Establishing Virtual Bioequivalence and Clinically Relevant Specifications for Omeprazole Enteric-Coated Capsules by Incorporating Dissolution Data in PBPK Modeling.

Currently, Biopharmaceutics Classification System (BCS) classes I and III are the only biological exemptions of immediate-release solid oral dosage forms eligible for regulatory approval. However, through virtual bioequivalence (VBE) studies, BCS class II drugs may qualify for biological exemptions if reliable and validated modeling is used. Here, we sought to establish physiologically based pharmacokinetic (PBPK) models, in vitro-in vivo relationship (IVIVR), and VBE models for enteric-coated omeprazole capsules, to establish a clinically-relevant dissolution specification (CRDS) for screening BE and non-BE batches, and to ultimately develop evaluation criteria for generic omeprazole enteric-coated capsules. To establish omeprazole's IVIVR based on the PBPK model, we explored its in vitro dissolution conditions and then combined in vitro dissolution profile studies with in vivo clinical trials. The predicted omeprazole pharmacokinetics (PK) profiles and parameters closely matched the observed PK data. Based on the VBE results, the bioequivalence study of omeprazole enteric-coated capsules required at least 48 healthy Chinese subjects. Based on the CRDS, the capsules' in vitro dissolution should not be < 28%-54%, < 52%, or < 80% after two, three, and six hours, respectively. Failure to meet these dissolution criteria may result in non-bioequivalence. Here, PBPK modeling and IVIVR methods were used to bridge the in vitro dissolution of the drug with in vivo PK to establish the BE safety space of omeprazole enteric-coated capsules. The strategy used in this study can be applied in BE studies of other BCS II generics to obtain biological exemptions and accelerate drug development.

Rapid identification of illegal synthetic adulterants in herbal anti-diabetic medicines using near infrared spectroscopy.

We created a rapid detection procedure for identifying herbal medicines illegally adulterated with synthetic drugs using near infrared spectroscopy. This procedure includes a reverse correlation coefficient method (RCCM) and comparison of characteristic peaks. Moreover, we made improvements to the RCCM based on new strategies for threshold settings. Any tested herbal medicine must meet two criteria to be identified with our procedure as adulterated. First, the correlation coefficient between the tested sample and the reference must be greater than the RCCM threshold. Next, the NIR spectrum of the tested sample must contain the same characteristic peaks as the reference. In this study, four pure synthetic anti-diabetic drugs (i.e., metformin, gliclazide, glibenclamide and glimepiride), 174 batches of laboratory samples and 127 batches of herbal anti-diabetic medicines were used to construct and validate the procedure. The accuracy of this procedure was greater than 80%. Our data suggest that this protocol is a rapid screening tool to identify synthetic drug adulterants in herbal medicines on the market.

[Feasibility of the extended application of near infrared universal quantitative models].

Construction of a successful near infrared analysis model is a complex task. It spends a lot of manpower and material resources, and is restricted by sample collection and model optimization. So it is important to study on the extended application of the existing near infrared (NIR) models. In this paper, cephradine capsules universal quantitative model was used as an example to study on the feasibility of its extended application. Slope/bias correction and piecewise direct standardization correction methods were used to make the universal model to fit to predict the intermediates in manufacturing processes of cephradine capsules, such as the content of powder blend or granules. The results showed that the corrected NIR universal quantitative model can be used for process control although the results of the model correction by slope/bias or piecewise direct standardization were not as good as that of model updating. And it also indicated that the model corrected by slope/bias is better than that by piecewise direct standardization. Model correction provided a new application for NIR universal models in process control.