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Neil Parrott

Publications and source records attributed to Neil Parrott.

7 recordsLinked to original sources
PubMed2006

A novel strategy for physiologically based predictions of human pharmacokinetics.

BACKGROUND: The major aim of this study was to develop a strategy for predicting human pharmacokinetics using physiologically based pharmacokinetic (PBPK) modelling. This was compared with allometry (of plasma concentration-time profiles using the Dedrick approach), in order to determine the best approaches and strategies for the prediction of human pharmacokinetics. METHODS: PBPK and Dedrick predictions were made for 19 F. Hoffmann-La Roche compounds. A strategy for the prediction of human pharmacokinetics using PBPK modelling was proposed in this study. Predicted values (pharmacokinetic parameters, plasma concentrations) were compared with observed values obtained after intravenous and oral administration in order to assess the accuracy of the prediction methods. RESULTS: By following the proposed strategy for PBPK, a prediction would have been made prospectively for approximately 70% of the compounds. The prediction accuracy for these compounds in terms of the percentage of compounds with an average-fold error of <2-fold was 83%, 50%, 75%, 67%, 92% and 100% for apparent oral clearance (CL/F), apparent volume of distribution during terminal phase after oral administration (V(z)/F), terminal elimination half-life (t(1/2)), peak plasma concentration (C(max)), area under the plasma concentration-time curve (AUC) and time to reach C(max) (t(max)), respectively. For the other 30% compounds, unacceptable prediction accuracy was obtained in animals; therefore, a prospective prediction of human pharmacokinetics would not have been made using PBPK. For these compounds, prediction accuracy was also poor using the Dedrick approach. In the majority of cases, PBPK gave more accurate predictions of pharmacokinetic parameters and plasma concentration-time profiles than the Dedrick approach. CONCLUSIONS: Based on the dataset evaluated in this study, PBPK gave reasonable predictions of human pharmacokinetics using preclinical data and is the recommended approach in the majority of cases. In addition, PBPK modelling is a useful tool to gain insights into the properties of a compound. Thus, PBPK can guide experimental efforts to obtain the relevant information necessary to understand the compound's properties before entry into human, ultimately resulting in a higher level of prediction accuracy.

Animals↗
PubMed2006

Predicting pharmacokinetic food effects using biorelevant solubility media and physiologically based modelling.

BACKGROUND: Food-induced changes in gastric emptying time, gastric pH and/or intestinal fluid composition may have an impact on the pharmacokinetics of drugs. The aim of this work was to use mathematical models describing physiology in fed and fasted states together with biorelevant solubility and degradation data to simulate food effects for six compounds from recent Roche projects. METHODS: The solubility of each compound was measured in different biorelevant media: simulated human gastric fluid for the fasted and fed state, simulated human intestinal fluid for the fasted, fed and high-fat state, and simulated human colonic fluid for the upper and the lower colon. A physiologically based absorption model was developed in GastroPlustrade mark for each compound using permeability, solubility, metabolism and distribution data. By incorporating the appropriate physiological parameters and solubility data into the model, the oral pharmacokinetics of each drug was simulated under fasted, fed and/or high-fat conditions. Predicted and observed plasma concentration-time profiles and food effects were compared for a range of doses to assess the accuracy of the simulations. RESULTS: The models were able to distinguish between minor and significant food effects. The simulation captured well the magnitude of the food effects and for the six compounds correctly predicted the observed plasma exposure in fasted, fed and high-fat conditions. CONCLUSION: Biorelevant solubility tests can be used together with physiologically based absorption models to predict clinical food effects caused by solubility and/or dissolution rate limitations.

Area Under Curve↗
PubMed2005

A strategy for preclinical formulation development using GastroPlus as pharmacokinetic simulation tool and a statistical screening design applied to a dog study.

The aim of this paper is to propose a pharmaceutical risk assessment strategy that goes beyond the usual characterisation of a clinical candidate molecule according to the biopharmaceutical classification system (BCS). This strategy was evaluated for a new CNS drug with poor solubility and good permeability. In a first step, GastroPlus was used to simulate the absorption process based on preformulation data. These input data involved a physicochemical drug characterisation including drug solubility measurements in simulated physiological media, as well as permeability determination. Further computer simulations were conducted to determine the sensitivity to changes of selected input values. Thus, oral bioavailability prediction was studied as a function of the particle size and drug solubility. The second part of the presented strategy for preclinical formulation development was to test specially designed formulations in a 2(3) screening factorial plan using the dog as the animal model. The factors were the dosage form, food effect and dose strength. One of the two experimental formulations was a capsule filled with the micronised drug, whereas the other formulation was a surfactant solution of the drug. Accordingly, a "worst case" formulation was compared with a "best case" drug solution over the clinically relevant dose range in fasted and fed dogs. The results of the computer simulation indicated that a fraction of the dose is dissolved in the stomach and precipitates partially in the small intestine. The simulation predicted almost full drug absorption during the GI transit time. Interestingly, the simulation implies that stomach drug solubility had little impact on overall fraction absorbed. The results also showed that changes of particle size and reference solubility within two orders of magnitude hardly affected the oral bioavailability. This in silico deduction was subsequently compared with the results of the dog studies. Indeed a surfactant drug solution showed no clear biopharmaceutical superiority over a solid capsule formulation on the average of both dose strengths in fasted and fed dogs. Despite the substantial variability of the in vivo data, the factorial screening design indicated marginal significant interaction between the dose level and feeding status. This can be viewed as a flag for the planning of further studies, since a potential effect of one factor may depend on the level of the other. In summary, the GastroPlus simulation together with the statistically designed dog study provided a thorough biopharmaceutical assessment of the new CNS drug. Based on these findings, it was decided to develop a standard granulate in capsules for phase I studies. More sophisticated formulation options were abandoned and so the clinical formulation development was conducted in a cost-efficient way.

Administration, Oral↗
PubMed2005

An evaluation of the utility of physiologically based models of pharmacokinetics in early drug discovery.

Generic physiologically-based models of pharmacokinetics were evaluated for early drug discovery. Plasma profiles after intravenous and oral dosing were simulated in rat for 68 compounds from six chemical classes. Input data consisted of structure based predictions of lipophilicity, ionization, and protein binding plus intrinsic clearance measured in rat hepatocytes, single measured values of aqueous solubility, and artificial membrane permeability. LogP of compounds was high with a mean of 3.9 while free fraction in plasma (mean 9%) and solubility (mean 37 microg/mL) were low. Predicted and observed clearance and volume showed mean fold-error and R2 of 1.8, 0.56, and 1.9, 0.25 respectively. Predicted bioavailability showed strong bias to under prediction correlated to very low aqueous solubility and a theoretical correction for bile salt solubilization in vivo brought some improvement in average prediction error (to 31%). Overall, this evaluation shows that generic simulation may be applicable for typical drug-like compounds to predict differences in pharmacokinetic parameters of more than twofold based upon minimal measured input data. However verification of the simulations with in vivo data for a few compounds of each compound class is recommended since recent discovery compounds may have properties beyond the scope of the current generic models.

Animals↗
PubMed2005

Application of full physiological models for pharmaceutical drug candidate selection and extrapolation of pharmacokinetics to man.

This paper describes how we are applying physiologically based models of pharmacokinetics as an integrated part in the research and preclinical development of novel drugs. The modeling and simulation tools and techniques used are briefly reviewed and the strategy for application in drug research is described. Three examples illustrate how such models may be applied at different stages ranging from early application prior to in vivo studies, through clinical candidate selection to the estimation of human kinetics and dose selection prior to clinical studies. Although there are obvious restrictions related to limited input data at the earlier stages, the examples illustrate some of the advantages of the approach compared to other more empirical methods. These advantages will be fully exploited with more widespread use of physiological models as powerful and user-friendly software make them accessible to non-specialists.

Drug Design↗
PubMed2002

Prediction of intestinal absorption: comparative assessment of GASTROPLUS and IDEA.

We have assessed two commercial software tools employing physiologically based models for prediction of intestinal absorption in human. IDEA 2.0 and GASTROPLUS 3.1.0 were compared both in their ability to predict fraction absorbed for a set of 28 drugs and in terms of the functionality offered. The emphasis was placed on the practical usefulness to pharmaceutical drug discovery. Predictions were assessed for three levels of input data (i) pure in silico input, (ii) thermodynamic solubility and in silico permeability, (iii) thermodynamic solubility and human colon carcinoma cell line (CACO-2) permeability. We found the pure in silico prediction ability of the tools to be comparable with 70% correct classification rate. With measured input data the IDEA prediction rate improved to 79% while GASTROPLUS stayed at 70%. In terms of functionality GASTROPLUS is a powerful system for the trained user. Open access to model parameters, diagnostic tools and the ability to integrate data make it particularly suitable for the later stages of discovery and development. IDEA is web based and presents a simple interface suitable for widespread use with minimal training. However the limited functionality and inconvenient handling of multiple compound batches currently restrict the usefulness of version 2.0 for drug discovery.

Intestinal Absorption↗