ABSTRACT
Introduction: The oral route is the most convenient way of administrating drugs. Therefore, accurate determination of oral bioavailability is paramount during drug discovery and development. Quantitative structure-property relationship (QSPR), rule-of-thumb (RoT) and physiologically based-pharmacokinetic (PBPK) approaches are promising alternatives to the early oral bioavailability prediction.
Areas covered: The authors give insight into the factors affecting bioavailability, the fundamental theoretical framework and the practical aspects of computational methods for predicting this property. They also give their perspectives on future computational models for estimating oral bioavailability.
Expert opinion: Oral bioavailability is a multi-factorial pharmacokinetic property with its accurate prediction challenging. For RoT and QSPR modeling, the reliability of datasets, the significance of molecular descriptor families and the diversity of chemometric tools used are important factors that define model predictability and interpretability. Likewise, for PBPK modeling the integrity of the pharmacokinetic data, the number of input parameters, the complexity of statistical analysis and the software packages used are relevant factors in bioavailability prediction. Although these approaches have been utilized independently, the tendency to use hybrid QSPR-PBPK approaches together with the exploration of ensemble and deep-learning systems for QSPR modeling of oral bioavailability has opened new avenues for development promising tools for oral bioavailability prediction.
Article Highlights
Oral bioavailability is an important pharmacokinetic property for oral drugs and is one of the bottlenecks during the drug discovery and development stages.
Two computational strategies have mainly been used to model oral bioavailability in humans, one based on the quantitative structure-property relationship (QSPR) and rule-of-thumb, and the other on physiologically based-pharmacokinetic (PBPK).
Several factors are involved in the variables results obtained in the computational prediction of oral bioavailability with the QSPR approach: i) the database used, ii) type of molecular descriptor and iii) statistical method employed to obtain the models.
Similar to QSPR approach, PBPK methods depend on the extent, quality and relevance of the input data used.
The accurate computational prediction of oral bioavailability using QSPR and PBPK approaches is still an unsolved problem.
The use of hybrid QSPR-PBPK approaches along with the exploration of ensemble and deep-learning systems for QSPR modeling of oral bioavailability could be a new perspective in the development of promising tools for predicting oral bioavailability.
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Declaration of Interest
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. One referee declares that they are an employee of Pfizer Inc while another declares that they are an employee of Johnson & Johnson.