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IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 3: Identifying gaps in system parameters by analysing In Silico performance across different compound classes. | LitMetric

AI Article Synopsis

  • - Three Physiologically Based Pharmacokinetic (PBPK) software packages (GI-Sim, Simcyp®, GastroPlus™) were assessed for predicting human drug absorption as part of the OrBiTo project, revealing issues with bioavailability predictions for various compounds.
  • - The models consistently underestimated oral bioavailability (F) for low-permeability and acidic compounds, indicating potential flaws in understanding intestinal absorption processes and solubility settings.
  • - High logP and poorly water-soluble compounds also had lower than expected bioavailability, pointing to the need for improved solubility models and more accurate input data, but caution was noted due to variability in available data used for predictions.

Article Abstract

Three Physiologically Based Pharmacokinetic software packages (GI-Sim, Simcyp® Simulator, and GastroPlus™) were evaluated as part of the Innovative Medicine Initiative Oral Biopharmaceutics Tools project (OrBiTo) during a blinded "bottom-up" anticipation of human pharmacokinetics. After data analysis of the predicted vs. measured pharmacokinetics parameters, it was found that oral bioavailability (F) was underpredicted for compounds with low permeability, suggesting improper estimates of intestinal surface area, colonic absorption and/or lack of intestinal transporter information. F was also underpredicted for acidic compounds, suggesting overestimation of impact of ionisation on permeation, lack of information on intestinal transporters, or underestimation of solubilisation of weak acids due to less than optimal intestinal model pH settings or underestimation of bile micelle contribution. F was overpredicted for weak bases, suggesting inadequate models for precipitation or lack of in vitro precipitation information to build informed models. Relative bioavailability was underpredicted for both high logP compounds as well as poorly water-soluble compounds, suggesting inadequate models for solubility/dissolution, underperforming bile enhancement models and/or lack of biorelevant solubility measurements. These results indicate areas for improvement in model software, modelling approaches, and generation of applicable input data. However, caution is required when interpreting the impact of drug-specific properties in this exercise, as the availability of input parameters was heterogeneous and highly variable, and the modellers generally used the data "as is" in this blinded bottom-up prediction approach.

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Source
http://dx.doi.org/10.1016/j.ejps.2016.09.037DOI Listing

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