A Promising New Approach for In Silico Prediction of Drug Concentration Profiles for Drug Candidates Lack of Experimental Pharmacokinetic Data

Abstract

Aim: The purpose of this study is to develop a novel protocol to predict the concentration profiles of a target drug based on the PBPK model of a structurally similar template drug by combining two software for PBPK modeling, the SimCYP simulator and ADMET Predictor. Methods: The method was evaluated by utilizing 13 drug pairs which come from 18 drugs in the built-in database of the SimCYP software. All drug pairs have their Tanimoto scores no less than 0.5. Three versions (V1, V2 and V3) of models for the target drug were constructed by gradually replacing the corresponding parameters of the template drug with those predicted by ADME Predictor for the target drug. Normalized RMSE and Wilcoxon rank-sum test were introduced for the evaluation of the model performance. Results: Overall, V3 models demonstrated better performance than the V1 and V2 models did. The relationship between the model performance and structural similarity of drug pairs was also explored. Three protocols have come out as guidance on how to build PBPK models for target drugs: (1) V1 models are recommended when the structural similarity is very high; (2) V2 models are recommended when the similarity is below 0.65 or high than 0.85; (3) V3 models are recommended when the similarity is below 0.85. Conclusion: By leveraging the prediction accuracy and application practicality, this novel approach has a great promise in predicting the preliminary PK profiles for novel drugs, propelling the drug discovery process by suggesting drug candidates with promising PK profiles.

Physiologically Based Toxicokinetic Modeling of Bisphenols in Zebrafish (Danio rerio) Accounting for Variations in Metabolic Rates, Brain Distribution, and Liver Accumulation

“…Predicted concentrations for whole fish or individual organs were then compared with measured data in terms of area under the curve (AUC) (μg/g/day), maximal concentration ( C max ) (μg/g), half-life ( t 1/2 ) (days), and bioconcentration factor (BCF). The goodness of fit was assessed by calculating the normalized root mean squared error (NRMSE) 54 values for predicted versus observed data for all organs combined. NRMSE for each compound prediction was calculated by normalizing the RMSE to the maximal predicted concentration for each organ.…”