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bharathi ☆ India, 2011-12-23 05:56 (5297 d 00:25 ago) Posting: # 7815 Views: 3,824 |
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We are planning for a BE study of Nicotine Chewing gum 1) Innovator adds Overages (unofficial data, supported by assay values (mean of 10 gums) of 10 batches (106 -108%) Justification for their overage may be - manufacturing loss/nicotine in the cud after chewing for 30 minutes is around 20% Our product doesn't need any overages (no manufacturing loss, cud analysis after chewing is 0%) Obviously assay value of our product will be 95- 100%, even if it is 100%, there is a minimum difference of 6% (more than 5% limit given in the EU guideline) How can we justify this? 2) Baseline correction LLOQ = 10 - 12% of Cmax, so if we go without baseline (0 -12% error adds up) Is it better to go with baseline or without baseline correction? 3) Exclusion criteria LLOQ being 10 -12% (How can we exclude subjects with baseline more than 5% of Cmax?) Please can you clarify/suggest - Edit: Category changed and subject line changed. Helmut |
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Helmut ★★★   Vienna, Austria, 2011-12-23 16:00 (5296 d 14:21 ago) @ bharathi Posting: # 7816 Views: 2,939 |
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Dear bharathi! Only answering your first question (have to think about the others). Since you can justify an expected difference of more than 5% (ten batches of the reference documented) you can plan for a content-corrected BE assessment. Show also data of different batches of the test product to document content uniformity. Covered by the GL Section 4.1.8: “[…] in exceptional cases where a reference batch with an assay content differing less than 5% from test product cannot be found (see section 4.1.2) content correction could be accepted. If content correction is to be used, this should be pre-specified in the protocol and justified by inclusion of the results from the assay of the test and reference products in the protocol.” — Dif-tor heh smusma 🖖🏼 Довге життя Україна! ![[image]](https://static.bebac.at/pics/Blue_and_yellow_ribbon_UA.png) Helmut Schütz ![[image]](https://static.bebac.at/img/CC by.png) The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes |
Ing. Helmut Schütz