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

A novel simulated media system for in vitro evaluation of bioequivalent intestinal drug solubility

Orally administered solid drug must dissolve in the gastrointestinal tract before absorption to provide a systemic response. Intestinal solubility is therefore crucial but difficult to measure since human intestinal fluid (HIF) is challenging to obtain, varies between fasted (Fa) and fed (Fe) states and exhibits inter and intra subject variability. A single simulated intestinal fluid (SIF) cannot reflect HIF variability, therefore current approaches are not optimal. In this study we have compared literature Fa/FeHIF drug solubilities to values measured in a novel in vitro simulated nine media system for either the fasted (Fa9SIF) or fed (Fe9SIF) state. The manuscript contains 129 literature sampled human intestinal fluid equilibrium solubility values and 387 simulated intestinal fluid equilibrium solubility values. Statistical comparison does not detect a difference (Fa/Fe9SIF vs Fa/FeHIF), a novel solubility correlation window enclosed 95% of an additional literature Fa/FeHIF data set and solubility behaviour is consistent with previous physicochemical studies. The Fa/Fe9SIF system therefore represents a novel in vitro methodology for bioequivalent intestinal solubility determination. Combined with intestinal permeability this provides an improved, population based, biopharmaceutical assessment that guides formulation development and indicates the presence of food based solubility effects. This transforms predictive ability during drug discovery and development and may represent a methodology applicable to other multicomponent fluids where no single component is responsible for performance.

The Use of Global Sensitivity Analysis to Assess the Oral Absorption of Weakly Basic Compounds: A Case Example of Dipyridamole

OBJECTIVE

To utilize the global system analysis (GSA) in oral absorption modeling to gain a deeper understanding of system behavior, improve model accuracy, and make informed decisions during drug development.

METHODS

GSA was utilized to give insight into which drug substance (DS), drug product (DP), and/or physiological parameter would have an impact on peak plasma concentration (Cmax) and area under the curve (AUC) of dipyridamole as a model weakly basic compound. GSA guided the design of in vitro experiments and oral absorption risk assessment using FormulatedProducts v2202.1.0. The solubility and precipitation profiles of dipyridamole in different bile salt concentrations were measured. The results were then used to build a mechanistic oral absorption model.

RESULTS

GSA warranted further investigation into the precipitation kinetics and its link to the levels of bile salt concentrations. Mechanistic modeling studies demonstrated that a precipitation-integrated modeling approach appropriately predicted the mean plasma profiles, Cmax, and AUC from the clinical studies.

CONCLUSIONS

This work shows the value of GSA utilization in early development to guide in vitro experimentation and build more confidence in identifying the critical parameters for the mathematical models.

Approaches to Account for Colon Absorption in Physiologically Based Biopharmaceutics Modeling of Extended-Release Drug Products

The rate and extent of colon absorption are important determinants of the in vivo performance of extended-release (ER) drug products. The ability to appropriately predict this at different stages of development using mechanistic physiologically based biopharmaceutic modeling (PBBM) is highly desirable. This investigation aimed to evaluate the prediction performance of three different approaches to account for colon absorption in predictions of the in vivo performance of ER drug product variants with different in vitro release profiles. This was done by mechanistic predictions of the absorption and plasma exposure of the ER drug products using GastroPlus and GI-Sim for five drugs with different degrees of colon absorption limitations in humans. Colon absorption was accounted for in the predictions using three different approaches: (1) by an a priori approach using the default colon models, (2) by fitting the colon absorption scaling factors to the observed plasma concentration-time profiles after direct administration to the colon in humans, or (3) from the ER drug product variant with the slowest in vitro release profile. The prediction performance was evaluated based on the percentage prediction error and the average absolute prediction error (AAPE). Two levels of acceptance criteria corresponding to highly accurate (AAPE ≤ 20%) and accurate (AAPE 20-50%) predictions were defined prior to the evaluation. For the a priori approach, the relative bioavailability (Frel), AUC0-t, and Cmax of the ER drug product variants for the low to medium colon absorption limitation risk drugs was accurately predicted with an AAPE range of 11-53 and 8-59% for GastroPlus and GI-Sim, respectively. However, the prediction performance was poor for the high colon absorption limitation risk drugs. Moreover, accounting for the human regional colon absorption data in the models did not improve the prediction performance. In contrast, using the colon absorption scaling factors derived from the slowest ER variant significantly improved the prediction performance regardless of colon absorption limitation, with a majority of the predictions meeting the high accuracy criteria. For the slowest ER approach, the AAPE ranges were 5-24 and 5-32% for GastroPlus and GI-Sim, respectively, excluding the low permeability drug. In conclusion, the a priori PBBM can be used during candidate selection and early product design to predict the in vivo performance of ER drug products for low to medium colon absorption limitation risk drugs with sufficient accuracy. The results also indicate a limited value in performing human regional absorption studies in which the drug is administered to the colon as a bolus to support PBBM development for ER drug products. Instead, by performing an early streamlined relative bioavailability study with the slowest relevant ER in vitro release profile, a highly accurate PBBM suitable for ER predictions for commercial and regulatory applications can be developed, except for permeability-limited drugs.

Predicting the Pharmacokinetics of Orally Administered Drugs across BCS Classes 1-4 by Virtual Bioequivalence Model

To evaluate the influence of solubility and permeability on the pharmacokinetic prediction performance of orally administered drugs using avirtual bioequivalence (VBE) model, a total of 23 orally administered drugs covering Biopharmaceutics Classification System (BCS) classes 1-4 were selected. A VBE model (i.e., a physiologically based pharmacokinetic model integrated with dissolution data) based on a B²O simulator was applied for pharmacokinetic (PK) prediction in a virtual population. Parameter sensitivity analysis was used for input parameter selection. The predictive performances of PK parameters (i.e., AUC_0-t, C_max, and T_max), PK profiles, and bioequivalence (BE) results were evaluated using the twofold error, average fold error (AFE), absolute average fold error (AAFE), and BE reassessment metrics. All models successfully simulated the mean PK profiles, with AAFE < 2 and AFE ranging from 0.58 to 1.66. As for the PK parameters, except for the time of peak concentration, T_max, of isosorbide mononitrate, other simulated PK parameters were all within a twofold error. The simulated PK behaviors were comparable to the observed ones, both for test (T) and reference (R) products, and the simulated T/R arithmetic mean ratios were all within 0.88-1.16 of the observed values. These four evaluation metrics were distributed equally among BCS class 1-4 drugs. The VBE model showed powerful performance to predict the PK behavior of orally administered drugs with various combinations of solubility and permeability, irrespective of the BCS category.

Evaluation of the Success of High-Throughput Physiologically Based Pharmacokinetic (HT-PBPK) Modeling Predictions to Inform Early Drug Discovery

Minimizing in vitro and in vivo testing in early drug discovery with the use of physiologically based pharmacokinetic (PBPK) modeling and machine learning (ML) approaches has the potential to reduce discovery cycle times and animal experimentation. However, the prediction success of such an approach has not been shown for a larger and diverse set of compounds representative of a lead optimization pipeline. In this study, the prediction success of the oral (PO) and intravenous (IV) pharmacokinetics (PK) parameters in rats was assessed using a “bottom-up” approach, combining in vitro and ML inputs with a PBPK model. More than 240 compounds for which all of the necessary inputs and PK data were available were used for this assessment. Different clearance scaling approaches were assessed, using hepatocyte intrinsic clearance and protein binding as inputs. In addition, a novel high-throughput PBPK (HT-PBPK) approach was evaluated to assess the scalability of PBPK predictions for a larger number of compounds in drug discovery. The results showed that bottom-up PBPK modeling was able to predict the rat IV and PO PK parameters for the majority of compounds within a 2- to 3-fold error range, using both direct scaling and dilution methods for clearance predictions. The use of only ML-predicted inputs from the structure did not perform well when using in vitro inputs, likely due to clearance miss predictions. The HT-PBPK approach produced comparable results to the full PBPK modeling approach but reduced the simulation time from hours to seconds. In conclusion, a bottom-up PBPK and HT-PBPK approach can successfully predict the PK parameters and guide early discovery by informing compound prioritization, provided that good in vitro assays are in place for key parameters such as clearance.

An IQ Consortium Perspective on Connecting Dissolution Methods to In Vivo Performance: Analysis of an Industrial Database and Case Studies to Propose a Workflow

Assessment of bioperformance to inform formulation selection and development decisions is an important aspect of drug development. There is high demand in the pharmaceutical industry to develop an efficient and streamlined approach for better understanding and predicting drug product performance to support acceleration of clinical timelines. This manuscript presents an effort from the IQ Formulation Bioperformance Prediction Working Group composed of members from 12 pharmaceutical companies under the IQ Consortium to develop a database around the topic of formulation bioperformance prediction and report findings from the database analysis. Six case studies described in the manuscript demonstrate how bioperformance models were used to predict in vivo performance and to provide guidance addressing questions encountered during oral solid dosage form development. The case studies also described findings of a correlation between in vitro dissolution and in vivo performance and how dissolution data can be incorporated into physiologically based biopharmaceutical modeling. Finally, a workflow for how in vitro dissolution data can be utilized to predict clinical bioperformance of oral solid dosage forms is proposed.

Integration of advanced methods and models to study drug absorption and related processes: An UNGAP perspective

This collection of contributions from the European Network on Understanding Gastrointestinal Absorption-related Processes (UNGAP) community assembly aims to provide information on some of the current and newer methods employed to study the behaviour of medicines. It is the product of interactions in the immediate pre-Covid period when UNGAP members were able to meet and set up workshops and to discuss progress across the disciplines. UNGAP activities are divided into work packages that cover special treatment populations, absorption processes in different regions of the gut, the development of advanced formulations and the integration of food and pharmaceutical scientists in the food-drug interface. This involves both new and established technical approaches in which we have attempted to define best practice and highlight areas where further research is needed. Over the last months we have been able to reflect on some of the key innovative approaches which we were tasked with mapping, including theoretical, in silico, in vitro, in vivo and ex vivo, preclinical and clinical approaches. This is the product of some of us in a snapshot of where UNGAP has travelled and what aspects of innovative technologies are important. It is not a comprehensive review of all methods used in research to study drug dissolution and absorption, but provides an ample panorama of current and advanced methods generally and potentially useful in this area. This collection starts from a consideration of advances in a priori approaches: an understanding of the molecular properties of the compound to predict biological characteristics relevant to absorption. The next four sections discuss a major activity in the UNGAP initiative, the pursuit of more representative conditions to study lumenal dissolution of drug formulations developed independently by academic teams. They are important because they illustrate examples of in vitro simulation systems that have begun to provide a useful understanding of formulation behaviour in the upper GI tract for industry. The Leuven team highlights the importance of the physiology of the digestive tract, as they describe the relevance of gastric and intestinal fluids on the behaviour of drugs along the tract. This provides the introduction to microdosing as an early tool to study drug disposition. Microdosing in oncology is starting to use gamma-emitting tracers, which provides a link through SPECT to the next section on nuclear medicine. The last two papers link the modelling approaches used by the pharmaceutical industry, in silico to Pop-PK linking to Darwich and Aarons, who provide discussion on pharmacometric modelling, completing the loop of molecule to man.

Translational precision medicine: an industry perspective

In the era of precision medicine, digital technologies and artificial intelligence, drug discovery and development face unprecedented opportunities for product and business model innovation, fundamentally changing the traditional approach of how drugs are discovered, developed and marketed. Critical to this transformation is the adoption of new technologies in the drug development process, catalyzing the transition from serendipity-driven to data-driven medicine. This paradigm shift comes with a need for both translation and precision, leading to a modern Translational Precision Medicine approach to drug discovery and development. Key components of Translational Precision Medicine are multi-omics profiling, digital biomarkers, model-based data integration, artificial intelligence, biomarker-guided trial designs and patient-centric companion diagnostics. In this review, we summarize and critically discuss the potential and challenges of Translational Precision Medicine from a cross-industry perspective.

Current challenges and future perspectives in oral absorption research: An opinion of the UNGAP network

Although oral drug delivery is the preferred administration route and has been used for centuries, modern drug discovery and development pipelines challenge conventional formulation approaches and highlight the insufficient mechanistic understanding of processes critical to oral drug absorption. This review presents the opinion of UNGAP scientists on four key themes across the oral absorption landscape: (1) specific patient populations, (2) regional differences in the gastrointestinal tract, (3) advanced formulations and (4) food-drug interactions. The differences of oral absorption in pediatric and geriatric populations, the specific issues in colonic absorption, the formulation approaches for poorly water-soluble (small molecules) and poorly permeable (peptides, RNA etc.) drugs, as well as the vast realm of food effects, are some of the topics discussed in detail. The identified controversies and gaps in the current understanding of gastrointestinal absorption-related processes are used to create a roadmap for the future of oral drug absorption research.

Physiological-based pharmacokinetic modeling trends in pharmaceutical drug development over the last 20-years; in-depth analysis of applications, organizations, and platforms

We assess the advancement of physiologically based pharmacokinetic (PBPK) modeling and simulation (M&S) over the last 20 years (start of 2000 to end of 2019) focusing on the trends in each decade with the relative contributions from different organizations, areas of applications, and software tools used. Unlike many of the previous publications which focused on regulatory applications, our analysis is based on PBPK publications in peer-reviewed journals based on a large sample (>700 original articles). We estimated a rate of growth for PBPK (>40 fold/20 years) that was much steeper than the general pharmacokinetic modeling (<3 fold/20 years) or overall scientific publications (∼3 fold/20 years). The analyses demonstrated that contrary to commonly held belief, commercial specialized PBPK platforms with graphical-user interface were a much more popular choice than open-source alternatives even within academic organizations. These platforms constituted 81% of the whole set of the sample we assessed. The major PBPK applications (top 3) were associated with the study design, predicting formulation effects, and metabolic drug-drug interactions, while studying the fate of drugs in special populations, predicting kinetics in early drug development, and investigating transporter drug interactions have increased proportionally over the last decade. The proportions of application areas based on published research were distinctively different from those shown previously for the regulatory submissions and impact on labels. This may demonstrate the lag time between the research applications versus verified usage within the regulatory framework. The report showed the trend of overall PBPK publications in pharmacology drug development from the past 2 decades stratified by the organizations involved, software used, and area of applications. The analysis showed a more rapid increase in PBPK than that of the pharmacokinetic space itself with an equal contribution from academia and industry. By establishing and recording the journey of PBPK modeling in the past and looking at its current status, the analysis can be used for devising plans based on the anticipated trajectory of future regulatory applications.

Human Health Effects of Lactose Consumption as a Food and Drug Ingredient

Lactose is a reducing sugar consisting of galactose and glucose, linked by a β (1→4) glycosidic bond, considered as an antioxidant due to its α-hydroxycarbonyl group. Lactose is widely ingested through the milk and other unfermented dairy products and is considered to be one of the primary foods. On the other hand, lactose is also considered as one of the most widely used excipients for the development of pharmaceutical formulations. In this sense, lactose has been related to numerous drug-excipient or drug-food pharmacokinetic interactions. Intolerance, maldigestion and malabsorption of carbohydrates are common disorders in clinical practice, with lactose-intolerance being the most frequently diagnosed, afflicting 10% of the world's population. Four clinical subtypes of lactose intolerance may be distinguished, namely lactase deficiency in premature infants, congenital lactase deficiency, adult-type hypolactasia and secondary lactase intolerance. An overview of the main uses of lactose in human nutrition and in the pharmaceutical industry and the problems derived from this circumstance are described in this review.

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.

Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies

Physiologically based pharmacokinetic modelling is well established in the pharmaceutical industry and is accepted by regulatory agencies for the prediction of drug-drug interactions. However, physiologically based pharmacokinetic modelling is valuable to address a much wider range of pharmaceutical applications, and new regulatory impact is expected as its full power is leveraged. As one example, physiologically based pharmacokinetic modelling is already routinely used during drug discovery for in-vitro to in-vivo translation and pharmacokinetic modelling in preclinical species, and this leads to the application of verified models for first-in-human pharmacokinetic predictions. A consistent cross-industry strategy in this application area would increase confidence in the approach and facilitate further learning. With this in mind, this article aims to enhance a previously published first-in-human physiologically based pharmacokinetic model-building strategy. Based on the experience of scientists from multiple companies participating in the GastroPlus™ User Group Steering Committee, new Absorption, Distribution, Metabolism and Excretion knowledge is integrated and decision trees proposed for each essential component of a first-in-human prediction. We have reviewed many relevant scientific publications to identify new findings and highlight gaps that need to be addressed. Finally, four industry case studies for more challenging compounds illustrate and highlight key components of the strategy.

Prediction Characteristics of Oral Absorption Simulation Software Evaluated Using Structurally Diverse Low-Solubility Drugs

The purpose of the present study was to characterize current biopharmaceutics modeling and simulation software regarding the prediction of the fraction of a dose absorbed (Fa) in humans. As commercial software products, GastroPlus™ and Simcyp® were used. In addition, the gastrointestinal unified theoretical framework, a simple and publicly accessible model, was used as a benchmark. The Fa prediction characteristics for a total of 96 clinical Fa data of 27 model drugs were systematically evaluated using the default settings of each software product. The molecular weight, dissociation constant, octanol-water partition coefficient, solubility in biorelevant media, dose, and particle size of model drugs were used as input data. Although the same input parameters were used, GastroPlus™, Simcyp®, and the gastrointestinal unified theoretical framework showed different Fa prediction characteristics depending on the rate-limiting steps of oral drug absorption. The results of the present study would be of great help for the overall progression of physiologically based absorption models.

Intestinal Permeability and Drug Absorption: Predictive Experimental, Computational and In Vivo Approaches

The main objective of this review is to discuss recent advancements in the overall investigation and in vivo prediction of drug absorption. The intestinal permeability of an orally administered drug (given the value P_eff) has been widely used to determine the rate and extent of the drug’s intestinal absorption (F_abs) in humans. Preclinical gastrointestinal (GI) absorption models are currently in demand for the pharmaceutical development of novel dosage forms and new drug products. However, there is a strong need to improve our understanding of the interplay between pharmaceutical, biopharmaceutical, biochemical, and physiological factors when predicting F_abs and bioavailability. Currently, our knowledge of GI secretion, GI motility, and regional intestinal permeability, in both healthy subjects and patients with GI diseases, is limited by the relative inaccessibility of some intestinal segments of the human GI tract. In particular, our understanding of the complex and highly dynamic physiology of the region from the mid-jejunum to the sigmoid colon could be significantly improved. One approach to the assessment of intestinal permeability is to use animal models that allow these intestinal regions to be investigated in detail and then to compare the results with those from simple human permeability models such as cell cultures. Investigation of intestinal drug permeation processes is a crucial biopharmaceutical step in the development of oral pharmaceutical products. The determination of the intestinal P_eff for a specific drug is dependent on the technique, model, and conditions applied, and is influenced by multiple interactions between the drug molecule and the biological membranes.

Variance based global sensitivity analysis of physiologically based pharmacokinetic absorption models for BCS I-IV drugs

Regulatory agencies have a strong interest in sensitivity analysis for the evaluation of physiologically-based pharmacokinetic (PBPK) models used in pharmaceutical research and drug development and regulatory submissions. One of the applications of PBPK is the prediction of fraction absorbed and bioavailability for drugs following oral administration. In this context, we performed a variance based global sensitivity analysis (GSA) on in-house PBPK models for drug absorption, with the aim of identifying key parameters that influence the predictions of the fraction absorbed and the bioavailability for neutral, acidic and basic compounds. This analysis was done for four different classes of drugs, defined according to the Biopharmaceutics Classification System, differentiating compounds by permeability and solubility. For class I compounds (highly permeable, highly soluble), the parameters that mainly influence the fraction absorbed are related to the formulation properties, for class II compounds (highly permeable, lowly soluble) to the dissolution process, for class III (lowly permeable, highly soluble) to both absorption process and formulation properties and for class IV (lowly permeable, lowly soluble) to both absorption and dissolution processes. Considering the bioavailability, the results are similar to those for the fraction absorbed, with the addition that parameters related to gut wall and liver clearance influence as well the predictions. This work aimed to give a demonstration of the GSA methodology and highlight its importance in improving our understanding of PBPK absorption models and in guiding the choice of parameters that can safely be assumed, estimated or require data generation to allow informed model prediction.

Population variability in animal health: Influence on dose-exposure-response relationships: Part II: Modelling and simulation

During the 2017 Biennial meeting, the American Academy of Veterinary Pharmacology and Therapeutics hosted a 1-day session on the influence of population variability on dose-exposure-response relationships. In Part I, we highlighted some of the sources of population variability. Part II provides a summary of discussions on modelling and simulation tools that utilize existing pharmacokinetic data, can integrate drug physicochemical characteristics with species physiological characteristics and dosing information or that combine observed with predicted and in vitro information to explore and describe sources of variability that may influence the safe and effective use of veterinary pharmaceuticals.

Ribociclib Bioavailability Is Not Affected by Gastric pH Changes or Food Intake: In Silico and Clinical Evaluations

Ribociclib (KISQALI), a cyclin‐dependent kinase 4/6 inhibitor approved for the first‐line treatment of HR+/HER2– advanced breast cancer with an aromatase inhibitor, is administered with no restrictions on concomitant gastric pH‐elevating agents or food intake. The influence of proton pump inhibitors (PPIs) on ribociclib bioavailability was assessed using 1) biorelevant media solubility, 2) physiologically based pharmacokinetic (PBPK) modeling, 3) noncompartmental analysis (NCA) of clinical trial data, and 4) population PK (PopPK) analysis. This multipronged approach indicated no effect of gastric pH changes on ribociclib PK and served as a platform for supporting ribociclib labeling language, stating no impact of gastric pH‐altering agents on the absorption of ribociclib, without a dedicated drug–drug interaction trial. The bioequivalence of ribociclib exposure with or without a high‐fat meal was demonstrated in a clinical trial. Lack of restrictions on ribociclib dosing may facilitate better patient compliance and therefore clinical benefit.

An in silico approach to determine challenges in the bioavailability of ciprofloxacin, a poorly soluble weak base with borderline solubility and permeability characteristics

Ciprofloxacin is administered as the hydrochloride salt in immediate release formulations for the treatment of various infectious diseases in different patient populations. Due to its weakly basic properties and poor solubility, the in vivo behaviour of this compound could be influenced by both physicochemical and physiological factors. The first aim of this study was to investigate the behaviour of ciprofloxacin (Ciprobay® 500 mg tablets) in the human gastro-intestinal tract with in vitro dissolution, transfer and two-stage experiments. Ciprobay® IR tablets dissolved completely in FaSSGF-V2, but dissolution was incomplete in FaSSIF-V2 and in an achlorhydric medium (FaSSGF-achlorhydric) and slow precipitation was observed in all three media. Ciprofloxacin did not precipitate in the transfer model but in the two-stage test, a simplified version of the transfer model, some precipitation was detected. In the second part of this study the data obtained in the in vitro transfer experiment were integrated into a Physiologically Based Pharmacokinetic (PBPK) Model. Based on the in vitro results, it was concluded that precipitation of ciprofloxacin would be unlikely in vivo. When precipitation was assumed to be negligible in the PBPK model, good predictions of plasma concentration time profiles provided by Bayer Pharma AG and obtained from the open literature were attained. Parameter Sensitivity Analysis (PSA) was conducted on several parameters which may influence the in vivo behaviour of ciprofloxacin. It was shown that precipitation in the gastro-intestinal tract in humans after a dose of 500 mg is not a determinant of the PK profile. PSA further suggested that ciprofloxacin behaves in vivo as a BCS Class I drug according to the Biopharmaceutics Classification System (BCS), even though on the basis of available solubility and permeability data the compound has been categorised as a BCS II/IV drug. These findings illustrate the importance of coupling in vitro results with in silico PBPK models to better understand the in vivo behaviour of weakly basic drugs. The PBPK model of ciprofloxacin, which was set up for healthy volunteers, was also modified to predict the in vivo behaviour of ciprofloxacin in several different patient populations. It was shown on the basis of these simulations that the plasma concentration time profile may be less influenced by disease state than previously expected.

Physiologically Based Oral Absorption Modelling to Study Gut-Level Drug Interactions

Physiologically based oral absorption models are in silico tools primarily used to guide formulation development and project the clinical performance of formulation variants. This commentary briefly discusses additional oral absorption model applications, focusing on gut-level drug interactions. Gut-level drug interactions can involve drug degradation, metabolic enzymes, transporters, gastrointestinal motility modulators, acid-reducing agents, and food. The growth in publications reporting physiologically based oral absorption model utilization and successful pharmacokinetic prediction (e.g., after acid-reducing agents or food coadministration) indicate that oral absorption models have achieved a level of maturity within the industry particularly over the past 15 years. Provided appropriate data and model validation, oral absorption modeling/simulation may serve as a surrogate for clinical studies by providing both mechanistic and quantitative understanding of oral delivery considerations on pharmacokinetics.

IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 2: An introduction to the simulation exercise and overview of results

Orally administered drugs are subject to a number of barriers impacting bioavailability (F_oral), causing challenges during drug and formulation development. Physiologically-based pharmacokinetic (PBPK) modelling can help during drug and formulation development by providing quantitative predictions through a systems approach. The performance of three available PBPK software packages (GI-Sim, Simcyp®, and GastroPlus™) were evaluated by comparing simulated and observed pharmacokinetic (PK) parameters. Since the availability of input parameters was heterogeneous and highly variable, caution is required when interpreting the results of this exercise. Additionally, this prospective simulation exercise may not be representative of prospective modelling in industry, as API information was limited to sparse details. 43 active pharmaceutical ingredients (APIs) from the OrBiTo database were selected for the exercise. Over 4000 simulation output files were generated, representing over 2550 study arm-institution-software combinations and approximately 600 human clinical study arms simulated with overlap. 84% of the simulated study arms represented administration of immediate release formulations, 11% prolonged or delayed release, and 5% intravenous (i.v.). Higher percentages of i.v. predicted area under the curve (AUC) were within two-fold of observed (52.9%) compared to per oral (p.o.) (37.2%), however, F_oral and relative AUC (F_rel) between p.o. formulations and solutions were generally well predicted (64.7% and 75.0%). Predictive performance declined progressing from i.v. to solution and immediate release tablet, indicating the compounding error with each layer of complexity. Overall performance was comparable to previous large-scale evaluations. A general overprediction of AUC was observed with average fold error (AFE) of 1.56 over all simulations. AFE ranged from 0.0361 to 64.0 across the 43 APIs, with 25 showing overpredictions. Discrepancies between software packages were observed for a few APIs, the largest being 606, 171, and 81.7-fold differences in AFE between SimCYP and GI-Sim, however average performance was relatively consistent across the three software platforms.