Anne Hersey

Rate-limited steps of human oral absorption and QSAR studies

AbstractPurpose. To classify the dissolution and diffusion rate-limited drugs and establish quantitative relationships between absorption and molecular descriptors. Methods. Absorption consists of kinetic transit processes in which dissolution, diffusion, or perfusion processes can become the rate-limited step. The absorption data of 238 drugs have been classified into either dissolution or diffusion rate-limited based on an equilibrium method developed from solubility, dose, and percentage of absorption. A nonlinear absorption model derived from first-order kinetics has been developed to identify the relationship between percentage of drug absorption and molecular descriptors. Results. Regression analysis was performed between percentage of absorption and molecular descriptors. The descriptors used were ClogP, molecular polar surface area, the number of hydrogen-bonding acceptors and donors, and Abraham descriptors. Good relationships were found between absorption and Abraham descriptors or ClogP. Conclusions. The absorption models can predict the following three BCS (Biopharmaceutics Classification Scheme) classes of compounds: class I, high solubility and high permeability; class III, high solubility and low permeability; class IV, low solubility and low permeability. The absorption models overpredict the absorption of class II, low solubility and high permeability compounds because dissolution is the rate-limited step of absorption.

Correlation and prediction of a large blood-brain distribution data set: an LFER study

We report linear free energy relation (LFER) models of the equilibrium distribution of molecules between blood and brain, as log BB values. This method relates log BB values to fundamental molecular properties, such as hydrogen bonding capability, polarity/polarisability and size. Our best model of this form covers 148 compounds, the largest set of log BB data yet used in such a model, resulting in R(2)=0.745 and e.s.d.=0.343 after inclusion of an indicator variable for carboxylic acids. This represents rather better accuracy than a number of previously reported models based on subsets of our data. The model also reveals the factors that affect log BB: molecular size and dispersion effects increase brain uptake, while polarity/polarisability and hydrogen-bond acidity and basicity decrease it. By splitting the full data set into several randomly selected training and test sets, we conclude that such a model can predict log BB values with an accuracy of less than 0.35 log units. The method is very rapid-log BB can be calculated from structure at a rate of 700 molecules per minute on a silicon graphics O(2).

Estimation of Molecular Linear Free Energy Relationship Descriptors by a Group Contribution Approach. 2. Prediction of Partition Coefficients

A previously published method for the prediction of molecular linear free energy relationship descriptors is tested against experimentally determined partition coefficients in various solvent systems. Sets of partition data between water and octanol, cyclohexane, and chloroform were taken from the literature. For each set of partition data used, r2 values ranged from 0.8 to 0.9 and RMS errors from 0.7 to 1.0 log unit, comparable to errors obtained with previously published models for octanol-water partition. Modified solvation equations for water-octanol and water-cyclohexane partition are presented, and their implications discussed. The possibility of applying the current approach to a wide range of solvation and transport properties is put forward.

Evaluation of rat intestinal absorption data and correlation with human intestinal absorption

The absorption of 111 drug and drug-like compounds was evaluated from 111 references based on the ratio of urinary excretion of drugs following oral and intravenous administration to intact rats and biliary excretion of bile duct-cannulated rats. Ninety-eight drug compounds for which both human and rat absorption data were available were selected for correlation analysis between the human and rat absorption. The result shows that the extent of absorption in these two species is similar. For 94% of the drugs the absorption difference between humans and rats is less than 20% and for 98% of drugs the difference is less than 30%. There is only one drug for which human absorption is significantly different from rat absorption. The standard deviation is 11% between human and rat absorption. The linear relationship between human and rat absorption forced through the origin, as determined by least squares regression, is %Absorption (human)=0.997%Absorption (rat) (n=98, SD=11). It is suggested that the absorption in rats could be used as an alternative method to human absorption in pre-clinical oral absorption studies.

On the mechanism of human intestinal absorption

In order to investigate whether the main step in intestinal absorption in humans is dominated by partition or by diffusion, we have transformed % human intestinal absorption into a first-order rate constant, and have regressed the latter, as logk, against our solvation parameters. The obtained regression coefficients are compared with those for diffusion and partition processes. The coefficients in the logk equation are completely different to those for water/solvent partitions, but are very similar to those for processes (not involving transport through membranes) in which diffusion is the major step. It is suggested that the main step in the absorption process is diffusion through a stagnant mucus layer, together with transfer across the mucusmid R:membrane interface. It is further shown that for strong Bronsted acids and bases, the rate constant for absorption of ionic species is close to that for absorption of the corresponding neutral species, so that to a first approximation the % intestinal absorption can be calculated from properties of the neutral species.

Estimation of Molecular Linear Free Energy Relationship Descriptors. 4. Correlation and Prediction of Cell Permeation

AbstractPurpose. The passage of molecules across cell membranes is acrucial step in many physiological processes. We therefore seek physicalmodels of this process, in order to predict permeation for new molecules,and to better understand the important interactions which determinethe rate of permeation. Methods. Several sets of cell permeation data reported byCollander have been correlated against calculated Linear Free Energy Relation(LFER) descriptors. These descriptors, taken as the sum of fragmentalcontributions, cover the size, polarity, polarizabilty, and hydrogenbonding capacity of each molecule. Results. For 36 values permeation into Chara ceratophyllacells, a model (sd = 0.24) dominated by hydrogen bond acidity is found, whilefor 63 rates of permeation values into Nitella cells a very similar modelyields sd = 0.46. Comparisons between the two cell types are madedirectly for 17 compounds in both data sets, indicate differences of asimilar magnitude to the standard deviations of the above models. Thetwo data sets can be combined to yield a generic model of rates ofpermeation into cells, resulting in an sd value of 0.46 for a total of100 data points. Conclusions. Models allowing accurate prediction of cell permeationhave been constructed using 100 experimental data. We demonstratethat hydrogen bond acidity is the dominating factor in determining cellpermeation for two distinct species of algal cell.

Theoretical prediction of the polarity/polarizability parameter π2H

Ab initio and DFT calculations on the structure and properties of over 98 molecules are reported. Properties calculated for the molecules are assessed for their ability to correlate and predict experimentally derived values of the polarity/polarizability parameter, π. Using multivariate linear regression and partial least squares methods, four properties stand out as predictors of π: the molecular dipole moment, the polarizability, the CHelpG atomic charges and the frontier molecular orbital energies. These properties correlate π to close to the standard deviation in a previously published fragmental approach. The partial least squares method is shown to result in significantly better predictions for an external validation set.

Pharmacokinetic/pharmacodynamic modelling of the EEG effects of opioids: the role of complex biophase distribution kinetics.

The objective of this investigation is to characterize the role of complex biophase distribution kinetics in the pharmacokinetic-pharmacodynamic correlation of a wide range of opioids. Following intravenous infusion of morphine, alfentanil, fentanyl, sufentanil, butorphanol and nalbuphine the time course of the EEG effect was determined in conjunction with blood concentrations. Different biophase distribution models were tested for their ability to describe hysteresis between blood concentration and effect. In addition, membrane transport characteristics of the opioids were investigated in vitro, using MDCK:MDR1 cells and in silico with QSAR analysis. For morphine, hysteresis was best described by an extended-catenary biophase distribution model with different values for k1e and keo of 0.038+/-0.003 and 0.043+/-0.003 min(-1), respectively. For the other opioids hysteresis was best described by a one-compartment biophase distribution model with identical values for k1e and keo. Between the different opioids, the values of k1e ranged from 0.04 to 0.47 min(-1). The correlation between concentration and EEG effect was successfully described by the sigmoidal Emax pharmacodynamic model. Between opioids significant differences in potency (EC50 range 1.2-451 ng/ml) and intrinsic activity (alpha range 18-109 microV) were observed. A statistically significant correlation was observed between the values of the in vivo k1e and the apparent passive permeability as determined in vitro in MDCK:MDR1 monolayers. It can be concluded that unlike other opioids, only morphine displays complex biophase distribution kinetics, which can be explained by its relatively low passive permeability and the interaction with active transporters at the blood-brain barrier.

Pyrazolopyridazine alpha-2-delta-1 ligands for the treatment of neuropathic pain

Optimization of the novel alpha-2-delta-1 ligand 4 provided compounds 37 and 38 which have improved DMPK profiles, good in vivo analgesic activity and in vitro selectivity over alpha-2-delta-2. An in-house P-gp prediction programme and the MetaSite software package were used to help solve the specific problems of high P-gp efflux and high in vivo clearance.

Theoretical prediction of partition coefficients via molecular electrostatic and electronic properties

Previously published methods for calculation of Abrahams polarity/polarizability and hydrogen bond acidity and basicity descriptors are validated for their ability to predict the various partition coefficients of 80 challenging molecules. As well as this indirect validation, accurate log P predictions are shown to be possible by using directly the fundamental molecular properties used in the calculation of descriptors. From a general point of view, the van der Waals and hydrogen bond interactions present between the solute and the water/solvent system can be represented by charge-based interactions, which are partitioned into a positive and a negative term (Sigma(T)V(Max) and Sigma(T)V(Min)), dipole-based interactions (mu) and induced dipole-based interactions (alpha); further stabilization is possible if solute and solvent densities come into contact and overlap (Sigma(T)E). A discussion is opened on the possibility to extend this set to describe systems with electron donor/acceptor interactions other than hydrogen bonding.