estimates, especially for those approaching 100%, are slightly different (deviated) from the exact calculated values by not more than (NMT) the statistically acceptable deviation limits.

Submitted: Aug. 24, 2020
Accepted: Oct. 12, 2020

Pramote Cholayudth is an industrial pharmacist with more than 40 years of experiences. He is a guest speaker on Process Validation to industrial pharmaceutical scientists organized by Thailand’s FDA. He is the founder and manager of PM Consult and can be contacted via cpramote2000@yahoo.com.

When referring to this article, please cite it as P. Cholayudth, “Determining the Best Estimate of Probability of Passing Multiple Stage Tests: Part 1–Content Uniformity,” 

This article introduces a practical approach to determining the best estimate for probability of passing uniformity of dosage units (content uniformity) using probability vs. lot coverage charts and tables constructed using simulated probability and lot coverage (LC1) data. 