Understanding S1, S2, and S3 Dissolution Acceptance Criteria

A dissolution result that does not meet the S1 acceptance criteria does not automatically mean the batch has failed. The staged evaluation process of S1, S2, and S3, as described in USP <711> Dissolution, is designed to assess both individual unit performance and overall batch variability. S1, S2 and S3 phase comes here.

Let's understand the concept with a practical example.

Suppose the dissolution specification is Q = 80%.

Therefore:

·        S1: Each unit is not less than Q + 5%. = 85%

·        S2: Average of 12 units (S1 + S2) is equal to or greater than Q, and no unit is less than Q − 15%. = 65%

·        S3: Average of 24 units (S1 + S2 +S3) is equal to or greater than Q, not more than 2 units are less than Q − 15%, and no unit is less than Q − 25%. = 55%

 

 

S1 Stage (6 Units)

Suppose the dissolution results for the first six units are: 88%, 91%, 86%, 89%, 87%, 83%

Although most units meet the requirement, one unit shows 83%, which is below the S1 criterion of 85%.

As a result, the batch does not meet S1 criteria.

However, this does not mean the batch fails.

The testing progresses to the S2 stage.

 

S2 Stage (12 Units Total)
Now, additional 6 units are tested, bringing the total to twelve units.

Suppose the average of all 12 units is 82%, and no individual unit is below 65%.

·        Average of 12 units = 82% ≥ Q (80%)

·        No individual unit < 65%

·        Therefore, S2 criteria are met.

 

In this example, the product can pass the dissolution acceptance criteria even though one unit initially failed at S1.

What Happens If S2 also Fails?

If the S2 criteria are not met, testing proceeds to the S3 stage, where an additional 12 units are tested, resulting in a total of 24 units.

 

S3 Stage (24 Units Total)

·        Average of all 24 units should be ≥ Q

·        Not more than 2 units should be < Q − 15%

·        No individual unit should be < Q − 25%

 

Why Is This Approach Important?
The stepwise S1 → S2 → S3 evaluation process recognizes normal unit-to-unit variability and prevents conclusions from being based on a single atypical result. It provides a scientifically justified and statistically balanced assessment of dissolution performance across the batch.

For professionals in Analytical R&D, Quality Control, and Regulatory Affairs, understanding these acceptance stages is essential for evaluating dissolution data, investigating unexpected or variable results, and ensuring compliance with pharmacopeial requirements.

Reference

USP <711> Dissolution