Oral bioavailability prediction

The genesis of in silico oral bioavailability predictions can be traced back to Lip-inski s Rule of Five and others qualitative attempts to describe drug-like molecules [13-15]. These processes are useful primarily as a qualitative tool in the early stage library design and in the candidate selection. Despite its large number of falsepositive results, Lipinski s Rule of Five has come into wide use as a qualitative tool to help the chemist design bioavailable compounds. It was concluded that compounds are most likely to have poor absorption when the molecular weight is >500, the calculated octan-l-ol/water partition coefficient (c log P) is >5, the number of H-bond donors is >5, and the number of H-bond acceptors is >10. Computation of these properties is now available as an ADME (absorption, distribution, metabolism, excretion) screen in commercial software such as Tsar (from Accelrys). The rule-of-5 should be seen as a qualitative, rather than quantitative, predictor of absorption and permeability [16, 17]. 

Finally, one of the main limitations of this model is the large false-positive rate and large experimental errors. Indeed, the primary limitation of the QSAR and in silico models is the high false-positive rates in oral bioavailability predictions. 

This model integrates existing in vitro data, such as Caco-2 permeability (Papp) and metabolic stability in liver S9 or microsomes, to estimate bioavailability as being either low, medium, or high. Oral bioavailability predictions for not only humans but also other species can be made by using the metabolic stability values of drugs in liver microsomal enzyme preparations from that species. A premise of this model is that metabolic clearance is more important than renal or biliary clearance in determining bioavailability. However, despite the lack of in vitro renal... 

The use of Caco-2 cell permeability studies has resulted in more accurate oral bioavailability predictions. Using the predicted hepatic clearance for compound X in humans (see above), estimating Fa by extrapolation from the Caco-2 cell Papp and assuming hepatic blood flow for humans (see, for example Rane et al., 1977) of 20 ml min 1 kg the human oral bioavailability of 69-98% is predicted for compound X. This compares well with the known oral bioavailability of this compound in rats and dogs (83 and 72%, respectively). 

Oral absorption and bioavailability, prediction of, 41 (2003) 1 Organophosphorus pesticides, pharmacology of, 8 (1971) 1 Oxopyranoazines and oxopyranoazoles,... 

Yoshida and Topliss compiled a dataset of 232 structurally diverse drugs (Table 16.4) and evaluated the possibility of constructing a predictive model for human oral bioavailability on categorical data [28]. The bioavailability data were classified into four categories ... 

L. X., Predicting human oral bioavailability of a compound development of a novel quantitative structure-bioavailability relationship, Pharm. 

A model for predicting oral bioavailability is an important tool, both in the early phases of drug discovery to select the most promising leads for further optimization, and in the later stages to select candidates for clinical development. The... 

Further analysis yielded new models for each of the chemical classes with improved statistical significance. The final model for nonaromatics contained six descriptors and had an Rs of 0.932 (leave-one-out 0.878), the final model for the aromatics contained 21 descriptors and had an Rs of 0.942 (leave-one-out 0.823), and the final model for the heteroaromatics contained 13 descriptors and had an Rs value of 0.863 (leave-one-out 0.758). These statistical results were considered reliable enough for the models to be regarded as predictive. The analysis did yield some interesting insights into the impact of various structural fragments on human oral bioavailability. However, these observations were based on the sign of the coefficient and so must be treated with some caution. 

Fig. 19.5. In silico model for estimating oral bioavailability. Plot of predicted versus observed bioavailability in humans for 591 drugs [22],...

Genetic programming, a specific form of evolutionary computing, has recently been used for predicting oral bioavailability [23], The results show a slight improvement compared with the ORMUCS Yoshida-Topliss approach. This supervised learning method and other described methods demonstrate that at least qualitative (binned) predictions of oral bioavailability seem tractable directly from the structure. 

Fig. 19.7. Correlation between predicted oral absorption based on polar surface area (PSA) and in vivo oral bioavailability for a series of beta-blockers. The nonlinearity is related to the different levels of P-gp efflux and differences in CYP3A4 metabolism of these compounds [25],...

It is important to remember that absolute oral bioavailability is a function of both absorption and first-pass metabolism. Therefore, a linear approach to predicting absolute oral bioavailability based on a single parameter, such as rate or extent of absorption (fraction of dose absorbed or estimated dose absorbed) or the rate of metabolism (microsomal or hepatic intrinsic clearance), may result in an inaccu-... 

In vitro Model for Predicting Oral Bioavailability in Human and other Species... 

Absorption and clearance are two of the fundamental parameters that determine oral bioavailability. There are many in vitro methods to assess the absorption and metabolic potential of a given molecule, and it can be argued that a combination of these data should produce a model capable of predicting oral bioavailability. Such a model, based on a graphical approach has recently been published [26]. 

J., Evolutionary computational methods to predict oral bioavailability QSPRs, Curr. Opin. Drug Disc. Dev. 2002, 5, 44-51. 

Lau, Y.Y. et al. 2004. Evaluation of a novel in vitro Caco-2 hepatocyte hybrid system for predicting in vivo oral bioavailability. Drug Met. Disp. 32 937. 

Andrews CW, Bennett L and Yu LX (2000) Predicting Human Oral Bioavailability of a Compound Development of a Novel Quantitative Structure-Bioavailability Relationship. Pharm Res 17 pp 639-644. 

The two major determinants of oral bioavailability are intestinal absorption and hepatic first-pass elimination. Caco-2 cells are useful to predict intestinal absorption. The validity of this application has been demonstrated in a number of studies in which percent drug absorption in humans was correlated with Caco-2 permeability coefficients.35-39113114... 

Dias, V. and Yatscoff, R.W., An in vitro method for predicting in vivo oral bioavailability of novel immunosuppressive drugs, Clin. Biochem., 29, 43,1996. 

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