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I fl f St bilit Eff t D li d D PTIT A t P b biliti Influence of Stability Effects on Delivered Dose PTIT Acceptance Probabilities Hans-Joachim Delzeit and Stefan Leiner, Boehringer Ingelheim Pharma GmbH & Co. KG 1. Summary: 130 135 Batch Mean at Release: 96 % Batch Mean after 36 M.: 93 % ./Year) 90 100 For the determination of the delivered dose uniformity (DDU) of inhalation products, FDA proposed a two one-sided parametric tolerance interval test (PTIT). In contrast to oral dosage forms, stability studies on inhalation products include testing of UDD at all ICH time points over shelf- life. This multiple testing decreases the overall DDU acceptance rate of a batch: As example, a batch with a mean of 96 % and a standard deviation of 7 % has an acceptance rate in FDA's proposed PTIT of about 93% (i.e., 7 out of 100 identical batches will fail the test, if tested once, e.g., for release). Even without a change, this batch will have an overall stability acceptance rate (8 time i fi d i l bili i ) f b 0 93 8 57% Thi h b 4 f 10 id i l bili arget] 110 115 120 125 Upper Goalpost (120 %) Fraction above: < 6.25 % Batch SD: 7 % Degradation / Year: 1 % il 36 Months (1% Deg 60 70 80 90 points fixed in a post-approval stability commitment) of about 0.93 8 = 57%. This means, that about 4 out of 10 identical stability batches are expected to fail the DDU test over stability with all consequences for information to and discussions with FDA. In every PTIT test, the acceptance rate of a batch depends (amongst others) on the difference between mean delivered dose and target delivered dose. A loss of active ingredient over time, typically by degradation, changes the mean delivered dose. This influences the acceptance rate at each stability testing point and also the overall acceptance rate. vered Dose [% of Ta 90 95 100 105 ility [%] - 8 Tests unt 30 40 50 60 We calculate the overall acceptance rate for a typical degradation rate of 1 % per year at long-term conditions and a typical number of 8 stability time points. The overall acceptance rate clearly decreases compared to the acceptance rate at batch release. As example, the above mentioned batch (mean delivered dose 96 % at release; standard deviation: 7 %) will show an overall DDU acceptance rate of about 12% only. This means that the studied batch ought to pass and yet it is failing with a high probability. For setting a suitable specification the authors recommend to consider this stability effect in order to avoid expected out-of- Deliv 75 80 85 90 Lower Goalpost (80 %) Fraction below: < 6.25 % ll Acceptance Probab 0 10 20 30 Figure 4 For setting a suitable specification, the authors recommend to consider this stability effect in order to avoid expected out-of- specification results during shelf-life. 2. Introduction: 65 70 Time [Months] 0 3 6 9 12 18 24 36 Overa True Batch Mean at Release [%] 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 FDA October 2005 PTIT TOST (n = 20/60), True Batch SD = ... 4 % 5 % 6 % 7 % 8 % 9 % 10 % Figure 2 A manufacturer must know whether his products are viable for a commercial process. For OINDPs, typically the delivered dose uniformity test is limiting the commercial viability. The parametric acceptance criteria of FDA’s PTIT proposal are based on the requirements on the batch population that at least 87.5 % of all doses are within the target interval (goal posts) of 80 – 120 %, and not more than 6.25 % of all doses are above or below the target interval (two-one-sided test (TOST)). N = 20/60 8 Tests until 36 M. Batch Mean at Release [%] Deg. /Year Batch SD [%] 95 96 97 98 99 100 101 102 103 104 105 0 % 4 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 6 91.7 98.5 99.8 100.0 100.0 100.0 100.0 100.0 99.8 98.5 91.6 N = 30/90 8 Tests until 36M. Batch Mean at Release [%] Deg. /Year Batch SD [%] 95 96 97 98 99 100 101 102 103 104 105 0 % 4 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 6 99.4 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 99.5 3. Methods and Results (cont.): Figure 2 (top) displays the dose distribution of an exemplary batch with a release mean of 96 % and a standard deviation of 7 % and with a linear annual API degradation of 1 % over the ICH long term stability testing points up to 36 months. The light, central parts For the two-stage through-container-life (TCL) test, which includes the determination of the first and last dose of each device (container), the proposed acceptance criteria for the sample size scenario 20/60, that means 20 doses (10 devices) are determined at stage 1 and 40 doses (further 20 devices) at stage 2 (=> totally 60 doses), are concretely: Stage 1: Mean First D. & Mean Last D. in 100 ± 15 % Stage 2: Mean First D. & Mean Last D. in 100 ± 15 % (n 20) Mean ± 2 45 * SD in 100 ± 20 % (n 60) Mean ± 1 94 * SD in 100 ± 20 % 7 22.0 57.0 84.3 95.9 99.2 99.7 99.1 95.8 84.3 57.0 22.1 8 0.3 3.5 18.1 47.2 74.2 83.8 73.6 47.1 18.3 3.5 0.2 9 0.0 0.0 0.3 2.9 10.9 17.2 11.0 3.0 0.3 0.0 0.0 10 0.0 0.0 0.0 0.0 0.1 0.2 0.1 0.0 0.0 0.0 0.0 1 % 4 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 5 96.7 99.6 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 7 59.9 89.8 98.4 99.8 100.0 100.0 100.0 99.9 98.3 89.7 59.7 8 1.7 17.2 54.1 84.8 96.5 98.9 96.5 84.1 53.7 17.1 1.7 9 0.0 0.1 2.2 16.4 46.1 62.5 46.2 16.5 2.3 0.1 0.0 10 0.0 0.0 0.0 0.1 1.4 3.1 1.4 0.1 0.0 0.0 0.0 1 % 4 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 5 99.7 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 indicate 87.5 % of the batch; the darker, blue parts indicate a proportion of 6.25 % in the tails. It is obvious that the batch at each time point complies with the requirement of having not more than 6.25 % doses in each tail outside the goal posts of 80 - 120%. Figure 3 (below) illustrates that the overall acceptance probability is the multiplication of the independent individual (n=20) Mean ± 2.45 * SD in 100 ± 20 % (n=60) Mean ± 1.94 * SD in 100 ± 20 % The mean values (Mean) and standard deviations (SD) used in the parametric tolerance interval criteria are calculated based on the samples pooled over first and last dose. The probability of a product to pass FDA’s default PTI test for delivered dose uniformity can be read from operation characteristic curves However not only the behavior during batch release but also during stability testing are important: OINDPs are – in 6 44.7 76.9 93.4 98.6 99.8 100.0 100.0 100.0 100.0 99.6 97.2 7 1.4 11.9 39.0 69.8 89.0 96.9 99.0 98.4 93.7 79.3 50.3 8 0.0 0.1 1.7 10.9 33.5 60.3 74.3 67.0 42.2 16.1 3.1 9 0.0 0.0 0.0 0.1 1.5 6.6 11.5 8.3 2.5 0.3 0.0 10 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.0 0.0 1.5 % 4 99.7 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 6 73.6 94.0 99.1 99.9 100.0 100.0 100.0 100.0 100.0 100.0 99.9 7 6.2 33.8 70.7 91.6 98.4 99.8 100.0 100.0 99.5 96.6 83.2 8 0.0 0.5 7.8 33.7 67.4 88.7 96.1 93.7 78.3 45.9 13.6 9 0.0 0.0 0.0 0.9 8.6 29.7 47.1 36.9 13.5 1.9 0.1 10 0.0 0.0 0.0 0.0 0.0 0.6 1.5 0.9 0.1 0.0 0.0 1.5 % 4 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 the multiplication of the independent individual acceptance probabilities at each time point … … and, thus, is relevantly lower (11.9 % in this example). curves. However, not only the behavior during batch release, but also during stability testing are important: OINDPs are – in contrast to standard oral dosage forms – tested for delivered dose several times during stability so that repetition effects and active ingredient degradation effects come into play. 5 75.5 93.5 98.9 99.9 100.0 100.0 100.0 100.0 100.0 100.0 100.0 6 12.7 40.6 71.0 89.9 97.4 99.5 99.9 100.0 100.0 99.7 97.8 7 0.1 2.1 13.1 38.1 66.4 85.8 95.2 97.7 94.9 83.5 58.5 8 0.0 0.0 0.2 2.5 12.7 34.0 55.9 62.2 47.5 22.7 5.9 9 0.0 0.0 0.0 0.0 0.3 2.0 5.7 6.8 3.4 0.7 0.1 10 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5 90.6 98.9 99.9 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 6 26.4 63.1 88.7 97.9 99.8 100.0 100.0 100.0 100.0 100.0 99.9 7 0.4 6.4 30.0 63.2 87.0 96.8 99.4 99.9 99.6 97.4 86.8 8 0.0 0.0 0.9 8.6 31.9 62.4 84.2 91.1 82.0 54.5 20.8 9 0.0 0.0 0.0 0.1 1.4 9.5 25.8 31.4 17.5 3.9 0.3 10 0.0 0.0 0.0 0.0 0.0 0.1 0.5 0.6 0.2 0.0 0.0 The OC curves of the overall acceptance probabilities are shown in Figure 4 (top right); our exemplary batch is indicated by a red circle. Below Figure 4, the underlying results are tabulated for products with either no degradation, or with 1 % or with 1.5 % annual degradation. The left table is based on a sample size of 20/60, the right table on a 3. Methods and Results: sample size of 30/90. It becomes clear, that … • despite some benefit of the increased sampling, the exemplary batch still will be rejected with high probability, • batches with degradation have the highest acceptance rates if the release doses are slightly above target, l SD f 6 % l ll i ll i bl In a first step, the probabilities of typical batch populations to pass a single test are estimated by simulation study and the results are displayed by the operation characteristic (OC) curves in Figure 1 below. For the simulation study, it was assumed that 50 % of the intra-batch variability, in the figure labeled as “True Batch SD” , is coming from differences between devices and the remaining 50 % from the actuation variability within a device. Furthermore, it was assumed that the first and last dose are on the same expected level, in the figure labeled as “True Batch Mean”. 100’000 simulation runs by generating normal distributed random values were performed for each batch population 4. Discussions and Conclusions: Repeated stability testing, even of an extremely stable product, clearly lowers the probability of a batch to meet FDA’s PTIT criteria. The more frequently DDU is tested over stability, the lower is the overall acceptance rate: Frequent testing punishes the manufacturer 90 100 True Batch SD: 7 % 3 91.2 0 93.2 Months Prob. [%] • only a SD of 6 % or less allows commercially viable acceptance rates. 90 100 simulation runs by generating normal distributed random values were performed for each batch population. manufacturer. An active ingredient degradation over shelf life typically further lowers the overall acceptance probability. Not unrealistically, overall acceptance probabilities of as low as 10 % may occur without increasing the benefit for the patient. However, this increases the burden both for the industry and the Agency in terms of reporting and assessing OOS results and related activities, e.g., recalls. A systematic approach to minimize the risk of an expectable OOS during stability could be to manufacture batches slightly above ity [%] - Single Test y [%] - Single Test 60 70 80 36 44.8 24 65.8 18 75.1 12 82.8 9 86.0 6 88.7 ity [%] - Single Test 60 70 80 A systematic approach to minimize the risk of an expectable OOS during stability could be to manufacture batches slightly above target. This is in contradiction to the philosophy of the GMP rules which require to formulate batches to an active ingredient content of 100 %. Therefore, the authors suggest that Agency and industry elaborate scenarios to overcome this situation. Options may include … • establishing wider limits (goal posts) for shelf life than for release, • changing the two-one-sided test characteristics to a real coverage test 5. References: Acceptance Probabil Acceptance Probabilit 30 40 50 Overall 11.9 Acceptance Probabil 30 40 50 changing the two one sided test characteristics to a real coverage test, • reducing the number of testing points for DDU during stability, • increased understanding that OOS must be expected and are not indicative of poor quality, with less impact of expected DDU failures for reporting to the Agency. Novick S, Christopher DJ, Dey M, Lyapustina S, Golden M, Leiner S, Wyka B, Delzeit HJ, Novak C, and Larner G: A Two One-Sided Parametric Tolerance Interval Test for Control of Delivered Dose Uniformity. Parts 1 – 3. Published online in AAPS PharmSciTech, DOI: 10.1208/s12249- 009-9270-x, 10.1208/s12249-009-9269-3 and 10.1208/s12249-009-9271-9. Awarded with AAPS "2010 Outstanding Manuscript Award" A 0 10 20 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 36 Months -3 % 8 Tests Release 0 10 20 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 Figure 1 Figure 3 True Batch Mean [%] 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 FDA October 2005 PTIT TOST n = 20/60 Doses (first & last Dose of 10/30 Devices) IPAC-RS Conference, Washington, March 2011 Contact: Hans-Joachim Delzeit, Stefan Leiner / Boehringer Ingelheim Pharma GmbH & Co.KG, 55216 Ingelheim am Rhein, Germany [email protected], [email protected] True Batch Mean [%] FDA October 2005 PTIT TOST (n = 20/60), True Batch SD = ... 4 % 5 % 6 % 7 % 8 % 9 % 10 %
