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jag009 ★★★ NJ, 2012-07-12 19:37 (5096 d 18:53 ago) Posting: # 8941 Views: 5,038 |
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Hi, Is it valid to generate an IVIVC without a 4-way study that involves 3 test ER formulations and IV/IR treatment? Can I generate one with the IR/IV data obtained from literature to serve as the impulse function for deconvoution and convolution steps? Data from 3 test ER formulations will be from one study, i.e., 4-way crossover study compared 3 test ER formulations vs reference ER product. Thanks John |
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JMCardot ☆ France, 2012-07-13 14:13 (5096 d 00:18 ago) @ jag009 Posting: # 8942 Views: 4,317 |
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Dear John, NO you cannot use literature data, lets modulate now the answer. It depends:
Best regards, Jean-Michel |
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jag009 ★★★ NJ, 2012-07-19 01:18 (5090 d 13:13 ago) (edited on 2012-07-19 15:08) @ JMCardot Posting: # 8958 Views: 4,208 |
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Thank you Jean-Michel, Questions: 1) I agree with most of what you said. Correct me on this.. --> Since the UIR (Unit impulse function) only serves as a "Denominator" for the IVIVC process for the convolution and deconvolution steps, if one keeps it constant throughout the IVIVC modelling process (and later stages) then shouldn't it be okay if literature IR or IV data is used? 2) There is a chapter in the IVIVC book edited by David Young et al. Bill Gullesbie wrote a chapter (2.3) on "Method Not Requiring an IV or IR Reference Dose". He suggested that the UIR can be estimated by fitting the overall convolution model to the plasma concentrations resulting from the ER dosage forms. John Edit: Dear John, please avoid typewiter-style multiple blanks in future posts. They are not displayed anyway. [Helmut] |
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JMCardot ☆ France, 2012-07-20 08:46 (5089 d 05:45 ago) @ jag009 Posting: # 8961 Views: 4,242 |
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Dear John, 1) Yes in theory and in an ideal world, NO in practice as in this case you have to assume that (i) the two sets of subjects respond exactly in the same way: exactly the same behavior/reaction and subjects composition of the datasets (for example not in one case slow acetylators and in the second fast, sex influence and different composition of dataset, for IR no influence of the formulation, no meal influence, same clearance between the datasets, etc…) => in other words the model and your data are reflecting the same overall subject population and the variability is low between the two (ii) that the mean value published reflect the individual data (iii) that the published data are accurate (analytical method, enough sampling points, model used, etc…) (iv) that variability is of no importance (invariance of the function in particular same clearance) (v) all other concerns . Even if you keep it constant throughout the IVIVC modeling process, it is not possible. To give you an extreme example: imagine you have set up an animal model IV for your drug will you use this IV model to deconvolate, establish correlation and then convulate in Human if you keep it constant?In addition I remind you that you are not allowed to use the results for any regulatory purpose and if you have made a mistake selecting the publication and the data, the results are going to be non-sense. If you want to apply such a method I can only tell you the risks associated. 2) I do not have the book in my hands but I think that you are referring to the (ii) below. Without IR or IV you can use (i) Wagner Nelson if you have a one compartment model (ii) a pure convolution approach (one step approach) which use often methods linked with population pharmacokinetic and is based on individual subjects convolution, in this case you do not have the absorption derived from the deconvolution process but you use only the dissolution observed. Based on dissolution you see which function (IVIVC and time scaling to simplify) must be applied to modify and make it a suitable input function for your convolution (using the IV model) which must fit your observed data adjusting the IVIVC function. In this case the quality of the IV model is of importance and must exist for each subject. You have 4 models to be implemented to do it: the dissolution data, the IV or IR data, the SR data and the IVIVC. See Gillespie WR. Convolution-based approaches for in vitro-in vivo correlation modeling. in: Young D., Devane J., Butler J. editors. Advances in Experimental Medicine and Biology, In vitro-in vivo Correlations, Plenum Press, New York. 1997. p. 53-65. Gaynor C, Dunne A and Davis J. A Comparison of the Prediction Accuracy of Two IVIVC Modelling Techniques. J Pharm Sci. 2008;97:3422-32. O’Hara T, Hayes S, Davis J, Devane J, Smart T and Dunne A. In vivo-in vitro (IVIVC) modeling incorporating a convolution step. J Pharmacokinet Phar. 2001;28:277-298. Best regards, JM |
. Even if you keep it constant throughout the IVIVC modeling process, it is not possible. To give you an extreme example: imagine you have set up an animal model IV for your drug will you use this IV model to deconvolate, establish correlation and then convulate in Human if you keep it constant?