Abstract
In all manufacturing settings, there is an inherent drive to improve product through the reduction in process variation, implementing new technology, increasing efficiency, optimizing resources, and improving customer experience through innovation. In the pharmaceutical industry, these improvements come with added responsibility to the patient such that product made under the post-improvement or post-change condition maintains the safety and efficacy of the pre-change product. Regulatory agencies recognize the importance in providing manufacturers the flexibility to improve their manufacturing processes (FDA, Guidance Concerning Demonstration of Comparability of Human Biological Products, 1996; ICH Q5E, ICH Guidance for Industry: Q5E Comparability of Biotechnology/Biological Product Subject to Changes in Their Manufacturing Process, 2005). They also acknowledge that some changes may not require additional clinical studies to demonstrate safety and efficacy so that implementation may be more efficient and expeditious to benefit patients. When clinical studies are not necessary, a minimum requirement remains to demonstrate that the post-change product is comparable to the pre-change product. This comparison is known as analytical comparability. Analytical comparability may be demonstrated through the use of statistical and non-statistical methods. The choice of the methodology is not defined by the guidance documents. This paper presents an overview and use of equivalence tests and statistical intervals as options to demonstrate analytical comparability.
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References
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The thoughts and opinions presented in this article represent the author’s positions.
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Software used for the computations in this chapter are Minitab v17.0, SAS University Edition v3.2 and MS Excel.
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Example 1: tolerance interval
Lot ID | Clinical scale data | Lot ID | Pre-change commercial scale data |
|---|---|---|---|
A | 33.2111 | F | 54.0648 |
B | 37.5348 | G | 59.7112 |
C | 36.1102 | H | 55.5946 |
D | 35.0890 | I | 59.5768 |
E | 34.9719 | J | 52.8764 |
Example 2: non-profile equivalence
Lot ID | Value | Lot ID | Value | Lot ID | Value | Lot ID | Value | Lot ID | Value |
|---|---|---|---|---|---|---|---|---|---|
1 | 64.6901 | 8 | 63.8596 | 15 | 63.4737 | 22 | 65.2484 | 29 | 65.7704 |
2 | 66.2940 | 9 | 64.4832 | 16 | 64.3895 | 23 | 66.6342 | 30 | 63.8568 |
3 | 65.8114 | 10 | 66.9188 | 17 | 63.5307 | 24 | 65.3451 | 31 | 63.9972 |
4 | 65.6446 | 11 | 64.8376 | 18 | 65.0348 | 25 | 66.8672 | 32 | 65.9727 |
5 | 63.9546 | 12 | 64.9620 | 19 | 66.9927 | 26 | 63.8307 | 33 | 64.5528 |
6 | 66.2753 | 13 | 64.7369 | 20 | 67.0247 | 27 | 65.9205 | 34 | 64.2946 |
7 | 64.4325 | 14 | 63.3229 | 21 | 62.4785 | 28 | 64.2135 | 35 | 65.4374 |
Example 3: profile equivalence
Lot ID | Time point | Value | Process | Lot ID | Time point | Value | Process | Lot ID | Time point | Value | Process |
|---|---|---|---|---|---|---|---|---|---|---|---|
A | 0 | 85.450 | PRE | H | 0 | 85.420 | PRE | O | 0 | 86.340 | PRE |
A | 1 | 84.540 | PRE | H | 1 | 85.200 | PRE | O | 1 | 86.430 | PRE |
A | 2 | 84.290 | PRE | H | 2 | 85.240 | PRE | O | 2 | 86.180 | PRE |
A | 3 | 83.110 | PRE | H | 3 | 85.210 | PRE | O | 3 | 85.690 | PRE |
B | 0 | 85.500 | PRE | I | 0 | 84.580 | PRE | P | 0 | 86.050 | POST |
B | 1 | 85.820 | PRE | I | 1 | 85.910 | PRE | P | 0 | 85.380 | POST |
B | 2 | 85.310 | PRE | I | 2 | 84.740 | PRE | P | 0 | 85.970 | POST |
B | 3 | 85.369 | PRE | I | 3 | 84.420 | PRE | P | 1 | 84.500 | POST |
C | 0 | 86.340 | PRE | J | 0 | 86.610 | PRE | P | 2 | 84.940 | POST |
C | 1 | 86.070 | PRE | J | 1 | 87.410 | PRE | P | 3 | 84.080 | POST |
C | 2 | 85.760 | PRE | J | 2 | 85.670 | PRE | P | 3 | 83.770 | POST |
C | 3 | 84.410 | PRE | J | 3 | 85.850 | PRE | P | 3 | 84.100 | POST |
D | 0 | 86.000 | PRE | K | 0 | 84.650 | PRE | Q | 0 | 85.450 | POST |
D | 1 | 85.870 | PRE | K | 1 | 84.450 | PRE | Q | 0 | 85.370 | POST |
D | 2 | 86.150 | PRE | K | 2 | 84.560 | PRE | Q | 0 | 85.330 | POST |
D | 3 | 85.600 | PRE | K | 3 | 84.340 | PRE | Q | 1 | 85.420 | POST |
E | 0 | 86.840 | PRE | L | 0 | 86.540 | PRE | Q | 2 | 84.480 | POST |
E | 1 | 85.480 | PRE | L | 1 | 86.440 | PRE | Q | 3 | 83.720 | POST |
E | 2 | 85.280 | PRE | L | 2 | 86.100 | PRE | Q | 3 | 84.050 | POST |
E | 3 | 85.680 | PRE | L | 3 | 86.270 | PRE | Q | 3 | 83.990 | POST |
F | 0 | 85.620 | PRE | M | 0 | 85.850 | PRE | R | 0 | 85.430 | POST |
F | 1 | 85.590 | PRE | M | 1 | 85.970 | PRE | R | 0 | 84.840 | POST |
F | 2 | 85.120 | PRE | M | 2 | 85.620 | PRE | R | 0 | 84.930 | POST |
F | 3 | 85.320 | PRE | M | 3 | 85.340 | PRE | R | 1 | 84.330 | POST |
G | 0 | 86.560 | PRE | N | 0 | 87.030 | PRE | R | 2 | 83.950 | POST |
G | 1 | 87.240 | PRE | N | 1 | 86.470 | PRE | R | 3 | 84.350 | POST |
G | 2 | 86.140 | PRE | N | 2 | 86.810 | PRE | R | 3 | 83.950 | POST |
G | 3 | 86.740 | PRE | N | 3 | 85.180 | PRE | R | 3 | 84.010 | POST |
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Sidor, L. (2016). Statistical Methods for Analytical Comparability. In: Lin, J., Wang, B., Hu, X., Chen, K., Liu, R. (eds) Statistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics. ICSA Book Series in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-42568-9_19
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