I have had the opportunity to read the (review) article, titled
“In vitro models for the prediction of in vivo performance of oral dosage forms (2013), link”
and certainly it is quite (very) long article, but is it useful? In one way it might be, since it implies that the practices of dissolution testing have not been successful, at least from the in vivo perspective. It is claimed that for QC purposes, the practices may be successful (however, without going into details, I would argue against this view, see below).
My biggest surprise, a pleasant one, is that there is no or limited emphasis on the IVIVC aspect. I am assuming that lack of use or relevance of IVIVC for predictability of plasma drug levels has been recognised. This is great!
On the other hand, there is an emphasis on PBPK (physiologically based pharmacokinetics) modelling (perhaps starting of a new “fad”), with an underlying assumption that one requires complex instrumentation and mathematical modelling to predict plasma drug levels. In my view, such an approach may not be necessary as a simple convolution approach can predict plasma drug levels very well and easily.
Surprisingly (or perhaps not surprisingly), there is no mention of crescent shape spindle, convolution technique or the name Qureshi in the publication. This may reflect lack of credibility of the publication for the literature assessment/review.
In addition, in my view, the publication does not provide any suggestion as to how one should determine dissolution characteristics of a, or any, product (IR or ER). So, the question remains, if one cannot determine dissolution characteristics of a product (e.g. see link), one cannot move further, may it be for QC, PBPK modelling or prediction of plasma drug levels etc.
However, answers to such questions can easily be found as described in the following articles:
(1) Determining blood concentration-time (C-t) profiles from in vitro dissolution results and product evaluation – carbamazepine (link).
(2) A Simple and Unique Approach for Developing and Evaluating Products (link).
