IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 4: Prediction accuracy and software comparisons with improved data and modelling strategies.

Oral drug absorption is a complex process depending on many factors, including the physicochemical properties of the drug, formulation characteristics and their interplay with gastrointestinal physiology and biology. Physiological-based pharmacokinetic (PBPK) models integrate all available information on gastro-intestinal system with drug and formulation data to predict oral drug absorption. The latter together with in vitro-in vivo extrapolation and other preclinical data on drug disposition can be used to predict plasma concentration-time profiles in silico. Despite recent successes of PBPK in many areas of drug development, an improvement in their utility for evaluating oral absorption is much needed. Current status of predictive performance, within the confinement of commonly available in vitro data on drugs and formulations alongside systems information, were tested using 3 PBPK software packages (GI-Sim (ver.4.1), Simcyp® Simulator (ver.15.0.86.0), and GastroPlus™ (ver.9.0.00xx)). This was part of the Innovative Medicines Initiative (IMI) Oral Biopharmaceutics Tools (OrBiTo) project. Fifty eight active pharmaceutical ingredients (APIs) were qualified from the OrBiTo database to be part of the investigation based on a priori set criteria on availability of minimum necessary information to allow modelling exercise. The set entailed over 200 human clinical studies with over 700 study arms. These were simulated using input parameters which had been harmonised by a panel of experts across different software packages prior to conduct of any simulation. Overall prediction performance and software packages comparison were evaluated based on performance indicators (Fold error (FE), Average fold error (AFE) and absolute average fold error (AAFE)) of pharmacokinetic (PK) parameters. On average, PK parameters (Area Under the Concentration-time curve (AUC0-tlast), Maximal concentration (Cmax), half-life (t1/2)) were predicted with AFE values between 1.11 and 1.97. Variability in FEs of these PK parameters was relatively high with AAFE values ranging from 2.08 to 2.74. Around half of the simulations were within the 2-fold error for AUC0-tlast and around 90% of the simulations were within 10-fold error for AUC0-tlast. Oral bioavailability (Foral) predictions, which were limited to 19 APIs having intravenous (i.v.) human data, showed AFE and AAFE of values 1.37 and 1.75 respectively. Across different APIs, AFE of AUC0-tlast predictions were between 0.22 and 22.76 with 70% of the APIs showing an AFE > 1. When compared across different formulations and routes of administration, AUC0-tlast for oral controlled release and i.v. administration were better predicted than that for oral immediate release formulations. Average predictive performance did not clearly differ between software packages but some APIs showed a high level of variability in predictive performance across different software packages. This variability could be related to several factors such as compound specific properties, the quality and availability of information, and errors in scaling from in vitro and preclinical in vivo data to human in vivo behaviour which will be explored further. Results were compared with previous similar exercise when the input data selection was carried by the modeller rather than a panel of experts on each in vitro test. Overall, average predictive performance was increased as reflected in smaller AAFE value of 2.8 as compared to AAFE value of 3.8 in case of previous exercise.

Computational prediction of drug solubility in fasted simulated and aspirated human intestinal fluid.

PURPOSE: To develop predictive models of apparent solubility (Sapp) of lipophilic drugs in fasted state simulated intestinal fluid (FaSSIF) and aspirated human intestinal fluid (HIF). METHODS: Measured Sapp values in FaSSIF, HIF and phosphate buffer pH 6.5 (PhBpH6.5) for 86 lipophilic drugs were compiled and divided into training (Tr) and test (Te) sets. Projection to latent structure (PLS) models were developed through variable selection of calculated molecular descriptors. Experimentally determined properties were included to investigate their contribution to the predictions. RESULTS: Modest relationships between Sapp in PhBpH6.5 and FaSSIF (R(2) = 0.61) or HIF (R(2) = 0.62) were found. As expected, there was a stronger correlation obtained between FaSSIF and HIF (R(2) = 0.78). Computational models were developed using calculated descriptors alone (FaSSIF, R(2) = 0.69 and RMSEte of 0.77; HIF, R(2) = 0.84 and RMSEte of 0.81). Accuracy improved when solubility in PhBpH6.5 was added as a descriptor (FaSSIF, R(2) = 0.76 and RMSETe of 0.65; HIF, R(2) = 0.86 and RMSETe of 0.69), whereas no improvement was seen when melting point (Tm) or logDpH 6.5 were included in the models. CONCLUSION: Computational models were developed, that reliably predicted Sapp of lipophilic compounds in intestinal fluid, from molecular structures alone. If experimentally determined pH-dependent solubility values were available, this further improved the accuracy of the predictions.

In silico predictions of gastrointestinal drug absorption in pharmaceutical product development: application of the mechanistic absorption model GI-Sim.

Oral drug delivery is the predominant administration route for a major part of the pharmaceutical products used worldwide. Further understanding and improvement of gastrointestinal drug absorption predictions is currently a highly prioritized area of research within the pharmaceutical industry. The fraction absorbed (fabs) of an oral dose after administration of a solid dosage form is a key parameter in the estimation of the in vivo performance of an orally administrated drug formulation. This study discloses an evaluation of the predictive performance of the mechanistic physiologically based absorption model GI-Sim. GI-Sim deploys a compartmental gastrointestinal absorption and transit model as well as algorithms describing permeability, dissolution rate, salt effects, partitioning into micelles, particle and micelle drifting in the aqueous boundary layer, particle growth and amorphous or crystalline precipitation. Twelve APIs with reported or expected absorption limitations in humans, due to permeability, dissolution and/or solubility, were investigated. Predictions of the intestinal absorption for different doses and formulations were performed based on physicochemical and biopharmaceutical properties, such as solubility in buffer and simulated intestinal fluid, molecular weight, pK(a), diffusivity and molecule density, measured or estimated human effective permeability and particle size distribution. The performance of GI-Sim was evaluated by comparing predicted plasma concentration-time profiles along with oral pharmacokinetic parameters originating from clinical studies in healthy individuals. The capability of GI-Sim to correctly predict impact of dose and particle size as well as the in vivo performance of nanoformulations was also investigated. The overall predictive performance of GI-Sim was good as >95% of the predicted pharmacokinetic parameters (C(max) and AUC) were within a 2-fold deviation from the clinical observations and the predicted plasma AUC was within one standard deviation of the observed mean plasma AUC in 74% of the simulations. GI-Sim was also able to correctly capture the trends in dose- and particle size dependent absorption for the study drugs with solubility and dissolution limited absorption, respectively. In addition, GI-Sim was also shown to be able to predict the increase in absorption and plasma exposure achieved with nanoformulations. Based on the results, the performance of GI-Sim was shown to be suitable for early risk assessment as well as to guide decision making in pharmaceutical formulation development.

Predicting intestinal precipitation--a case example for a basic BCS class II drug.

PURPOSE: To investigate the prediction accuracy of in vitro and in vitro/in silico methods for in vivo intestinal precipitation of basic BCS class II drugs in humans. METHODS: Precipitation rate of a model drug substance, AZD0865 (pKa = 6.1; log K(D) = 4.2), was investigated in vitro using simulated intestinal media, and calculations of the crystallization rates were made with a theoretical model. Human intestinal precipitation was estimated by analysis of pharmacokinetic data from clinical studies at different doses. RESULTS: All in vitro models predicted rapid drug precipitation, where the intestinal concentration of dissolved AZD0865 at the highest dose tested was expected to decrease to half after less than 20 min. However, there was no indication of precipitation in vivo in humans as there was a dose proportional increase in drug plasma exposure. The theoretical model predicted no significant precipitation within the range of expected in vivo intestinal concentrations. CONCLUSIONS: This study indicated that simple in vitro methods of in vivo precipitation of orally administered bases overpredict the intestinal crystalline precipitation in vivo in humans. Hydrodynamic conditions were identified as one important factor that needs to be better addressed in future in vivo predictive methods.

The effects of food on the dissolution of poorly soluble drugs in human and in model small intestinal fluids.

PURPOSE: This study was conducted to determine the effect of food on drug solubility and dissolution rate in simulated and real human intestinal fluids (HIF). METHODS: Dissolution rate obtained via the rotating disk method and saturation solubility studies were carried out in fed and fasted state HIF, fed dog (DIF), and simulated (FeSSIF) intestinal fluid for six aprotic low solubility drugs. The intestinal fluids were characterized with respect to physical-chemical characteristics and contents. RESULTS: Fed HIF provided a 3.5- to 30-times higher solubility compared to fasted HIF and FeSSIF, whereas fed DIF corresponded well (difference of less than 30%) to fed HIF. The increased solubility of food could mainly be attributed to dietary lipids and bile acids. The dissolution rate was also 2 to 7 times higher in fed HIF than fasted HIF. This was well predicted by both DIF and FeSSIF (difference of less than 30%). CONCLUSIONS: Intestinal solubility is higher in fed state compared to fasted state. However, the dissolution rate does not increase to the same extent. Dog seems to be a good model for man with respect to dissolution in the small intestine after intake of a meal, whereas FeSSIF is a poorer means of determining intestinal saturation solubility in the fed state.