Assessing Dose-Exposure-Response Relationships of Miltefosine in Adults and Children using Physiologically-Based Pharmacokinetic Modeling Approach.

OBJECTIVES: Miltefosine is the first and only oral medication to be successfully utilized as an antileishmanial agent. However, the drug is associated with differences in exposure patterns and cure rates among different population groups e.g. ethnicity and age (i.e., children v adults) in clinical trials. In this work, mechanistic population physiologically-based pharmacokinetic (PBPK) models have been developed to study the dose-exposure-response relationship of miltefosine in in silico clinical trials and evaluate the differences in population groups, particularly children and adults. METHODS: The Simcyp population pharmacokinetics platform was employed to predict miltefosine exposure in plasma and peripheral blood mononuclear cells (PBMCs) in a virtual population under different dosing regimens. The cure rate of a simulation was based on the percentage of number of the individual virtual subjects with AUCd0-28 > 535 µg⋅day/mL in the virtual population. RESULTS: It is shown that both adult and paediatric PBPK models of miltefosine can be developed to predict the PK data of the clinical trials accurately. There was no significant difference in the predicted dose-exposure-response of the miltefosine treatment for different simulated ethnicities under the same dose regime and the dose-selection strategies determined the clinical outcome of the miltefosine treatment. A lower cure rate of the miltefosine treatment in paediatrics was predicted because a lower exposure of miltefosine was simulated in virtual paediatric in comparison with adult virtual populations when they received the same dose of the treatment. CONCLUSIONS: The mechanistic PBPK model suggested that the higher fraction of unbound miltefosine in plasma was responsible for a higher probability of failure in paediatrics because of the difference in the distribution of plasma proteins between adults and paediatrics. The developed PBPK models could be used to determine an optimal miltefosine dose regime in future clinical trials.

Non-specific binding of compounds in in vitro metabolism assays: a comparison of microsomal and hepatocyte binding in different species and an assessment of the accuracy of prediction models.

Non-specific binding in in vitro metabolism systems leads to an underestimation of the true intrinsic metabolic clearance of compounds being studied. Therefore in vitro binding needs to be accounted for when extrapolating in vitro data to predict the in vivo metabolic clearance of a compound. While techniques exist for experimentally determining the fraction of a compound unbound in in vitro metabolism systems, early in drug discovery programmes computational approaches are often used to estimate the binding in the in vitro system.Experimental fraction unbound data (n = 60) were generated in liver microsomes (fumic) from five commonly used pre-clinical species (rat, mouse, dog, minipig, monkey) and humans. Unbound fraction in incubations with mouse, rat or human hepatocytes was determined for the same 60 compounds. These data were analysed to determine the relationship between experimentally determined binding in the different matrices and across different species. In hepatocytes there was a good correlation between fraction unbound in human and rat (r2=0.86) or mouse (r2=0.82) hepatocytes. Similar correlations were observed between binding in human liver microsomes and microsomes from rat, mouse, dog, Göttingen minipig or monkey liver microsomes (r2 of >0.89, n = 51 - 52 measurements in different species). Physicochemical parameters (logP, pKa and logD) were predicted for all evaluated compounds. In addition, logP and/or logD were measured for a subset of compounds.Binding to human hepatocytes predicted using 5 different methods was compared to the measured data for a set of 59 compounds. The best methods evaluated used measured microsomal binding in human liver microsomes to predict hepatocyte binding. The collated physicochemical data were used to predict the human fumic using four different in silico models for a set of 53-60 compounds. The correlation (r2) and root mean square error between predicted and observed microsomal binding was 0.69 & 0.20, 0.47 & 0.23, 0.56 & 0.21 and 0.54 & 0.26 for the Turner-Simcyp, Austin, Hallifax-Houston and Poulin models, respectively. These analyses were extended to include measured literature values for binding in human liver microsomes for a larger set of compounds (n=697). For the larger dataset of compounds, microsomal binding was well predicted for neutral compounds (r2=0.67 - 0.70) using the Poulin, Austin, or Turner-Simcyp methods but not for acidic or basic compounds (r2<0.5) using any of the models. While the lipophilicity-based models can be used, the in vitro binding should be measured for compounds where more certainty is needed, using appropriately calibrated assays and possibly established weak, moderate, and strong binders as reference compounds to allow comparison across databases.

Artemisinin Cocrystals for Bioavailability Enhancement. Part 2: In Vivo Bioavailability and Physiologically Based Pharmacokinetic Modeling.

We report the evaluation and prediction of the pharmacokinetic (PK) performance of artemisinin (ART) cocrystal formulations, that is, 1:1 artemisinin/orcinol (ART-ORC) and 2:1 artemisinin/resorcinol (ART2-RES), using in vivo murine animal and physiologically based pharmacokinetic (PBPK) models. The efficacy of the ART cocrystal formulations along with the parent drug ART was tested in mice infected with Plasmodium berghei. When given at the same dose, the ART cocrystal formulation showed a significant reduction in parasitaemia at day 4 after infection compared to ART alone. PK parameters including Cmax (maximum plasma concentration), Tmax (time to Cmax), and AUC (area under the curve) were obtained by determining drug concentrations in the plasma using liquid chromatography-high-resolution mass spectrometry (LC-HRMS), showing enhanced ART levels after dosage with the cocrystal formulations. The dose-response tests revealed that a significantly lower dose of the ART cocrystals in the formulation was required to achieve a similar therapeutic effect as ART alone. A PBPK model was developed using a PBPK mouse simulator to accurately predict the in vivo behavior of the cocrystal formulations by combining in vitro dissolution profiles with the properties of the parent drug ART. The study illustrated that information from classical in vitro and in vivo experimental investigations of the parent drug of ART formulations can be coupled with PBPK modeling to predict the PK parameters of an ART cocrystal formulation in an efficient manner. Therefore, the proposed modeling strategy could be used to establish in vitro and in vivo correlations for different cocrystals intended to improve dissolution properties and to support clinical candidate selection, contributing to the assessment of cocrystal developability and formulation development.

Population-Based PBPK Model for the Prediction of Time-Variant Bile Salt Disposition within GI Luminal Fluids.

In vivo studies have shown cyclic bile salt (BS) outputs during fasting whereas higher amounts have been observed in fed states. This leads to fluctuations of intestinal BS concentrations ([BS]) that can affect the rate and extent of absorption of lipophilic drugs in particular. However, most PBPK models use fixed values of [BS] in fasted and fed states albeit with different values in different regions of the GI tract. During fasting, there is a relationship between gallbladder volume (GBV) and the phase of the Interdigestive Migrating Motor Complex cycle (IMMCc), showing cyclic GBV changes with periodic filling and emptying. This relationship is also affected by the origin of the IMMCc (antral or duodenal). In fed states, meta-analysis indicated that GB residual volume (% of fasting maximum) was 46.4 ± 27%CV and 30.7 ± 48%CV for low- and high-fat meals, respectively. The corresponding values for the duration of the emptying phase were for low fat meals 0.72h ± 1%CV and for high fat meals 1.17h ± 37%CV. The model, the Advanced Dynamic Bile Salt Model (ADBSM), was built bottom-up and its parameters were not fitted against in vivo measurements of [BS]. It involved update of the dynamic luminal fluid volumes model based on meta-analysis of available imaging data. The ADBSM is incorporated into the Simcyp (v18r2) PBPK simulator. The model predictivity was good (within 1.25-fold error for 11/20 of the clinical studies) and was assessed against clinical studies of luminal [BS] that provide only the type of meal (i.e., low- or high-fat), the timing of the meal and/or water intake events, and the number and age range of the study participants. The model is also an important component of models capturing enterohepatic recirculation of drug and metabolite. Further work is required to validate the current model and compare to simpler models with respect to drug absorption, especially of the lipophilic compounds.

Biopharmaceutic In Vitro In Vivo Extrapolation (IVIV_E) Informed Physiologically-Based Pharmacokinetic Model of Ritonavir Norvir Tablet Absorption in Humans Under Fasted and Fed State Conditions.

Ritonavir is a well-known CYP3A4 and CYP2D6 enzyme inhibitor, frequently used to assess the drug-drug interaction (DDI) liability of susceptible drugs. It is also used as a pharmacokinetic booster to increase exposure to CYP3A4 substrates. This study aimed to develop a mechanistic absorption and disposition model to describe exposure to ritonavir following oral dosing of the commercial amorphous solid dispersion tablet, Norvir, under fasted and fed conditions. A mechanistic description of ritonavir absorption from Norvir tablets may help to improve the design of DDI studies. Key parameters of amorphous ritonavir including free base solubility (solubility of the unbound, un-ionized species), bile micelle partition coefficients, formulation wetting/disintegration, and in vivo precipitation parameters were either obtained from the literature or estimated by modeling in vitro biopharmaceutic experiments. Based on variety of in vitro evidence, a main assumption of the model is that ritonavir does not form a crystalline precipitate while resident in the gastrointestinal tract. In the model, if simulated luminal concentration exceeds the amorphous solubility limit, then precipitation to an amorphous form is immediate. Simulated and observed Cmax and AUC0-t parameters were well captured (within 1.5-fold) for both fasted and fed states in healthy volunteers. By accounting for luminal fluid viscosity differences in the different prandial states (affecting drug diffusivity) as well as the effect of drug free fraction on gut wall permeation rates, it was possible to explain the negative food effect observed for Norvir tablets in humans. In summary, a biopharmaceutic in vitro in vivo extrapolation approach provides confidence in (verification of) key input parameters of the physiologically-based pharmacokinetic ritonavir model which resulted in successful simulation of observed plasma profiles.

Model-Based Analysis of Biopharmaceutic Experiments To Improve Mechanistic Oral Absorption Modeling: An Integrated in Vitro in Vivo Extrapolation Perspective Using Ketoconazole as a Model Drug.

Mechanistic modeling of in vitro data generated from metabolic enzyme systems (viz., liver microsomes, hepatocytes, rCYP enzymes, etc.) facilitates in vitro-in vivo extrapolation (IVIV_E) of metabolic clearance which plays a key role in the successful prediction of clearance in vivo within physiologically-based pharmacokinetic (PBPK) modeling. A similar concept can be applied to solubility and dissolution experiments whereby mechanistic modeling can be used to estimate intrinsic parameters required for mechanistic oral absorption simulation in vivo. However, this approach has not widely been applied within an integrated workflow. We present a stepwise modeling approach where relevant biopharmaceutics parameters for ketoconazole (KTZ) are determined and/or confirmed from the modeling of in vitro experiments before being directly used within a PBPK model. Modeling was applied to various in vitro experiments, namely: (a) aqueous solubility profiles to determine intrinsic solubility, salt limiting solubility factors and to verify pKa; (b) biorelevant solubility measurements to estimate bile-micelle partition coefficients; (c) fasted state simulated gastric fluid (FaSSGF) dissolution for formulation disintegration profiling; and (d) transfer experiments to estimate supersaturation and precipitation parameters. These parameters were then used within a PBPK model to predict the dissolved and total (i.e., including the precipitated fraction) concentrations of KTZ in the duodenum of a virtual population and compared against observed clinical data. The developed model well characterized the intraluminal dissolution, supersaturation, and precipitation behavior of KTZ. The mean simulated AUC0-t of the total and dissolved concentrations of KTZ were comparable to (within 2-fold of) the corresponding observed profile. Moreover, the developed PBPK model of KTZ successfully described the impact of supersaturation and precipitation on the systemic plasma concentration profiles of KTZ for 200, 300, and 400 mg doses. These results demonstrate that IVIV_E applied to biopharmaceutical experiments can be used to understand and build confidence in the quality of the input parameters and mechanistic models used for mechanistic oral absorption simulations in vivo, thereby improving the prediction performance of PBPK models. Moreover, this approach can inform the selection and design of in vitro experiments, potentially eliminating redundant experiments and thus helping to reduce the cost and time of drug product development.

In Silico Modeling Approach for the Evaluation of Gastrointestinal Dissolution, Supersaturation, and Precipitation of Posaconazole.

The aim of this study was to evaluate gastrointestinal (GI) dissolution, supersaturation, and precipitation of posaconazole, formulated as an acidified (pH 1.6) and neutral (pH 7.1) suspension. A physiologically based pharmacokinetic (PBPK) modeling and simulation tool was applied to simulate GI and systemic concentration-time profiles of posaconazole, which were directly compared with intraluminal and systemic data measured in humans. The Advanced Dissolution Absorption and Metabolism (ADAM) model of the Simcyp Simulator correctly simulated incomplete gastric dissolution and saturated duodenal concentrations of posaconazole in the duodenal fluids following administration of the neutral suspension. In contrast, gastric dissolution was approximately 2-fold higher after administration of the acidified suspension, which resulted in supersaturated concentrations of posaconazole upon transfer to the upper small intestine. The precipitation kinetics of posaconazole were described by two precipitation rate constants, extracted by semimechanistic modeling of a two-stage medium change in vitro dissolution test. The 2-fold difference in exposure in the duodenal compartment for the two formulations corresponded with a 2-fold difference in systemic exposure. This study demonstrated for the first time predictive in silico simulations of GI dissolution, supersaturation, and precipitation for a weakly basic compound in part informed by modeling of in vitro dissolution experiments and validated via clinical measurements in both GI fluids and plasma. Sensitivity analysis with the PBPK model indicated that the critical supersaturation ratio (CSR) and second precipitation rate constant (sPRC) are important parameters of the model. Due to the limitations of the two-stage medium change experiment the CSR was extracted directly from the clinical data. However, in vitro experiments with the BioGIT transfer system performed after completion of the in silico modeling provided an almost identical CSR to the clinical study value; this had no significant impact on the PBPK model predictions.

Optically Transparent Lead Halide Perovskite Polycrystalline Ceramics.

We utilize room-temperature uniaxial pressing at applied loads achievable with low-cost, laboratory-scale presses to fabricate freestanding CH3NH3PbX3 (X- = Br-, Cl-) polycrystalline ceramics with millimeter thicknesses and optical transparency up to ∼70% in the infrared. As-fabricated perovskite ceramics can be produced with desirable form factors (i.e., size, shape, and thickness) and high-quality surfaces without any postprocessing (e.g., cutting or polishing). This method should be broadly applicable to a large swath of metal halide perovskites, not just the compositions shown here. In addition to fabrication, we analyze microstructure-optical property relationships through detailed experiments (e.g., transmission measurements, electron microscopy, X-ray tomography, optical profilometry, etc.) as well as modeling based on Mie theory. The optical, electrical, and mechanical properties of perovskite polycrystalline ceramics are benchmarked against those of single-crystalline analogues through spectroscopic ellipsometry, Hall measurements, and nanoindentation. Finally, γ-ray scintillation from a transparent MAPbBr3 ceramic is demonstrated under irradiation from a 137Cs source. From a broader perspective, scalable methods to produce freestanding polycrystalline lead halide perovskites with comparable properties to their single-crystal counterparts could enable key advancements in the commercial production of perovskite-based technologies (e.g., direct X-ray/γ-ray detectors, scintillators, and nonlinear optics).

Physiologically Based Biopharmaceutics Model (PBBM) of Minimally Absorbed Locally Acting Drugs in the Gastrointestinal Tract-Case Study: Tenapanor.

A physiologically based biopharmaceutics model (PBBM) was developed to predict stool and urine sodium content in response to tenapanor administration in healthy subjects. Tenapanor is a minimally absorbed small molecule that inhibits the sodium/hydrogen isoform 3 exchanger (NHE3). It is used to treat irritable bowel syndrome with constipation (IBS-C). Its mode of action in the gastrointestinal tract reduces the uptake of sodium, resulting in an increase in water secretion in the intestinal lumen and accelerating intestinal transit time. The strategy employed was to perform drug-drug interaction (DDI) modelling between sodium and tenapanor, with sodium as the "victim" administered as part of daily food intake and tenapanor as the "perpetrator" altering sodium absorption. Food effect was modelled, including meal-induced NHE3 activity using sodium as an inducer by normalising the induction kinetics of butyrate to sodium equivalents. The presented model successfully predicted both urine and stool sodium content in response to tenapanor dosed in healthy subjects (within 1.25-fold error) and provided insight into the clinical observations of tenapanor dosing time relative to meal ingestion. The PBBM model was applied retrospectively to assess the impact of different forms of tenapanor (free base vs. HCl salt) on its pharmacodynamic (PD) effect. The developed modelling strategy can be effectively adopted to increase confidence in using PBBM models for the prediction of the in vivo behaviour of minimally absorbed, locally acting drugs in the gastrointestinal tract, when other approaches (e.g., biomarkers or PD data) are not available.

Physiologically based pharmacokinetic modeling for development and applications of a virtual celiac disease population using felodipine as a model drug.

In celiac disease (CeD), gastrointestinal CYP3A4 abundance and morphology is affected by the severity of disease. Therefore, exposure to CYP3A4 substrates and extent of drug interactions is altered. A physiologically-based pharmacokinetic (PBPK) population for different severities of CeD was developed. Gastrointestinal physiology parameters, such as luminal pH, transit times, morphology, P-gp, and CYP3A4 expression were included in development of the CeD population. Data on physiological difference between healthy and CeD subjects were incorporated into the model as the ratio of celiac to healthy. A PBPK model was developed and verified for felodipine extended-release tablet in healthy volunteers (HVs) and then utilized to verify the CeD populations. Plasma concentration-time profile and PK parameters were predicted and compared against those observed in both groups. Sensitivity analysis was carried out on key system parameters in CeD to understand their impact on drug exposure. For felodipine, the predicted mean concentration-time profiles and 5th and 95th percentile intervals captured the observed profile and variability in the HV and CeD populations. Predicted and observed clearance was 56.9 versus 56.1 (L/h) in HVs. Predicted versus observed mean ± SD area under the curve for extended release felodipine in different severities of CeD were values of 14.5 ± 9.6 versus 14.4 ± 2.1, 14.6 ± 9.0 versus 17.2 ± 2.8, and 28.1 ± 13.5 versus 25.7 ± 5.0 (ng.h/mL), respectively. Accounting for physiology differences in a CeD population accurately predicted the PK of felodipine. The developed CeD population can be applied for determining the drug concentration of CYP3A substrates in the gut as well as for systemic levels, and for application in drug-drug interaction studies.

Leveraging the use of in vitro and computational methods to support the development of enabling oral drug products: An InPharma commentary.

Due to the strong tendency towards poorly soluble drugs in modern development pipelines, enabling drug formulations such as amorphous solid dispersions, cyclodextrins, co-crystals and lipid-based formulations are frequently applied to solubilize or generate supersaturation in gastrointestinal fluids, thus enhancing oral drug absorption. Although many innovative in vitro and in silico tools have been introduced in recent years to aid development of enabling formulations, significant knowledge gaps still exist with respect to how best to implement them. As a result, the development strategy for enabling formulations varies considerably within the industry and many elements of empiricism remain. The InPharma network aims to advance a mechanistic, animal-free approach to the assessment of drug developability. This commentary focuses current status and next steps that will be taken in InPharma to identify and fully utilize 'best practice' in vitro and in silico tools for use in physiologically based biopharmaceutic models.

A Mechanistic Absorption and Disposition Model of Ritonavir to Predict Exposure and Drug-Drug Interaction Potential of CYP3A4/5 and CYP2D6 Substrates.

BACKGROUND AND OBJECTIVES: Due to health authority warnings and the recommended limited use of ketoconazole as a model inhibitor of cytochrome P450 (CYP) 3A4 in clinical drug-drug interaction (DDI) studies, there is a need to search for alternatives. Ritonavir is a strong inhibitor for CYP3A4/5-mediated DDIs and has been proposed as a suitable alternative to ketoconazole. It can also be used as a weak inhibitor for CYP2D6-mediated DDIs. Most of the currently available physiologically based pharmacokinetic (PBPK) inhibitor models developed for predicting DDIs use first-order absorption models, which do not mechanistically capture the effect of formulations on the systemic exposure of the inhibitor. Thus, the main purpose of the current study was to verify the predictive performance of a mechanistic absorption and disposition model of ritonavir when it was applied to the inhibition of CYP2D6 and CYP3A4/5 by ritonavir. METHODS: A PBPK model that incorporates formulation characteristics and enzyme kinetic parameters for post-absorptive pharmacokinetic processes of ritonavir was constructed. Key absorption-related parameters in the model were determined using mechanistic modelling of in vitro biopharmaceutics experiments. The model was verified for systemic exposure and DDI risk assessment using clinical observations from 13 and 18 studies, respectively. RESULTS: Maximal inhibition of hepatic (3.53% of the activity remaining) and gut (5.16% of the activity remaining) CYP3A4 activity was observed when ritonavir was orally administered in doses of 100 mg or higher. The PBPK model accurately described the concentrations of ritonavir in the different simulated studies. The prediction accuracy for maximum concentration (Cmax) and area under the plasma concentration versus time curve (AUC) were assessed. The bias (average fold error, AFE) for the prediction of Cmax and AUC was 0.92 and 1.06, respectively, and the precision (absolute average fold error, AAFE) was 1.29 and 1.23, respectively. The PBPK model predictions for all Cmax and AUC ratios when ritonavir was used as an inhibitor of CYP metabolism fell within twofold of the clinical observations. The prediction accuracy for Cmax and AUC ratios had a bias (AFE) of 0.85 and 0.99, respectively, and a precision (AAFE) of 1.21 and 1.33, respectively. CONCLUSIONS: The current model, which incorporates formulation characteristics and mechanistic disposition parameters, can be used to assess the DDI potential of CYP3A4/5 and CYP2D6 substrates administered with a twice-daily dose of 100 mg of ritonavir for 14 days.

Developing Clinically Relevant Dissolution Specifications (CRDSs) for Oral Drug Products: Virtual Webinar Series.

A webinar series that was organised by the Academy of Pharmaceutical Sciences Biopharmaceutics focus group in 2021 focused on the challenges of developing clinically relevant dissolution specifications (CRDSs) for oral drug products. Industrial scientists, together with regulatory and academic scientists, came together through a series of six webinars, to discuss progress in the field, emerging trends, and areas for continued collaboration and harmonisation. Each webinar also hosted a Q&A session where participants could discuss the shared topic and information. Although it was clear from the presentations and Q&A sessions that we continue to make progress in the field of CRDSs and the utility/success of PBBM, there is also a need to continue the momentum and dialogue between the industry and regulators. Five key areas were identified which require further discussion and harmonisation.

Mechanistic PBPK Modelling to Predict the Advantage of the Salt Form of a Drug When Dosed with Acid Reducing Agents.

Acid reducing agents (ARAs) reduce the dissolution rate of weakly basic drugs in the stomach potentially leading to lower bioavailability. Formulating the API as a rapidly dissolving salt is one strategy employed to reduce the impact of ARAs on dissolution of such drugs. In the present work, a model drug was selected with an immediate release formulation of the free base dosed in both the absence and presence of the ARA famotidine. In the latter case, bioavailability is restricted and several salt formulations were investigated. To simulate these drug products a mechanistic physiologically based pharmacokinetic (PBPK) model was built using the Simcyp Simulator, which illustrates the advantage of formulating an API as a salt compared to the free base form. The simulations use a mechanistic salt model utilising knowledge of the solubility product which was applied to predict the salt advantage. The developed PBPK model exemplifies that it can be critical to account for the surface pH and solubility when modelling the dissolution of low pKa bases and their salts in the gastric environment. In particular, the mechanistic salt model can be used to aid in screening and salt form selection where the aim is to mitigate effects of ARAs.

Evaluating the impact of acid-reducing agents on drug absorption using biorelevant in vitro tools and PBPK modeling - case example dipyridamole.

BACKGROUND: In vitro and in silico methods have become an essential tool in assessing metabolic drug-drug interactions (DDI) and avoiding reduced efficacy and increased side-effects. Another important type of DDI is the impact of acid-reducing agent (ARA) co-therapy on drug pharmacokinetics due to changes in gastric pH, especially for poorly soluble weakly basic drugs. METHODS: One-stage, two-stage and transfer dissolution experiments with dipyridamole tablets using novel biorelevant media representing the ARA effect were conducted and the results were coupled with a PBPK model. Clinical pharmacokinetic data were compared with the simulations from the PBPK model and with output from TIM-1 experiments, an evolved in vitro system which aims to simulate the physiology in the upper GI tract. RESULTS: Two-stage and transfer experiments confirmed that these in vitro set-ups tend to overestimate the extent of dipyridamole precipitation occurring in the intestines in vivo. Consequently, data from one-stage dissolution testing under elevated gastric pH conditions were used as an input for PBPK modeling of the ARA/dipyridamole interaction. Using media representing the ARA effect in conjunction with the PBPK model, the ARA effect observed in vivo was successfully bracketed. As an alternative, the TIM-1 system with gastric pH values adjusted to simulate ARA pre-treatment can be used to forecast the ARA effect on dipyridamole pharmacokinetics. CONCLUSION: Drug-drug interactions of dipyridamole with ARA were simulated well with a combination of dissolution experiments using biorelevant media representing the gastric environment after an ARA treatment together with the PBPK model. Adjustment of the TIM-1 model to reflect ARA-related changes in gastric pH was also successful in forecasting the interaction. Further testing of both approaches for predicting ARA-related DDIs using a wider range of drugs should be conducted to verify their utility for this purpose.

Establishing virtual bioequivalence and clinically relevant specifications using in vitro biorelevant dissolution testing and physiologically-based population pharmacokinetic modeling. case example: Naproxen.

BACKGROUND: Physiologically-based population pharmacokinetic modeling (popPBPK) coupled with in vitro biopharmaceutics tools such as biorelevant dissolution testing can serve as a powerful tool to establish virtual bioequivalence and set clinically relevant specifications. One of several applications of popPBPK modeling is in the emerging field of virtual bioequivalence (VBE), where it can be used to streamline drug development by implementing model-informed formulation design and to inform regulatory decision-making e.g., with respect to evaluating the possibility of extending BCS-based biowaivers beyond BCS Class I and III compounds in certain cases. METHODS: In this study, Naproxen, a BCS class II weak acid was chosen as the model compound. In vitro biorelevant solubility and dissolution experiments were performed and the resulting data were used as an input to the PBPK model, following a stepwise workflow for the confirmation of the biopharmaceutical parameters. The naproxen PBPK model was developed by implementing a middle-out approach and verified against clinical data obtained from the literature. Once confidence in the performance of the model was achieved, several in vivo dissolution scenarios, based on model-based analysis of the in vitro data, were used to simulate clinical trials in healthy adults. Inter-occasion variability (IOV) was also added to critical physiological parameters and mechanistically propagated through the simulations. The various trials were simulated on a "worst/best case" dissolution scenario and average bioequivalence was assessed according to Cmax, AUC and Tmax. RESULTS: VBE results demonstrated that naproxen products with in vitro dissolution reaching 85% dissolved within 90 min would lie comfortably within the bioequivalence limits for Cmax and AUC. Based on the establishment of VBE, a dissolution "safe space" was designed and a clinically relevant specification for naproxen products was proposed. The interplay between formulation-related and drug-specific PK parameters (e.g., t1/2) to predict the in vivo performance was also investigated. CONCLUSION: Over a wide range of values, the in vitro dissolution rate is not critical for the clinical performance of naproxen products and therefore naproxen could be eligible for BCS-based biowaivers based on in vitro dissolution under intestinal conditions. This approach may also be applicable to other poorly soluble acidic compounds with long half-lives, providing an opportunity to streamline drug development and regulatory decision-making without putting the patient at a risk.

Combining biorelevant in vitro and in silico tools to investigate the in vivo performance of the amorphous solid dispersion formulation of etravirine in the fed state.

INTRODUCTION: In the development of bio-enabling formulations, innovative in vivo predictive tools to understand and predict the in vivo performance of such formulations are needed. Etravirine, a non-nucleoside reverse transcriptase inhibitor, is currently marketed as an amorphous solid dispersion (Intelence® tablets). The aims of this study were 1) to investigate and discuss the advantages of using biorelevant in vitro setups to simulate the in vivo performance of Intelence® 100 mg and 200 mg tablets in the fed state, 2) to build a Physiologically Based Pharmacokinetic (PBPK) model by combining experimental data and literature information with the commercially available in silico software Simcyp® Simulator V17.1 (Certara UK Ltd.), and 3) to discuss the challenges of predicting the in vivo performance of an amorphous solid dispersion and identify the parameters which influence the pharmacokinetics of etravirine most. METHODS: Solubility, dissolution and transfer experiments were performed in various biorelevant media simulating the fasted and fed state environment in the gastrointestinal tract. An in silico PBPK model for etravirine in healthy volunteers was developed in the Simcyp® Simulator, using in vitro results and data available from the literature as input. The impact of pre- and post-absorptive parameters on the pharmacokinetics of etravirine was investigated by simulating various scenarios. RESULTS: In vitro experiments indicated a large effect of naturally occurring solubilizing agents on the solubility of etravirine. Interestingly, supersaturated concentrations of etravirine were observed over the entire duration of dissolution experiments on Intelence® tablets. Coupling the in vitro results with the PBPK model provided the opportunity to investigate two possible absorption scenarios, i.e. with or without implementation of precipitation. The results from the simulations suggested that a scenario in which etravirine does not precipitate is more representative of the in vivo data. On the post-absorptive side, it appears that the concentration dependency of the unbound fraction of etravirine in plasma has a significant effect on etravirine pharmacokinetics. CONCLUSIONS: The present study underlines the importance of combining in vitro and in silico biopharmaceutical tools to advance our knowledge in the field of bio-enabling formulations. Future studies on other bio-enabling formulations can be used to further explore this approach to support rational formulation design as well as robust prediction of clinical outcomes.

Current status and future opportunities for incorporation of dissolution data in PBPK modeling for pharmaceutical development and regulatory applications: OrBiTo consortium commentary.

In vitro dissolution experiments are used to qualitatively assess the impact of formulation composition and process changes on the drug dosage form performance. However, the use of dissolution data to quantitatively predict changes in the absorption profile remains limited. Physiologically-based Pharmacokinetic(s) (PBPK) models facilitate incorporation of in vitro dissolution experiments into mechanistic oral absorption models to predict in vivo oral formulation performance, and verify if the drug product dissolution method is biopredictive or clinically relevant. Nevertheless, a standardized approach for using dissolution data within PBPK models does not yet exist and the introduction of dissolution data in PBPK relies on a case by case approach which accommodates from differences in release mechanism and limitations to drug absorption. As part of the Innovative Medicines Initiative (IMI) Oral Biopharmaceutics Tools (OrBiTo) project a cross-work package was set up to gather a realistic understanding of various approaches used and their areas of applications. This paper presents the approaches shared by academic and industrial scientists through the OrBiTo project to integrate dissolution data within PBPK software to improve the prediction accuracy of oral formulations in vivo. Some general recommendations regarding current use and future improvements are also provided.

Ultrafast ligand exchange: detection of a pentacoordinate Ru(II) intermediate and product formation.

The ultrafast kinetics of ligand exchange of cis-[Ru(bpy)(2)(CH(3)CN)(2)](2+) were measured in H(2)O and CH(3)CN. The formation of the (3)MLCT excited-state and a five-coordinate intermediate are observed in both solvents within 2 ps after excitation (310 nm, fwhm approximately 300 fs). The (3)MLCT excited-state undergoes vibrational cooling (5-6 ps), then decays to regenerate the ground-state with a lifetime of approximately 50 ps. In CH(3)CN, ligand recombination takes place in 28 ps, while the formation of cis-[Ru(bpy)(2)(CH(3)CN)(H(2)O)](2+) in H(2)O takes place with tau = 77 ps.