Physiologically Based Absorption Modeling to Impact Biopharmaceutics and Formulation Strategies in Drug Development—Industry Case Studies

Oral Absorption from Surfactant-Based Drug Formulations: The Impact of Molecularly Dissolved Drug on Bioavailability

Enabling drug formulations are often required to ensure sufficient absorption after oral administration of poorly soluble drugs. While these formulations typically increase the apparent solubility of the drug, it is widely acknowledged that only molecularly dissolved, i.e., free fraction of the drug, is prone for direct absorption, while colloid-associated drug does not permeate to the same extent. In the present study, we aimed at comparing the effect of molecularly and apparently (i.e., the sum of molecularly and colloid-associated drug) dissolved drug concentrations on the oral absorption of a poorly water-soluble drug compound, Alectinib. Mixtures of Alectinib and respectively 50 %, 25 %, 12.5 %, and 3 % sodium lauryl sulfate (SLS) relative to the dose were prepared and small-scale dissolution tests were performed under simulated fed and fasted state conditions. Both the molecularly and apparently dissolved drug concentrations were assessed in parallel using microdialysis and centrifugation/filtration sampling, respectively. The data served as the basis for an in vitro-in vivo correlation (IVIVC) and as input for a GastroPlusTM physiologically-based biopharmaceutics model (PBBM). It was shown that with increasing the content of SLS the apparently dissolved drug in FeSSIF and FaSSIF increased to a linear extent and thus, the predicted in vivo performance of the 50 % SLS formulation, based on apparently dissolved drug, would outperform all other formulations. Against common expectation, however, the free (molecularly dissolved) drug concentrations were found to vary with SLS concentrations as well, yet to a minor extent. A systematic comparison of solubilized and free drug dissolution patterns at different SLS contents of the formulations and prandial states allowed for interesting insights into the complex dissolution-/supersaturation-, micellization-, and precipitation-behavior of the formulations. When comparing the in vitro datasets with human pharmacokinetic data from a bioequivalence study, it was shown that the use of molecularly dissolved drug resulted in an improved IVIVC. By incorporating the in vitro dissolution datasets into the GastroPlusTM PBBM, the apparently dissolved drug concentrations resulted in both, a remarkable overprediction of plasma concentrations as well as a misprediction of the influence of SLS on systemic exposure. In contrast, by using the molecularly dissolved drug (i.e., free fraction) as the model input, the predicted plasma concentration-time profiles were in excellent agreement with observed data for all formulations under both fed and fasted conditions. By combining an advanced in vitro assessment with PBBM, the present study confirmed that only the molecularly dissolved drug, and not the colloid-associated drug, is available for direct absorption.

Using molecularly dissolved drug concentrations in PBBMs improves the prediction of oral absorption from supersaturating formulations

Predicting the absorption of drugs from enabling formulations is still challenging due to the limited capabilities of standard physiologically based biopharmaceutics models (PBBMs) to capture complex absorption processes. Amongst others, it is often assumed that both, molecularly and apparently dissolved drug in the gastrointestinal lumen are prone to absorption. A recently introduced method for measuring concentrations of molecularly dissolved drug in a dynamic in vitro dissolution setup using microdialysis has opened new opportunities to test this hypothesis and refine mechanistic PBBM approaches. In the present study, we compared results of PBBMs that used either molecularly or apparently dissolved concentrations in the simulated gastrointestinal lumen as input parameters. The in vitro dissolution data from three supersaturating formulations of Posaconazole (PCZ) were used as model input. The modeling outcome was verified using PCZ concentration vs. time profiles measured in human intestinal aspirates and in the blood plasma. When using apparently dissolved drug concentrations (i.e., the sum of colloid-associated and molecularly dissolved drug) the simulated systemic plasma exposures were overpredicted, most pronouncedly with the ASD-based tablet. However, if the concentrations of molecularly dissolved drug were used as input values, the PBBM resulted in accurate prediction of systemic exposures for all three PCZ formulations. The present study impressively demonstrated the value of considering molecularly dissolved drug concentrations as input value for PBBMs of supersaturating drug formulations.

Refining mutanome-based individualised immunotherapy of melanoma using artificial intelligence

Using the particular nature of melanoma mutanomes to develop medicines that activate the immune system against specific mutations is a game changer in immunotherapy individualisation. It offers a viable solution to the recent rise in resistance to accessible immunotherapy alternatives, with some patients demonstrating innate resistance to these drugs despite past sensitisation to these agents. However, various obstacles stand in the way of this method, most notably the practicality of sequencing each patient's mutanome, selecting immunotherapy targets, and manufacturing specific medications on a large scale. With the robustness and advancement in research techniques, artificial intelligence (AI) is a potential tool that can help refine the mutanome-based immunotherapy for melanoma. Mutanome-based techniques are being employed in the development of immune-stimulating vaccines, improving current options such as adoptive cell treatment, and simplifying immunotherapy responses. Although the use of AI in these approaches is limited by data paucity, cost implications, flaws in AI inference capabilities, and the incapacity of AI to apply data to a broad population, its potential for improving immunotherapy is limitless. Thus, in-depth research on how AI might help the individualisation of immunotherapy utilising knowledge of mutanomes is critical, and this should be at the forefront of melanoma management.

Physiologically Based Biopharmaceutics Modeling of regional and colon absorption in humans

Colon absorption is a key determinant for successful development of extended release and colon targeted drug products. This is the first systematic evaluation of the ability to predict in vivo regional differences in absorption and the extent of colon absorption in humans using mechanistic physiologically based biopharmaceutics modeling (PBBM). A new dataset, consisting of 19 drugs with a wide range of biopharmaceutics properties and extent of colon absorption in humans, was established. Mechanistic predictions of the extent of absorption and plasma exposure after oral, or jejunal and direct colon administration were performed in GastroPlus and GI-Sim using an a priori approach. Two new colon models developed in GI-Sim, were also evaluated to assess if the prediction performance could be improved. Both GastroPlus and GI-Sim met the pre-defined criteria for accurate predictions of regional and colon absorption for high permeability drugs irrespective of formulation type, while the prediction performance was poor for low permeability drugs. For solutions, the two new GI-Sim colon models improved the colon absorption prediction performance for the low permeability drugs while maintaining the accurate prediction performance for the high permeability drugs. In contrast, the prediction performance decreased for non-solutions using the two new colon models. In conclusion, PBBM can be used with sufficient accuracy to predict regional and colon absorption in humans for high permeability drugs in candidate selection as well as early design and development of extended release or colon targeted drug products. The prediction performance of the current models needs to be improved to allow high accuracy predictions for commercial drug product applications including highly accurate predictions of the entire plasma concentration-time profiles as well as for low permeability drugs.

Current State and Challenges of Physiologically Based Biopharmaceutics Modeling (PBBM) in Oral Drug Product Development

Physiologically based biopharmaceutics modeling (PBBM) emphasizes the integration of physicochemical properties of drug substance and formulation characteristics with system physiological parameters to predict the absorption and pharmacokinetics (PK) of a drug product. PBBM has been successfully utilized in drug development from discovery to postapproval stages and covers a variety of applications. The use of PBBM facilitates drug development and can reduce the number of preclinical and clinical studies. In this review, we summarized the major applications of PBBM, which are classified into six categories: formulation selection and development, biopredictive dissolution method development, biopharmaceutics risk assessment, clinically relevant specification settings, food effect evaluation and pH-dependent drug-drug-interaction risk assessment. The current state of PBBM applications is illustrated with examples from published studies for each category of application. Despite the variety of PBBM applications, there are still many hurdles limiting the use of PBBM in drug development, that are associated with the complexity of gastrointestinal and human physiology, the knowledge gap between the in vitro and the in vivo behavior of drug products, the limitations of model interfaces, and the lack of agreed model validation criteria, among other issues. The challenges and essential considerations related to the use of PBBM are discussed in a question-based format along with the scientific thinking on future research directions. We hope this review can foster open discussions between the pharmaceutical industry and regulatory agencies and encourage collaborative research to fill the gaps, with the ultimate goal to maximize the applications of PBBM in oral drug product development.

Physiologically Based Biopharmaceutics Model for Selumetinib Food Effect Investigation and Capsule Dissolution Safe Space - Part I: Adults

OBJECTIVE

A physiologically based biopharmaceutics model (PBBM) was developed to mechanistically investigate the effect of formulation and food on selumetinib pharmacokinetics.

METHODS

Selumetinib is presented as a hydrogen sulfate salt, and in vitro and in vivo data were used to verify the precipitation rate to apply to simulations. Dissolution profiles observed for capsules and granules were used to derive product-particle size distributions for model input. The PBBM incorporated gut efflux and first-pass gut metabolism, based on intravenous and oral pharmacokinetic data, alongside in vitro data for the main enzyme isoform and P-glycoprotein efflux. The PBBM was validated across eight clinical scenarios.

RESULTS

The quality-control dissolution method for selumetinib capsules was found to be clinically relevant through PBBM validation. A safe space for capsule dissolution was established using a virtual batch. The effect of food (low fat vs high fat) on capsules and granules was elucidated by the PBBM. For capsules, a lower amount was dissolved in the fed state due to a pH increase in the stomach followed by higher precipitation in the small intestine. First-pass gut extraction is higher for capsules in the fed state due to drug dilution in the stomach chyme and reduced concentration in the lumen. The enteric-coated granules dissolve more slowly than capsules after stomach emptying, attenuating the difference in first-pass gut extraction between prandial states.

CONCLUSIONS

The PBBM was instrumental in understanding and explaining the different behaviors of the selumetinib formulations. The model can be used to predict the impact of food in humans.

Model-Informed drug development of gastroretentive release systems for sildenafil citrate

Gastroretentive drug delivery systems (GRDDS) are modified-release dosage forms designed to prolong their residence time in the upper gastrointestinal tract, where some drugs are preferentially absorbed, and increase the drug bioavailability. This work aimed the development of a novel GRDDS containing 60 mg of sildenafil citrate, and the evaluation of the feasibility of the proposed formulation for use in the treatment of pulmonary arterial hypertension (PAH), for once a day administration, by using in silico pharmacokinetic (PK) modeling and simulations using GastroPlus^TM. The Model-Informed Drug Development (MIDD) approach was used in formulation design and pharmacokinetic exposure prospecting. A 2² factorial design with a central point was used for optimization of the formulation, which was produced by direct compression and characterized by some tests, including buoyancy test, assay, impurities, and in vitro dissolution. A compartmental PK model was built using the GatroPlus^TM software for virtual bioequivalence of the proposed formulations in comparison with the defined target release profile provided by an immediate release (IR) tablet formulation containing 20 mg of sildenafil administered three times a day (TID). The results of the factorial design showed a direct correlation between the dissolution rate and the amount of hydroxypropyl methyl cellulose (HPMC) in the formulations. By comparing the PK parameters predicted by the virtual bioequivalence, the formulations F1, F2, F3 and F5 failed on bioequivalence. The F4 showed bioequivalence to the reference and was considered the viable formulation to substitute the IR. Thus, GRDDS could be a promising alternative for controlling the release of drugs with a pH-dependent solubility and narrow absorption window, specifically in the gastric environment, and an interesting way to reduce dose frequency and increase the drug bioavailability. The MIDD approach increases the level of information about the pharmaceutical product and guide the drug development for more assertive ways.

In-Depth Analysis of Physiologically Based Pharmacokinetic (PBPK) Modeling Utilization in Different Application Fields Using Text Mining Tools

In the past decade, only a small number of papers have elaborated on the application of physiologically based pharmacokinetic (PBPK) modeling across different areas. In this review, an in-depth analysis of the distribution of PBPK modeling in relation to its application in various research topics and model validation was conducted by text mining tools. Orange 3.32.0, an open-source data mining program was used for text mining. PubMed was used for data retrieval, and the collected articles were analyzed by several widgets. A total of 2699 articles related to PBPK modeling met the predefined criteria. The number of publications per year has been rising steadily. Regarding the application areas, the results revealed that 26% of the publications described the use of PBPK modeling in early drug development, risk assessment and toxicity assessment, followed by absorption/formulation modeling (25%), prediction of drug-disease interactions (20%), drug-drug interactions (DDIs) (17%) and pediatric drug development (12%). Furthermore, the analysis showed that only 12% of the publications mentioned model validation, of which 51% referred to literature-based validation and 26% to experimentally validated models. The obtained results present a valuable review of the state-of-the-art regarding PBPK modeling applications in drug discovery and development and related fields.

Applications of bio-predictive dissolution tools for the development of solid oral dosage forms: Current industry experience

Development and optimization of orally administered drug products often require bio-predictive tools to help with informing formulation and manufacturing decisions. Reliable bio-predictive dissolution toolkits not only allow rational development of target formulations without having to conduct excessive in vivo studies but also help in detecting critical material attributes (CMAs), critical formulation variables (CFVs), or critical process parameters (CPPs) that could impact a drug's in vivo performance. To provide early insights for scientists on the development of a bio-predictive method for drug product development, this review summarizes current phase-appropriate bio-predictive dissolution approaches applicable to address typical concerns on solubility-limited absorption, food effect, achlorhydria, development of extended-release formulation, clinically relevant specification, and biowaiver. The selection of an in vitro method which can capture the key rate-limiting step(s) of the in vivo dissolution and/or absorption is considered to have a better chance to produce a meaningful in vitro-in vivo correlation (IVIVC) or in vitro-in vivo relationship (IVIVR).

The Use of Physiologically Based Pharmacokinetic Analyses-in Biopharmaceutics Applications -Regulatory and Industry Perspectives

The use of physiologically based pharmacokinetic (PBPK) modeling to support the drug product quality attributes, also known as physiologically based biopharmaceutics modeling (PBBM) is an evolving field and the interest in using PBBM is increasing. The US-FDA has emphasized on the use of patient centric quality standards and clinically relevant drug product specifications over the years. Establishing an in vitro in vivo link is an important step towards achieving the goal of patient centric quality standard. Such a link can aid in constructing a bioequivalence safe space and establishing clinically relevant drug product specifications. PBBM is an important tool to construct a safe space which can be used during the drug product development and lifecycle management. There are several advantages of using the PBBM approach, though there are also a few challenges, both with in vitro methods and in vivo understanding of drug absorption and disposition, that preclude using this approach and therefore further improvements are needed. In this review we have provided an overview of experience gained so far and the current perspective from regulatory and industry point of view. Collaboration between scientists from regulatory, industry and academic fields can further help to advance this field and deliver on promises that PBBM can offer towards establishing patient centric quality standards.

Physiologically Based Pharmacokinetic Modeling of Cefadroxil in Mouse, Rat, and Human to Predict Concentration-Time Profile at Infected Tissue

The aim of this study was to develop physiologically based pharmacokinetic (PBPK) models capable of simulating cefadroxil concentrations in plasma and tissues in mouse, rat, and human. PBPK models in this study consisted of 14 tissues and 2 blood compartments. They were established using measured tissue to plasma partition coefficient (K_p) in mouse and rat, absolute expression levels of hPEPT1 along the entire length of the human intestine, and the transporter kinetic parameters. The PBPK models also assumed that all the tissues were well-stirred compartments with perfusion rate limitations, and the ratio of the concentration in tissue to the unbound concentration in plasma is identical across species. These PBPK models were validated strictly by a series of observed plasma concentration–time profile data. The average fold error (AFE) and absolute average fold error (AAFE) values were all less than 2. The models’ rationality and accuracy were further demonstrated by the almost consistent V_ss calculated by the PBPK model and noncompartmental method, as well as the good allometric scaling relationship of V_ss and CL. The model suggests that hPEPT1 is the major transporter responsible for the oral absorption of cefadroxil in human, and the plasma concentration–time profiles of cefadroxil were not sensitive to dissolution rate faster than T_85% = 2 h. The cefadroxil PBPK model in human is reliable and can be used to predict concentration–time profile at infected tissue. It may be useful for dose selection and informative decision-making during clinical trials and dosage form design of cefadroxil and provide a reference for the PBPK model establishment of hPEPT1 substrate.

Performance Evaluation of Montelukast Pediatric Formulations: Part II - a PBPK Modelling Approach

This study aimed to build a physiologically based pharmacokinetic (PBPK) model coupled with age-appropriate in vitro dissolution data to describe drug performance in adults and pediatric patients. Montelukast sodium was chosen as a model drug. Two case studies were investigated: case study 1 focused on the description of formulation performance from adults to children; case study 2 focused on the description of the impact of medicine co-administration with vehicles on drug exposure in infants. The PBPK model for adults and pediatric patients was developed in Simcyp^® v18.2 informed by age-appropriate in vitro dissolution results obtained in a previous study. Oral administration of montelukast was simulated with the ADAM™ model. For case study 1, the developed PBPK model accurately described montelukast exposure in adults and children populations after the administration of montelukast chewable tablets. Two-stage dissolution testing in simulated fasted gastric to intestinal conditions resulted in the best description of in vivo drug performance in adults and children. For case study 2, a good description of in vivo drug performance in infants after medicine co-administration with vehicles was achieved by incorporating in vitro drug dissolution (under simulated fasted gastric to fed intestinal conditions) into a fed state PBPK model with consideration of the in vivo dosing conditions (mixing of formulation with applesauce or formula). The case studies presented demonstrate how a PBPK absorption modelling strategy can facilitate the description of drug performance in the pediatric population to support decision-making and biopharmaceutics understanding during pediatric drug development.

Best practices in current models mimicking drug permeability in the gastrointestinal tract - an UNGAP review

The absorption of orally administered drug products is a complex, dynamic process, dependent on a range of biopharmaceutical properties; notably the aqueous solubility of a molecule, stability within the gastrointestinal tract (GIT) and permeability. From a regulatory perspective, the concept of high intestinal permeability is intrinsically linked to the fraction of the oral dose absorbed. The relationship between permeability and the extent of absorption means that experimental models of permeability have regularly been used as a surrogate measure to estimate the fraction absorbed. Accurate assessment of a molecule's intestinal permeability is of critical importance during the pharmaceutical development process of oral drug products, and the current review provides a critique of in vivo, in vitro and ex vivo approaches. The usefulness of in silico models to predict drug permeability is also discussed and an overview of solvent systems used in permeability assessments is provided. Studies of drug absorption in humans are an indirect indicator of intestinal permeability, but in vitro and ex vivo tools provide initial screening approaches are important tools for direct assessment of permeability in drug development. Continued refinement of the accuracy of in silico approaches and their validation with human in vivo data will facilitate more efficient characterisation of permeability earlier in the drug development process and will provide useful inputs for integrated, end-to-end absorption modelling.

In silico bioavailability for BCS class II efavirenz tablets using biorelevant dissolution media for IVIVR and simulation of formulation changes

OBJECTIVE

This work aims to evaluate the ability of biorelevant dissolution media to simulate the bioavailability of efavirenz tablets, establish an in vitro-in vivo relationship (IVIVR) based on in vivo data using GastroPlus^® and simulate formulation changes using DDDPlus™.

METHODS

Solubility and drug release profiles were conducted in SLS 0.5% and biorelevant media, such as FaSSIF, FeSSIF, FaSSIF-V2, and FeSSIF-V2. The efavirenz physicochemical properties were used to simulate the plasma concentration profile and compare the simulated pharmacokinetic parameters in fasted and fed states. An IVIVR was developed using Loo-Riegelman as the deconvolution method to estimate drug bioavailability. DDDPlus™ was used to perform virtual trials of formulations to evaluate whether formulations changes and the efavirenz particle size could influence the bioavailability.

RESULTS

The drug dissolution displayed higher levels in the biorelevant media that simulated gut-fed state (FeSSIF and FeSSIF-V2). The absorption model successfully predicted the efavirenz pharmacokinetics, and FeSSIF-V2 was chosen as the predictive dissolution media, while an IVIVR was established using the Loo-Riegelman deconvolution method.

CONCLUSIONS

The present work provides valuable information about efavirenz solubility and kinetics in the gastrointestinal tract, allowing an IVIVR to support future formulation changes. This understanding is essential for rational science-driven formulation development. At least, this study also showed the validity and applicability of in vitro and in silico tools in the regulatory scenario helping on drug development.

Physiologically Based Biopharmaceutics Modeling to Demonstrate Virtual Bioequivalence and Bioequivalence Safe-space for Ribociclib which has Permeation Rate-controlled Absorption

A physiologically based biopharmaceutics model (PBBM) was developed to support formulation development of ribociclib, an orally bioavailable selective CDK4/6 inhibitor. Ribociclib is a weak base with moderate permeability and complete in vitro dissolution under stomach pH. GastroPlus™ was used to simulate the pharmacokinetics (PK) in healthy volunteers after capsule dosing. Simulations showed rapid, complete dissolution in human stomach without intestinal precipitation and with permeation-controlled absorption. Permeability was identified as controlling the systemic exposure. PBBM predicted bioequivalence (BE) between capsule and tablet in healthy volunteers, despite non-similarity between in vitro dissolution kinetics (f2<50). BE was verified in a clinical study. Then virtual bioequivalence (VBE) simulations predicted comparable PK in cancer patients between capsule and tablet of commercial batch, which was also confirmed in a clinical study. Finally, virtual trial simulations using virtual batches with slower dissolution were used to define an in vitro BE safe-space for tablets, where BE is expected. PBBM can identify drugs with permeability-controlled absorption for which formulation optimization can focus more on manufacturability rather than dissolution. PBBM can be used to predict BE study outcomes, define clinically relevant specification and BE safe-space, superseding dissolution similarity f2 criteria.

Topical finasteride dose evaluation for treatment of androgenetic alopecia using computer simulations

OBJECTIVE

Our objective was to evaluate the absorption of finasteride administered by oral and topical routes for treatment of androgenetic alopecia, by means of computer simulations using the GastroPlus ® software.

MATERIAL AND METHODS

In vivo plasma concentration profile of oral administration of finasteride 1 mg tablets from the literature was used in the software to build a compartmental pharmacokinetic model that was extrapolated to simulate topical administration of finasteride 0.25% solution in the scalp. Results were compared to literature and other drug concentrations (0.1% and 1%) were also predicted.

RESULTS

Compared to literature data, predictive plasma curve from oral administration of finasteride 1 mg showed good correlation, R²=0.992, and Cmax=4.6769 ng/mL. Simulations of topical administration in the scalp for finasteride 0.25% solution showed good correlation, R²=0.908, and Cmax=0.04325 ng/mL when compared to literature data. Topical administration was also simulated at concentrations 0.1% and 1%, both with low plasma concentrations.

CONCLUSION

The results obtained in this study suggest that topical finasteride is a potential treatment for androgenetic alopecia in the concentrations analyzed using computer simulations in GastroPlus ®.

Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Support Waivers of In Vivo Clinical Studies: Current Status, Challenges, and Opportunities

Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling has been extensively applied to quantitatively translate in vitro data, predict the in vivo performance, and ultimately support waivers of in vivo clinical studies. In the area of biopharmaceutics and within the context of model-informed drug discovery and development (MID3), there is a rapidly growing interest in applying verified and validated mechanistic PBPK models to waive in vivo clinical studies. However, the regulatory acceptance of PBPK analyses for biopharmaceutics and oral drug absorption applications, which is also referred to variously as "PBPK absorption modeling" [Zhang et al. CPT: Pharmacometrics Syst. Pharmacol. 2017, 6, 492], "physiologically based absorption modeling", or "physiologically based biopharmaceutics modeling" (PBBM), remains rather low [Kesisoglou et al. J. Pharm. Sci. 2016, 105, 2723] [Heimbach et al. AAPS J. 2019, 21, 29]. Despite considerable progress in the understanding of gastrointestinal (GI) physiology, in vitro biopharmaceutic and in silico tools, PBPK models for oral absorption often suffer from an incomplete understanding of the physiology, overparameterization, and insufficient model validation and/or platform verification, all of which can represent limitations to their translatability and predictive performance. The complex interactions of drug substances and (bioenabling) formulations with the highly dynamic and heterogeneous environment of the GI tract in different age, ethnic, and genetic groups as well as disease states have not been yet fully elucidated, and they deserve further research. Along with advancements in the understanding of GI physiology and refinement of current or development of fully mechanistic in silico tools, we strongly believe that harmonization, interdisciplinary interaction, and enhancement of the translational link between in vitro, in silico, and in vivo will determine the future of PBBM. This Perspective provides an overview of the current status of PBBM, reflects on challenges and knowledge gaps, and discusses future opportunities around PBPK/PD models for oral absorption of small and large molecules to waive in vivo clinical studies.

Can PBPK Modeling Streamline Food Effect Assessments?

Physiologically based pharmacokinetic (PBPK) modeling is routinely used to study drug-drug interactions, replace some dedicated clinical studies, and inform product labeling. More recently, there has been increased application of PBPK models in the oral absorption field around drug product quality. Given the success of the models to characterize absorption of several orally administered drug products, a question arises whether PBPK could be used in a clinical setting to model food-drug interactions and thus streamline food effect assessments. Multiple publications have reported food effect predictions and comparisons with clinical data, primarily focusing on 2 food effect mechanisms: slowing down of gastric emptying and luminal solubilization by bile salts. Based on the available literature, this commentary proposes a workflow that PBPK model could be used to streamline food effect assessment during clinical development for different Biopharmaceutics Classification System classes.

Simulation of oral absorption from non-bioequivalent dosage forms of the salt of raltegravir, a poorly soluble acidic drug, using a physiologically based biopharmaceutical modeling (PBBM) approach

Non-bioequivalent plasma concentration profiles among different dosage forms of the salt of raltegravir, a poorly soluble acidic drug, were investigated using biorelevant in vitro testing combined with the commercial in silico software, Simcyp®. A suspension and a tablet dosage forms of raltegravir potassium were selected as the test formulations. While dissolution from the suspension was rapid, dissolution from the tablets was slow and delayed by pre-exposure to an acidic environment. Although the tablet was expected to have complex in vivo performance, plasma concentration profiles were successfully simulated when gastric emptying was taken into account as a key physiological factor in in vitro and in silico trials. The effect of pre-exposure to acid in the stomach on dissolution behavior in the intestine was estimated by two-stage in vitro dissolution testing. Based on these results, theoretical in vivo dissolution profiles for different gastric emptying times were inputted into the in silico model and plasma concentration profiles were simulated taking the distribution of individual gastric emptying times into account. The in vitro and in silico method presented in this report would be a practical approach to simulate oral absorption from various formulations of poorly soluble weak acids and their salts.

Best Practices in the Development and Validation of Physiologically Based Biopharmaceutics Modeling. A Workshop Summary Report

This workshop report summarizes the proceedings of Day 2 of a three-day workshop on "Current State and Future Expectations of Translational Modeling Strategies toSupportDrug Product Development, Manufacturing Changes and Controls". From a drug product quality perspective, physiologically based biopharmaceutics modeling (PBBM) is a tool to link variations in the drug product quality attributes to in vivo outcomes enabling the establishment of clinically relevant drug product specifications (CRDPS). Day 2 of the workshop focused on best practices in developing, verifying and validating PBBM. This manuscript gives an overview of podium presentations and summarizes breakout (BO) session discussions related to (1) challenges and opportunities for using PBBM to assess the clinical impact of formulation and manufacturing changes on the in vivo performance of a drug product, (2) best practices to account for parameter uncertainty and variability during model development, (3) best practices in the development, verification and validation of PBBM and (4) opportunities and knowledge gaps related to leveraging PBBM for virtual bioequivalence simulations.

Predicting the effect of prandial stage and particle size on absorption of ODM-204

The prediction of absorption properties plays a key role in formulation development when the compound under development shows poor solubility and its absorption is therefore presumed to be solubility limited. In our work, we combined and compared data obtained from in vitro dissolution tests, transit intestinal model studies (TIM-1) and physiologically based pharmacokinetic modelling. Our aim was to determine the ability of these methods to predict performance of poorly soluble lipophilic weak base in vivo. The validity of the predictive methods was evaluated against the in vivo clinical pharmacokinetic (PK) data obtained after administration of the first test formulation, T1. The aim of our study was to utilize the models in evaluating absorption properties of the second test formulation, T2, which has not yet been clinically administered. The compound in the studies was ODM-204, which is a novel, orally administered, investigational, nonsteroidal dual inhibitor of CYP17A1 and androgen receptor. Owing to its physicochemical properties ODM-204 is prone to low or variable bioavailability. The models examined provided congruent data on dose dependent absorption, food effect at a dose of 200 mg and on the effect of API (active pharmaceutical ingredient) particle size on absorption. Our study shows that the predictive tools of in vitro dissolution, TIM-1 system and the PBPK (physiologically based pharmacokinetic) simulation, showed predictive power of different mechanisms of bioavailability and together provided valuable information for decision making.

A Biopharmetrics Approach for Drug Product Quality Control with Clinical Relevance

To exemplify a systematic and quantitative approach (Biopharmetrics approach) for product quality control with clinical relevance, the study utilized multivariate models to connect raw material attributes of a product to its dissolution obtained in a DOE (design of experiment) and further extended the connection to the in vivo exposures (AUC and Cmax) of the product using an available IVIVC (in vitro/in vivo correlation). Thus, a model for the relationship between in vivo exposure and raw material attributes of the product was established. Based on the model, the exposure ratios between future batches (with various raw material attributes) and the pivotal clinical batches (with confirmed clinical efficacy and safety) were predicted resulting in a set of contour lines in a graphical representation. Among these contour lines, the lines for exposure ratios of 0.8 and 1.2 were defined as lower and upper limits. With the failure edges defined, clinically meaningful limits for the raw material quality control were specified. If the raw material attributes in the future production conform to the specifications, the manufacturing would lead to products bioequivalent to the clinical batches. From these exercises, Biopharmetrics, a subdiscipline of biopharmaceutics, was introduced and its definition, scope, and characteristics were discussed.

Integrated Multi-stakeholder Systems Thinking Strategy: Decision-making with Biopharmaceutics Risk Assessment Roadmap (BioRAM) to Optimize Clinical Performance of Drug Products

Decision-making in drug development benefits from an integrated systems approach, where the stakeholders identify and address the critical questions for the system through carefully designed and performed studies. Biopharmaceutics Risk Assessment Roadmap (BioRAM) is such a systems approach for application of systems thinking to patient focused and timely decision-making, suitable for all stages of drug discovery and development. We described the BioRAM therapy-driven drug delivery framework, strategic roadmap, and integrated risk assessment instrument (BioRAM Scoring Grid) in previous publications (J Pharm Sci 103:3377-97, 2014; J Pharm Sci 105:3243-55, 2016). Integration of systems thinking with pharmaceutical development, manufacturing, and clinical sciences and health care is unique to BioRAM where the developed strategy identifies the system and enables risk characterization and balancing for the entire system. Successful decision-making process in BioRAM starts with the Blueprint (BP) meetings. Through shared understanding of the system, the program strategy is developed and captured in the program BP. Here, we provide three semi-hypothetical examples for illustrating risk-based decision-making in high and moderate risk settings. In the high-risk setting, which is a rare disease area, two completely alternate development approaches are considered (gene therapy and small molecule). The two moderate-risk examples represent varied knowledge levels and drivers for the programs. In one moderate-risk example, knowledge leveraging opportunities are drawn from the manufacturing knowledge and clinical performance of a similar drug substance. In the other example, knowledge on acute tolerance patterns for a similar mechanistic pathway is utilized for identifying markers to inform the drug release profile from the dosage form with the necessary "flexibility" for dosing. All examples illustrate implementation of the BioRAM strategy for leveraging knowledge and decision-making to optimize the clinical performance of drug products for patient benefit.

The Provisional No-Effect Threshold of Sugar Alcohols on Oral Drug Absorption Estimated by Physiologically Based Biopharmaceutics Model

Sugar alcohols reduce oral drug bioavailability by osmotic effects, but the magnitude of these effects differs among different drugs. This study aimed to identify the drug-related critical attributes of osmotic effects and estimate the impact of a "practical" sugar alcohol dose on the pharmacokinetics of various molecules using modeling and simulation approaches. We developed a physiologically based biopharmaceutics model that considers the dose-dependent effects of sugar alcohols on the gastrointestinal physiology. The developed model captured the effects of sugar alcohols on ranitidine hydrochloride, metoprolol tartrate, theophylline, cimetidine, and lamivudine. Sensitivity analysis provided quantitative insights into the effects of sugar alcohols dependent on different drug permeability. In addition, our developed model indicated for the first time that a high systemic elimination rate is crucial for the reduction in maximum plasma concentration even for highly permeable drugs. Nonetheless, mannitol/sorbitol level of less than 400 mg had minor effects on the pharmacokinetics of the most sensitive drugs, indicating a provisional no-effect threshold dose. This mechanistic approach provides comprehensive estimation of osmotic effects on variety of drugs. Subsequently, these findings may invoke scientific discussion on the criteria for excipient changes in the context of biowaiver guidelines (e.g. biopharmaceutics classification system-based biowaiver).

In vitro - in vivo relations for the parenteral liposomal formulation of Amphotericin B: A clinically relevant approach with PBPK modeling

In vitro release testing is a useful tool for the quality control of controlled release parenteral formulations, but in vitro release test conditions that reflect or are able to predict the in vivo performance are advantageous. Therefore, it is important to investigate the factors that could affect drug release from formulations and relate them to in vivo performance. In this study the effect of media composition including albumin presence, type of buffer and hydrodynamics on drug release were evaluated on a liposomal Amphotericin B formulation (Ambisome®). A physiologically based pharmacokinetic (PBPK) model was developed using plasma concentration profiles from healthy subjects, in order to investigate the impact of each variable from the in vitro release tests on the prediction of the in vivo performance. It was found that albumin presence was the most important factor for the release of Amphotericin B from Ambisome®; both hydrodynamics setups, coupled with the PBPK model, had comparable predictive ability for simulating in vivo plasma concentration profiles. The PBPK model was extrapolated to a hypothetical hypoalbuminaemic population and the Amphotericin B plasma concentration and its activity against fungal cells were simulated. Selected in vitro release tests for these controlled release parenteral formulations were able to predict the in vivo AmB exposure, and this PBPK driven approach to release test development could benefit development of such formulations.

In Silico Prediction of Plasma Concentrations of Fluconazole Capsules with Different Dissolution Profiles and Bioequivalence Study Using Population Simulation

A biowaiver is accepted by the Brazilian Health Surveillance Agency (ANVISA) for immediate-release solid oral products containing Biopharmaceutics Classification System (BCS) class I drugs showing rapid drug dissolution. This study aimed to simulate plasma concentrations of fluconazole capsules with different dissolution profiles and run population simulation to evaluate their bioequivalence. The dissolution profiles of two batches of the reference product Zoltec^® 150 mg capsules, A1 and A2, and two batches of other products (B1 and B2; C1 and C2), as well as plasma concentration–time data of the reference product from the literature, were used for the simulations. Although products C1 and C2 had drug dissolutions < 85% in 30 min at 0.1 M HCl, simulation results demonstrated that these products would show the same in vivo performance as products A1, A2, B1, and B2. Population simulation results of the ln-transformed 90% confidence interval for the ratio of C_max and AUC_0–t values for all products were within the 80–125% interval, showing to be bioequivalent. Thus, even though the in vitro dissolution behavior of products C1 and C2 was not equivalent to a rapid dissolution profile, the computer simulations proved to be an important tool to show the possibility of bioequivalence for these products.

Assessment of Biopharmaceutical Performance of Supersaturating Formulations of Carbamazepine in Rats Using Physiologically Based Pharmacokinetic Modeling

There is an overgrowing emphasis on supersaturating drug delivery systems (SDDS) with increase in number of poorly water-soluble compounds. However, biopharmaceutical performance from these formulations is limited by phase transformation to stable crystalline form due to their high-energy physical form. In the present study, in vitro kinetic solubility in water and dissolution in biorelevant medium integrated with in silico physiologically based pharmacokinetic (PBPK) modeling was used to predict biopharmaceutical performance of SDDS of poorly water-soluble compound, carbamazepine (CBZ). GastroPlus™ with advanced compartmental absorption and transit model was used as a simulation tool for the study. Wherein, the model was developed using physicochemical properties of CBZ and disposition parameters obtained after intravenous administration of CBZ (20 mg/kg) into Sprague-Dawley (SD) rats. Biorelevant medium was selected by screening different dissolution media for their capability to predict oral plasma concentration-time profile of marketed formulation of CBZ. In vivo performance of SDDS was predicted with the developed model and compared to observed plasma concentration-time profile obtained after oral administration of SDDS into SD rats (20 mg/kg). The predictions, with strategy of using kinetic solubility and dissolution in the selected biorelevant medium, were consistent with observed biopharmaceutical performance of SDDS. Additionally, phase transformation of CBZ during gastrointestinal transit of formulations was evaluated and correlated with in vivo dissolution deconvoluted by Loo-Reigelman analysis.

The impact of food intake on the luminal environment and performance of oral drug products with a view to in vitro and in silico simulations: a PEARRL review

Objectives

Using the type of meal and dosing conditions suggested by regulatory agencies as a basis, this review has two specific objectives: first, to summarize our understanding on the impact of food intake on luminal environment and drug product performance and second, to summarize the usefulness and limitations of available in vitro and in silico methodologies for the evaluation of drug product performance after food intake.

Key findings

Characterization of the luminal environment and studies evaluating product performance in the lumen, under conditions suggested by regulatory agencies for simulating the fed state, are limited. Various in vitro methodologies have been proposed for evaluating drug product performance in the fed state, but systematic validation is lacking. Physiologically based pharmacokinetic (PBPK) modelling approaches require the use of in vitro biorelevant data and, to date, have been used primarily for investigating the mechanisms via which an already observed food effect is mediated.

Summary

Better understanding of the impact of changes induced by the meal administration conditions suggested by regulatory agencies on the luminal fate of the drug product is needed. Relevant information will be useful for optimizing the in vitro test methods and increasing the usefulness of PBPK modelling methodologies.

The growing role of precision and personalized medicine for cancer treatment

Cancer is a devastating disease that takes the lives of hundreds of thousands of people every year. Due to disease heterogeneity, standard treatments, such as chemotherapy or radiation, are effective in only a subset of the patient population. Tumors can have different underlying genetic causes and may express different proteins in one patient versus another. This inherent variability of cancer lends itself to the growing field of precision and personalized medicine (PPM). There are many ongoing efforts to acquire PPM data in order to characterize molecular differences between tumors. Some PPM products are already available to link these differences to an effective drug. It is clear that PPM cancer treatments can result in immense patient benefits, and companies and regulatory agencies have begun to recognize this. However, broader changes to the healthcare and insurance systems must be addressed if PPM is to become part of standard cancer care.

Effects of medicines used to treat gastrointestinal diseases on the pharmacokinetics of coadministered drugs: a PEARRL Review

Objectives

Drugs used to treat gastrointestinal diseases (GI drugs) are widely used either as prescription or over-the-counter (OTC) medications and belong to both the 10 most prescribed and 10 most sold OTC medications worldwide. The objective of this review article is to discuss the most frequent interactions between GI and other drugs, including identification of the mechanisms behind these interactions, where possible.

Key findings

Current clinical practice shows that in many cases, these drugs are administered concomitantly with other drug products. Due to their metabolic properties and mechanisms of action, the drugs used to treat gastrointestinal diseases can change the pharmacokinetics of some coadministered drugs. In certain cases, these interactions can lead to failure of treatment or to the occurrence of serious adverse events. The mechanism of interaction depends highly on drug properties and differs among therapeutic categories. Understanding these interactions is essential to providing recommendations for optimal drug therapy.

Summary

Interactions with GI drugs are numerous and can be highly significant clinically in some cases. While alterations in bioavailability due to changes in solubility, dissolution rate, GI transit and metabolic interactions can be (for the most part) easily identified, interactions that are mediated through other mechanisms, such as permeability or microbiota, are less well-understood. Future work should focus on characterising these aspects.

Computational modeling of human oral bioavailability: what will be next?

INTRODUCTION

The oral route is the most convenient way of administrating drugs. Therefore, accurate determination of oral bioavailability is paramount during drug discovery and development. Quantitative structure-property relationship (QSPR), rule-of-thumb (RoT) and physiologically based-pharmacokinetic (PBPK) approaches are promising alternatives to the early oral bioavailability prediction. Areas covered: The authors give insight into the factors affecting bioavailability, the fundamental theoretical framework and the practical aspects of computational methods for predicting this property. They also give their perspectives on future computational models for estimating oral bioavailability. Expert opinion: Oral bioavailability is a multi-factorial pharmacokinetic property with its accurate prediction challenging. For RoT and QSPR modeling, the reliability of datasets, the significance of molecular descriptor families and the diversity of chemometric tools used are important factors that define model predictability and interpretability. Likewise, for PBPK modeling the integrity of the pharmacokinetic data, the number of input parameters, the complexity of statistical analysis and the software packages used are relevant factors in bioavailability prediction. Although these approaches have been utilized independently, the tendency to use hybrid QSPR-PBPK approaches together with the exploration of ensemble and deep-learning systems for QSPR modeling of oral bioavailability has opened new avenues for development promising tools for oral bioavailability prediction.

Predictive Performance of Physiologically Based Pharmacokinetic Models for the Effect of Food on Oral Drug Absorption: Current Status

A comprehensive search in literature and published US Food and Drug Administration reviews was conducted to assess whether physiologically based pharmacokinetic (PBPK) modeling could be prospectively used to predict clinical food effect on oral drug absorption. Among the 48 resulted food effect predictions, ∼50% were predicted within 1.25‐fold of observed, and 75% within 2‐fold. Dissolution rate and precipitation time were commonly optimized parameters when PBPK modeling was not able to capture the food effect. The current work presents a knowledgebase for documenting PBPK experience to predict food effect.

Physiologically-based pharmacokinetic models: approaches for enabling personalized medicine

Personalized medicine strives to deliver the 'right drug at the right dose' by considering inter-person variability, one of the causes for therapeutic failure in specialized populations of patients. Physiologically-based pharmacokinetic (PBPK) modeling is a key tool in the advancement of personalized medicine to evaluate complex clinical scenarios, making use of physiological information as well as physicochemical data to simulate various physiological states to predict the distribution of pharmacokinetic responses. The increased dependency on PBPK models to address regulatory questions is aligned with the ability of PBPK models to minimize ethical and technical difficulties associated with pharmacokinetic and toxicology experiments for special patient populations. Subpopulation modeling can be achieved through an iterative and integrative approach using an adopt, adapt, develop, assess, amend, and deliver methodology. PBPK modeling has two valuable applications in personalized medicine: (1) determining the importance of certain subpopulations within a distribution of pharmacokinetic responses for a given drug formulation and (2) establishing the formulation design space needed to attain a targeted drug plasma concentration profile. This review article focuses on model development for physiological differences associated with sex (male vs. female), age (pediatric vs. young adults vs. elderly), disease state (healthy vs. unhealthy), and temporal variation (influence of biological rhythms), connecting them to drug product formulation development within the quality by design framework. Although PBPK modeling has come a long way, there is still a lengthy road before it can be fully accepted by pharmacologists, clinicians, and the broader industry.