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A novel chemometric method for the prediction of human oral bioavailability.

ABSTRACT: Orally administered drugs must overcome several barriers before reaching their target site. Such barriers depend largely upon specific membrane transport systems and intracellular drug-metabolizing enzymes. For the first time, the P-glycoprotein (P-gp) and cytochrome P450s, the main line of defense by limiting the oral bioavailability (OB) of drugs, were brought into construction of QSAR modeling for human OB based on 805 structurally diverse drug and drug-like molecules. The linear (multiple linear regression: MLR, and partial least squares regression: PLS) and nonlinear (support-vector machine regression: SVR) methods are used to construct the models with their predictivity verified with five-fold cross-validation and independent external tests. The performance of SVR is slightly better than that of MLR and PLS, as indicated by its determination coefficient (R(2)) of 0.80 and standard error of estimate (SEE) of 0.31 for test sets. For the MLR and PLS, they are relatively weak, showing prediction abilities of 0.60 and 0.64 for the training set with SEE of 0.40 and 0.31, respectively. Our study indicates that the MLR, PLS and SVR-based in silico models have good potential in facilitating the prediction of oral bioavailability and can be applied in future drug design.

SUBMITTER: Xu X

PROVIDER: S-EPMC3397506 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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A novel chemometric method for the prediction of human oral bioavailability.

Xu Xue X Zhang Wuxia W Huang Chao C Li Yan Y Yu Hua H Wang Yonghua Y Duan Jinyou J Ling Yang Y

International journal of molecular sciences 20120607 6

Orally administered drugs must overcome several barriers before reaching their target site. Such barriers depend largely upon specific membrane transport systems and intracellular drug-metabolizing enzymes. For the first time, the P-glycoprotein (P-gp) and cytochrome P450s, the main line of defense by limiting the oral bioavailability (OB) of drugs, were brought into construction of QSAR modeling for human OB based on 805 structurally diverse drug and drug-like molecules. The linear (multiple li ...[more]

PMID: 22837674

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Project description:BackgroundPoor oral bioavailability is an important parameter accounting for the failure of the drug candidates. Approximately, 50% of developing drugs fail because of unfavorable oral bioavailability. In silico prediction of oral bioavailability (%F) based on physiochemical properties are highly needed. Although many computational models have been developed to predict oral bioavailability, their accuracy remains low with a significant number of false positives. In this study, we present an oral bioavailability model based on systems biological approach, using a machine learning algorithm coupled with an optimal discriminative set of physiochemical properties.ResultsThe models were developed based on computationally derived 247 physicochemical descriptors from 2279 molecules, among which 969, 605 and 705 molecules were corresponds to oral bioavailability, intestinal absorption (HIA) and caco-2 permeability data set, respectively. The partial least squares discriminate analysis showed 49 descriptors of HIA and 50 descriptors of caco-2 are the major contributing descriptors in classifying into groups. Of these descriptors, 47 descriptors were commonly associated to HIA and caco-2, which suggests to play a vital role in classifying oral bioavailability. To determine the best machine learning algorithm, 21 classifiers were compared using a bioavailability data set of 969 molecules with 47 descriptors. Each molecule in the data set was represented by a set of 47 physiochemical properties with the functional relevance labeled as (+bioavailability/-bioavailability) to indicate good-bioavailability/poor-bioavailability molecules. The best-performing algorithm was the logistic algorithm. The correlation based feature selection (CFS) algorithm was implemented, which confirms that these 47 descriptors are the fundamental descriptors for oral bioavailability prediction.ConclusionThe logistic algorithm with 47 selected descriptors correctly predicted the oral bioavailability, with a predictive accuracy of more than 71%. Overall, the method captures the fundamental molecular descriptors, that can be used as an entity to facilitate prediction of oral bioavailability.

Project description:The leukotriene receptor antagonist Montelukast (MTK) is an approved medication for the treatment of asthma and allergic rhinitis. The existing marketed tablet forms of MTK exhibit inconsistent uptake and bioavailability, which partially explains the presence of a significant proportion of MTK low- and non-responders in the population. Besides that, tablets are suboptimal formulations for patients suffering from dysphagia, for example, seen in patients with neurodegenerative diseases such as Alzheimer's disease, a disease with increasing interest in repurposing of MTK. This, and the need for an improved bioavailability, triggered us to reformulate MTK. Our aim was to develop a mucoadhesive MTK film with good safety and improved pharmacological features, i.e., an improved bioavailability profile in humans as well as in a mouse model of Alzheimer's disease. We tested dissolution of the MTK mucoadhesive film and assessed pharmacoexposure and kinetics after acute and chronic oral application in mice. Furthermore, we performed a Phase I analysis in humans, which included a comparison with the marketed tablet form as well as a quantitative analysis of the MTK levels in the cerebrospinal fluid. The novel MTK film demonstrated significantly improved bioavailability compared to the marketed tablet in the clinical Phase 1a study. Furthermore, there were measurable amounts of MTK present in the cerebrospinal fluid (CSF). In mice, MTK was detected in serum and CSF after acute and chronic exposure in a dose-dependent manner. The mucoadhesive film of MTK represents a promising alternative for the tablet delivery. The oral film might lower the non-responder rate in patients with asthma and might be an interesting product for repurposing of MTK in other diseases. As we demonstrate Blood-Brain-Barrier (BBB) penetrance in a preclinical model, as well as in a clinical study, the oral film of MTK might find its use as a therapeutic for acute and chronic neurodegenerative diseases such as dementias and stroke.

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A novel chemometric method for the prediction of human oral bioavailability.

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A novel chemometric method for the prediction of human oral bioavailability.

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