Physiologically-based pharmacokinetic simulation modelling

G × E interactions as a basis for toxicological uncertainty

To transfer toxicological findings from model systems, e.g. animals, to humans, standardized safety factors are applied to account for intra-species and inter-species variabilities. An alternative approach would be to measure and model the actual compound-specific uncertainties. This biological concept assumes that all observed toxicities depend not only on the exposure situation (environment = E), but also on the genetic (G) background of the model (G × E). As a quantitative discipline, toxicology needs to move beyond merely qualitative G × E concepts. Research programs are required that determine the major biological variabilities affecting toxicity and categorize their relative weights and contributions. In a complementary approach, detailed case studies need to explore the role of genetic backgrounds in the adverse effects of defined chemicals. In addition, current understanding of the selection and propagation of adverse outcome pathways (AOP) in different biological environments is very limited. To improve understanding, a particular focus is required on modulatory and counter-regulatory steps. For quantitative approaches to address uncertainties, the concept of "genetic" influence needs a more precise definition. What is usually meant by this term in the context of G × E are the protein functions encoded by the genes. Besides the gene sequence, the regulation of the gene expression and function should also be accounted for. The widened concept of past and present "gene expression" influences is summarized here as Ge. Also, the concept of "environment" needs some re-consideration in situations where exposure timing (Et) is pivotal: prolonged or repeated exposure to the insult (chemical, physical, life style) affects Ge. This implies that it changes the model system. The interaction of Ge with Et might be denoted as Ge × Et. We provide here general explanations and specific examples for this concept and show how it could be applied in the context of New Approach Methodologies (NAM).

Quantitative prediction of pharmacokinetic properties of drugs in humans: Recent advance in in vitro models to predict the impact of efflux transporters in the small intestine and blood-brain barrier

Efflux transport systems are essential to suppress the absorption of xenobiotics from the intestinal lumen and protect the critical tissues at the blood-tissue barriers, such as the blood-brain barrier. The function of drug efflux transport is dominated by various transporters. Accumulated clinical evidences have revealed that genetic variations of the transporters, together with coadministered drugs, affect the expression and/or function of transporters and subsequently the pharmacokinetics of substrate drugs. Thus, in the preclinical stage of drug development, quantitative prediction of the impact of efflux transporters as well as that of uptake transporters and metabolic enzymes on the pharmacokinetics of drugs in humans has been performed using various in vitro experimental tools. Various kinds of human-derived cell systems can be applied to the precise prediction of drug transport in humans. Mathematical modeling consisting of each intrinsic metabolic or transport process enables us to understand the disposition of drugs both at the organ level and at the level of the whole body by integrating a variety of experimental results into model parameters. This review focuses on the role of efflux transporters in the intestinal absorption and brain distribution of drugs, in addition to recent advances in predictive tools and methodologies.

A Mechanistic Site-Of-Action Model: A Tool for Informing Right Target, Right Compound, And Right Dose for Therapeutic Antagonistic Antibody Programs

Quantitative modeling is increasingly utilized in the drug discovery and development process, from the initial stages of target selection, through clinical studies. The modeling can provide guidance on three major questions–is this the right target, what are the right compound properties, and what is the right dose for moving the best possible candidate forward. In this manuscript, we present a site-of-action modeling framework which we apply to monoclonal antibodies against soluble targets. We give a comprehensive overview of how we construct the model and how we parametrize it and include several examples of how to apply this framework for answering the questions postulated above. The utilities and limitations of this approach are discussed.

The EU-ToxRisk method documentation, data processing and chemical testing pipeline for the regulatory use of new approach methods

Hazard assessment, based on new approach methods (NAM), requires the use of batteries of assays, where individual tests may be contributed by different laboratories. A unified strategy for such collaborative testing is presented. It details all procedures required to allow test information to be usable for integrated hazard assessment, strategic project decisions and/or for regulatory purposes. The EU-ToxRisk project developed a strategy to provide regulatorily valid data, and exemplified this using a panel of > 20 assays (with > 50 individual endpoints), each exposed to 19 well-known test compounds (e.g. rotenone, colchicine, mercury, paracetamol, rifampicine, paraquat, taxol). Examples of strategy implementation are provided for all aspects required to ensure data validity: (i) documentation of test methods in a publicly accessible database; (ii) deposition of standard operating procedures (SOP) at the European Union DB-ALM repository; (iii) test readiness scoring accoding to defined criteria; (iv) disclosure of the pipeline for data processing; (v) link of uncertainty measures and metadata to the data; (vi) definition of test chemicals, their handling and their behavior in test media; (vii) specification of the test purpose and overall evaluation plans. Moreover, data generation was exemplified by providing results from 25 reporter assays. A complete evaluation of the entire test battery will be described elsewhere. A major learning from the retrospective analysis of this large testing project was the need for thorough definitions of the above strategy aspects, ideally in form of a study pre-registration, to allow adequate interpretation of the data and to ensure overall scientific/toxicological validity.

The Financial Benefits of Faster Development Times: Integrated Formulation Development, Real-Time Manufacturing, and Clinical Testing

PURPOSE

Faster drug development times get new therapies to patients sooner and financially benefit drug developers by shortening the time between investment and returns and increasing the time on the market with intellectual property protection. The result is enhanced incentives to innovate. We provide a real-world example of the financial gains from quicker development using recent estimates of drug development costs, returns, and estimates of time reductions from an alternative early-stage drug development paradigm.

METHODS

We utilized data obtained from a drug development and manufacturing services organization to estimate the reduction in development time for drug sponsors from using an integrated platform of formulation development, real-time manufacturing, and clinical testing for 19 completed drug product development projects covering three key drug development activities (transitioning from first-in-human to proof-of-concept [FIH-PoC], modified release formulation development [MR], and enhanced solubility formulation development [ES]). A traditional drug development paradigm was taken as the base case and financial impacts of the alternative development program were determined relative to the base case.

FINDINGS

The total after-tax financial benefits of shorter development times from integrating formulation development, real-time manufacturing, and clinical testing when applied across a broad portfolio of investigational drugs ranged from $230.5 million to $290.1 million, $196.4 million to $247.5 million, and $102.6 million to $275.5 million, per approved new drug for FIH-PoC, MR, and ES applications, respectively (2018 dollars).

IMPLICATIONS

For the data we examined, this integrated development model yielded substantial financial benefits over traditional drug development.

Concordance between Thioacetamide-Induced Liver Injury in Rat and Human In Vitro Gene Expression Data

The immense resources required and the ethical concerns for animal-based toxicological studies have driven the development of in vitro and in silico approaches. Recently, we validated our approach in which the expression of a set of genes is uniquely associated with an organ-injury phenotype (injury module), by using thioacetamide, a known liver toxicant. Here, we sought to explore whether RNA-seq data obtained from human cells (in vitro) treated with thioacetamide-S-oxide (a toxic intermediate metabolite) would correlate across species with the injury responses found in rat cells (in vitro) after exposure to this metabolite as well as in rats exposed to thioacetamide (in vivo). We treated two human cell types with thioacetamide-S-oxide (primary hepatocytes with 0 (vehicle), 0.125 (low dose), or 0.25 (high dose) mM, and renal tubular epithelial cells with 0 (vehicle), 0.25 (low dose), or 1.00 (high dose) mM) and collected RNA-seq data 9 or 24 h after treatment. We found that the liver-injury modules significantly altered in human hepatocytes 24 h after high-dose treatment involved cellular infiltration and bile duct proliferation, which are linked to fibrosis. For high-dose treatments, our modular approach predicted the rat in vivo and in vitro results from human in vitro RNA-seq data with Pearson correlation coefficients of 0.60 and 0.63, respectively, which was not observed for individual genes or KEGG pathways.

Kinetic analysis of sequential metabolism of triazolam and its extrapolation to humans using an entero-hepatic two-organ microphysiological system

The microphysiological system (MPS) is a promising tool for predicting drug disposition in humans, although limited information is available on the quantitative assessment of sequential drug metabolism in MPS and its extrapolation to humans. In the present study, we first constructed a mechanism-based pharmacokinetic model for triazolam (TRZ) and its metabolites in the entero-hepatic two-organ MPS, composed of intestinal Caco-2 and hepatic HepaRG cells, and attempted to extrapolate the kinetic information obtained with the MPS to the plasma concentration profiles in humans. In the two-organ MPS and HepaRG single culture systems, TRZ was found to be metabolized into α- and 4-hydroxytriazolam and their respective glucuronides. All these metabolites were almost completely reduced in the presence of a CYP3A inhibitor, itraconazole, confirming sequential phase I and II metabolism. Both pharmacokinetic model-dependent and -independent analyses were performed, providing consistent results regarding the metabolic activity of TRZ: clearance of glucuronidation metabolites in the two-organ MPS was higher than that in the single culture system. The plasma concentration profile of TRZ and its two hydroxy metabolites in humans was quantitatively simulated based on the pharmacokinetic model, by incorporating several scaling factors representing quantitative gaps between the MPS and humans. Thus, the present study provided the first quantitative extrapolation of sequential drug metabolism in humans by combining MPS and pharmacokinetic modeling.

Meta-Analysis of Pharmacokinetic Studies of Nanobiomaterials for the Prediction of Excretion Depending on Particle Characteristics

The growth in development and use of nanobiomaterials (NBMs) has raised questions regarding their possible distribution in the environment. Because most NBMs are not yet available on the market and exposure monitoring is thus not possible, prospective exposure modeling is the method of choice to get information on their future environmental exposure. An important input for such models is the fraction of the NBM excreted after their application to humans. The aim of this study was to analyze the current literature on excretion of NBMs using a meta-analysis. Published pharmacokinetic data from in vivo animal experiments was collected and compiled in a database, including information on the material characteristics. An evaluation of the data showed that there is no correlation between the excretion (in % of injected dose, ID) and the material type, the dose, the zeta potential or the size of the particles. However, the excretion is dependent on the type of administration with orally administered NBMs being excreted to a larger extent than intravenously administered ones. A statistically significant difference was found for IV vs. oral and oral vs. inhalation. The database provided by this work can be used for future studies to parameterize the transfer of NBMs from humans to wastewater. Generic probability distributions of excretion for oral and IV-administration are provided to enable excretion modeling of NBMs without data for a specific NBM.

Animal to human translation: a systematic scoping review of reported concordance rates

Background

Drug development is currently hampered by high attrition rates; many developed treatments fail during clinical testing. Part of the attrition may be due to low animal-to-human translational success rates; so-called “translational failure”. As far as we know, no systematic overview of published translational success rates exists.

Systematic scoping review

The following research question was examined: “What is the observed range of the animal-to-human translational success (and failure) rates within the currently available empirical evidence?”. We searched PubMed and Embase on 16 October 2017. We included reviews and all other types of “umbrella”-studies of meta-data quantitatively comparing the translational results of studies including at least two species with one being human. We supplemented our database searches with additional strategies. All abstracts and full-text papers were screened by two independent reviewers. Our scoping review comprises 121 references, with various units of measurement: compound or intervention (k = 104), study/experiment (k = 10), and symptom or event (k = 7). Diagnostic statistics corresponded with binary and continuous definitions of successful translation. Binary definitions comprise percentages below twofold error, percentages accurately predicted, and predictive values. Quantitative definitions comprise correlation/regression (r²) and meta-analyses (percentage overlap of 95% confidence intervals). Translational success rates ranged from 0 to 100%.

Conclusion

The wide range of translational success rates observed in our study might indicate that translational success is unpredictable; i.e. it might be unclear upfront if the results of primary animal studies will contribute to translational knowledge. However, the risk of bias of the included studies was high, and much of the included evidence is old, while newer models have become available. Therefore, the reliability of the cumulative evidence from current papers on this topic is insufficient. Further in-depth “umbrella”-studies of translational success rates are still warranted. These are needed to evaluate the probabilistic evidence for predictivity of animal studies for the human situation more reliably, and to determine which factors affect this process.

Application of a Novel 'Make and Test in Parallel' Strategy to Investigate the Effect of Formulation on the Pharmacokinetics of GDC-0810 in Healthy Subjects

Purpose

GDC-0810, administered orally, was used in Phase I and II clinical studies to treat estrogen receptor positive breast cancers. It contains N-methyl-D-glucamine (NMG) salt of GDC-0810 with 10% sodium lauryl sulfate (SLS) as a surfactant and 15% sodium bicarbonate (NaHCO₃) as an alkalizing agent to aid dissolution. To improve the processability of the formulation and reduce potential mucosal irritation in future Phase III clinical studies, the salt form and the amount of excipient required further optimization. To achieve this, we employed a novel “Make and Test in Parallel” strategy that facilitated selecting formulation in a rapid timeframe.

Methods

RapidFACT®, a streamlined, data-driven drug product optimization platform was used to bridge Phase I/II and Phase III formulations of GDC-0810. Five prototype formulations, varying in either the form of active pharmaceutical ingredient and/or the levels of the excipients SLS and NaHCO₃ were assessed. Uniquely, the specific compositions of formulations manufactured and dosed were selected in real-time from emerging clinical data.

Results

The study successfully identified a Phase III formulation with a reduced SLS content, which when administered following a low-fat meal, gave comparable pharmacokinetic exposure to the Phase I/II formulation administered under the same conditions.

Conclusions

Our novel ‘Make and Test in Parallel’ approach enabled optimization of GDC-0810 formulation in a time- and cost-efficient fashion.

Prediction of tissue concentrations of monoclonal antibodies in mice from plasma concentrations

The objectives of this study were to develop and evaluate allometric methods for predicting tissue-to-plasma partition coefficients (Kp) in mice from experimentally determined in-vivo volume of distribution at steady state (Vss) for monoclonal antibodies (mAbs). The Vss was allometrically predicted (using a fixed exponent 1.0 or 0.9) in a given tissue of the mice. The Kp was predicted using Vss and tissue specific physiological parameters. In total, Kp values were predicted for 20 mAbs, 121 tissues, and 665 tissue concentrations. The predicted Kp values and tissue concentrations were compared with the experimental results as well as an empirically predicted antibody biodistribution coefficient (ABC). Comparison of the predicted Kp values by the two proposed methods with experimentally determined Kp values indicated that 64-75% of the predicted Kp values were within two-fold prediction error. For 665 tissue concentrations, 63%, 74%, and 48% tissue concentration ratio were within 0.5-2 fold prediction error by exponent 1.0, exponent 0.9, and ABC, respectively. The proposed allometric methods are better than ABC method for the prediction of tissue Kp values and tissue concentrations. The proposed methods can reasonably predict tissue concentrations of mAbs using plasma concentration gathered at early stage of biologics development.

Structural insights into suppressor of cytokine signaling 1 protein- identification of new leads for type 2 diabetes mellitus

The study considers the Suppressor of cytokine signaling 1 (SOCS1) protein as a novel Type 2 diabetes mellitus (T2DM) drug target. T2DM in human beings is also triggered by the over expression of SOCS proteins. The SOCS1 acts as a ubiquitin ligase (E3), degrades Insulin Receptor Substrate 1 and 2 (IRS1 and IRS2) proteins, and causes insulin resistance. Therefore, the structure of the SOCS1 protein was evaluated using homology-modeling and molecular dynamics methods and validated using standard computational protocols. The Protein-Protein docking study of SOCS1 with its natural substrates, IRS1 and IRS2, and subsequent solvent accessible surface area analysis gave insight into the binding region of the SOCS1 protein. The in silico active site prediction tools highlight the residues Val155 to Ile211 in SOCS1 being implicated in the ubiquitin mediated protein degradation of the proteins IRS1 and IRS2. Virtual screening in the active site region, using large structural databases, results in selective lead structures with 3-Pyridinol, Xanthine, and Alanine moieties as Pharmacophore. The virtual screening study shows that the residues Glu149, Gly187, Arg188, Leu191, and Ser205 of the SOCS1 are important for binding. The docking study with current anti-diabetic therapeutics shows that the drugs Glibenclamide and Glyclopyramide have a partial affinity towards SOCS1. The predicted ADMET and IC₅₀ properties for the identified ligands are within the acceptable range with drug-like properties. The structural data of SOCS1, its active site, and the identified lead structures are expedient in the development of new T2DM therapeutics.

Improved anticoagulant effect of fucosylated chondroitin sulfate orally administered as gastroresistant tablets

Fucosylated chondroitin sulfate (FucCS) is a potent anticoagulant polysaccharide extracted from sea cucumber. Its anticoagulant activity is attributed to the presence of unique branches of sulfated fucose. Although this glycosaminoglycan exerts an antithrombotic effect following oral administration, high doses are necessary to achieve the maximum effect. The diminished activity of FucCS following oral administration is likely due to its degradation in the gastrointestinal tract and its limited ability to cross the intestinal cell membranes. The latter aspect is particularly difficult to overcome. However, gastroresistant tablet formulation may help limit the degradation of FucCS in the gastrointestinal tract. In the present work, we found that the oral administration of FucCS as gastroresistant tablets produces a more potent and prolonged anticoagulant effect compared with its administration as an aqueous solution, with no significant changes in the bleeding tendency or arterial blood pressure. Experiments using animal models of arterial thrombosis initiated by endothelial injury demonstrated that FucCS delivered as gastro-protective tablets produced a potent antithrombotic effect, whereas its aqueous solution was ineffective. However, there was no significant difference between the effects of FucCS delivered as gastroresistant tablets or as aqueous solution in a venous thrombosis model, likely due to the high dose of thromboplastin used. New oral anticoagulants tested in these experimental models for comparison showed significantly increased bleeding tendencies. Our study provides a framework for developing effective oral anticoagulants based on sulfated polysaccharides from marine organisms. The present results suggest that FucCS is a promising oral anticoagulant.

Supplementary Material to this article is available online at www.thrombosis-online.com.

Pharmaceutical cocrystals, salts and polymorphs: Advanced characterization techniques

The main goal of a novel drug development is to obtain it with optimal physiochemical, pharmaceutical and biological properties. Pharmaceutical companies and scientists modify active pharmaceutical ingredients (APIs), which often are cocrystals, salts or carefully selected polymorphs, to improve the properties of a parent drug. To find the best form of a drug, various advanced characterization methods should be used. In this review, we have described such analytical methods, dedicated to solid drug forms. Thus, diffraction, spectroscopic, thermal and also pharmaceutical characterization methods are discussed. They all are necessary to study a solid API in its intrinsic complexity from bulk down to the molecular level, gain information on its structure, properties, purity and possible transformations, and make the characterization efficient, comprehensive and complete. Furthermore, these methods can be used to monitor and investigate physical processes, involved in the drug development, in situ and in real time. The main aim of this paper is to gather information on the current advancements in the analytical methods and highlight their pharmaceutical relevance.

Lipid-associated oral delivery: Mechanisms and analysis of oral absorption enhancement

The majority of newly discovered oral drugs are poorly water soluble, and co-administration with lipids has proven effective in significantly enhancing bioavailability of some compounds with low aqueous solubility. Yet, lipid-based delivery technologies have not been widely employed in commercial oral products. Lipids can impact drug transport and fate in the gastrointestinal (GI) tract through multiple mechanisms including enhancement of solubility and dissolution kinetics, enhancement of permeation through the intestinal mucosa, and triggering drug precipitation upon lipid emulsion depletion (e.g., by digestion). The effect of lipids on drug absorption is currently not quantitatively predictable, in part due to the multiple complex dynamic processes that can be impacted by lipids. Quantitative mechanistic analysis of the processes significant to lipid system function and overall impact on drug absorption can aid in the understanding of drug-lipid interactions in the GI tract and exploitation of such interactions to achieve optimal lipid-based drug delivery. In this review, we discuss the impact of co-delivered lipids and lipid digestion on drug dissolution, partitioning, and absorption in the context of the experimental tools and associated kinetic expressions used to study and model these processes. The potential benefit of a systems-based consideration of the concurrent multiple dynamic processes occurring upon co-dosing lipids and drugs to predict the impact of lipids on drug absorption and enable rational design of lipid-based delivery systems is presented.

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.

The solubility-permeability interplay and oral drug formulation design: Two heads are better than one

Poor aqueous solubility is a major challenge in today's biopharmaceutics. While solubility-enabling formulations can significantly increase the apparent solubility of the drug, the concomitant effect on the drug's apparent permeability has been largely overlooked. The mathematical equation to describe the membrane permeability of a drug comprises the membrane/aqueous partition coefficient, which in turn is dependent on the drug's apparent solubility in the GI milieu, suggesting that the solubility and the permeability are closely related, exhibit a certain interplay between them, and treating the one irrespectively of the other may be insufficient. In this article, an overview of this solubility-permeability interplay is provided, and the available data is analyzed in the context of the effort to maximize the overall drug exposure. Overall, depending on the type of solubility-permeability interplay, the permeability may decrease, remain unchanged, and even increase, in a way that may critically affect the formulation capability to improve the overall absorption. Therefore, an intelligent design of solubility-enabling formulation needs to consider both the solubility afforded by the formulation and the permeability in the new luminal environment resulting from the formulation.

Gut Wall Metabolism. Application of Pre-Clinical Models for the Prediction of Human Drug Absorption and First-Pass Elimination

Quantifying the multiple processes which control and modulate the extent of oral bioavailability for drug candidates is critical to accurate projection of human pharmacokinetics (PK). Understanding how gut wall metabolism and hepatic elimination factor into first-pass clearance of drugs has improved enormously. Typically, the cytochrome P450s, uridine 5'-diphosphate-glucuronosyltransferases and sulfotransferases, are the main enzyme classes responsible for drug metabolism. Knowledge of the isoforms functionally expressed within organs of first-pass clearance, their anatomical topology (e.g. zonal distribution), protein homology and relative abundances and how these differ across species is important for building models of human metabolic extraction. The focus of this manuscript is to explore the parameters influencing bioavailability and to consider how well these are predicted in human from animal models or from in vitro to in vivo extrapolation. A unique retrospective analysis of three AstraZeneca molecules progressed to first in human PK studies is used to highlight the impact that species differences in gut wall metabolism can have on predicted human PK. Compared to the liver, pharmaceutical research has further to go in terms of adopting a common approach for characterisation and quantitative prediction of intestinal metabolism. A broad strategy is needed to integrate assessment of intestinal metabolism in the context of typical DMPK activities ongoing within drug discovery programmes up until candidate drug nomination.

Lost in translation: the need for better tools

Although for most pharmaceutical compounds the final aim is improving human health, almost all the methods used to identify and pursue therapeutic targets and to obtain new potential drugs have traditionally focused on animal models

Paediatric oral biopharmaceutics: key considerations and current challenges

The complex process of oral drug absorption is influenced by a host of drug and formulation properties as well as their interaction with the gastrointestinal environment in terms of drug solubility, dissolution, permeability and pre-systemic metabolism. For adult dosage forms the use of biopharmaceutical tools to aid in the design and development of medicinal products is well documented. This review considers current literature evidence to guide development of bespoke paediatric biopharmaceutics tools and reviews current understanding surrounding extrapolation of adult methodology into a paediatric population. Clinical testing and the use of in silico models were also reviewed. The results demonstrate that further work is required to adequately characterise the paediatric gastrointestinal tract to ensure that biopharmaceutics tools are appropriate to predict performance within this population. The most vulnerable group was found to be neonates and infants up to 6 months where differences from adults were greatest.

The use of ROC analysis for the qualitative prediction of human oral bioavailability from animal data

Purpose

To develop and evaluate a tool for the qualitative prediction of human oral bioavailability (F_human) from animal oral bioavailability (F_animal) data employing ROC analysis and to identify the optimal thresholds for such predictions.

Methods

A dataset of 184 compounds with known F_human and F_animal in at least one species (mouse, rat, dog and non-human primates (NHP)) was employed. A binary classification model for F_human was built by setting a threshold for high/low F_human at 50%. The thresholds for high/low F_animal were varied from 0 to 100 to generate the ROC curves. Optimal thresholds were derived from ‘cost analysis’ and the outcomes with respect to false negative and false positive predictions were analyzed against the BDDCS class distributions.

Results

We successfully built ROC curves for the combined dataset and per individual species. Optimal F_animal thresholds were found to be 67% (mouse), 22% (rat), 58% (dog), 35% (NHP) and 47% (combined dataset). No significant trends were observed when sub-categorizing the outcomes by the BDDCS.

Conclusions

F_animal can predict high/low F_human with adequate sensitivity and specificity. This methodology and associated thresholds can be employed as part of decisions related to planning necessary studies during development of new drug candidates and lead selection.

Electronic supplementary material

The online version of this article (doi:10.1007/s11095-013-1193-2) contains supplementary material, which is available to authorized users.

Animal versus human oral drug bioavailability: do they correlate?

Oral bioavailability is a key consideration in development of drug products, and the use of preclinical species in predicting bioavailability in human has long been debated. In order to clarify whether any correlation between human and animal bioavailability exist, an extensive analysis of the published literature data was conducted. Due to the complex nature of bioavailability calculations inclusion criteria were applied to ensure integrity of the data. A database of 184 compounds was assembled. Linear regression for the reported compounds indicated no strong or predictive correlations to human data for all species, individually and combined.

The lack of correlation in this extended dataset highlights that animal bioavailability is not quantitatively predictive of bioavailability in human. Although qualitative (high/low bioavailability) indications might be possible, models taking into account species-specific factors that may affect bioavailability are recommended for developing quantitative prediction.

A simplified PBPK modeling approach for prediction of pharmacokinetics of four primarily renally excreted and CYP3A metabolized compounds during pregnancy

During pregnancy, a drug's pharmacokinetics may be altered and hence anticipation of potential systemic exposure changes is highly desirable. Physiologically based pharmacokinetics (PBPK) models have recently been used to influence clinical trial design or to facilitate regulatory interactions. Ideally, whole-body PBPK models can be used to predict a drug's systemic exposure in pregnant women based on major physiological changes which can impact drug clearance (i.e., in the kidney and liver) and distribution (i.e., adipose and fetoplacental unit). We described a simple and readily implementable multitissue/organ whole-body PBPK model with key pregnancy-related physiological parameters to characterize the PK of reference drugs (metformin, digoxin, midazolam, and emtricitabine) in pregnant women compared with the PK in nonpregnant or postpartum (PP) women. Physiological data related to changes in maternal body weight, tissue volume, cardiac output, renal function, blood flows, and cytochrome P450 activity were collected from the literature and incorporated into the structural PBPK model that describes HV or PP women PK data. Subsequently, the changes in exposure (area under the curve (AUC) and maximum concentration (C max)) in pregnant women were simulated. Model-simulated PK profiles were overall in agreement with observed data. The prediction fold error for C max and AUC ratio (pregnant vs. nonpregnant) was less than 1.3-fold, indicating that the pregnant PBPK model is useful. The utilization of this simplified model in drug development may aid in designing clinical studies to identify potential exposure changes in pregnant women a priori for compounds which are mainly eliminated renally or metabolized by CYP3A4.

Utilizing in vitro and PBPK tools to link ADME characteristics to plasma profiles: case example nifedipine immediate release formulation

One of the most prominent food-drug interactions is the inhibition of intestinal cytochrome P450 (CYP) 3A enzymes by grapefruit juice ingredients, and, as many drugs are metabolized via CYP 3A, this interaction can be of clinical importance. Calcium channel-blocking agents of the dihydropyridine type, such as felodipine and nifedipine, are subject to extensive intestinal first pass metabolism via CYP 3A, thus resulting in significantly enhanced in vivo exposure of the drug when administered together with grapefruit juice. Physiologically based pharmacokinetic (PBPK) modeling was used to simulate pharmacokinetics of a nifedipine immediate release formulation following concomitant grapefruit juice ingestion, that is, after inhibition of small intestinal CYP 3A enzymes. For this purpose, detailed data about CYP 3A levels were collected from the literature and implemented into commercial PBPK software. As literature reports show that grapefruit juice (i) leads to a marked delay in gastric emptying, and (ii) rapidly lowers the levels of intestinal CYP 3A enzymes, inhibition of intestinal first pass metabolism following ingestion of grapefruit juice was simulated by altering the intestinal CYP 3A enzyme levels and simultaneously decelerating the gastric emptying rate. To estimate the in vivo dispersion and dissolution behavior of the formulation, dissolution tests in several media simulating both the fasted and fed state stomach and small intestine were conducted, and the results from the in vitro dissolution tests were used as input function to describe the in vivo dissolution of the drug. Plasma concentration-time profiles of the nifedipine immediate release formulation both with and without simultaneous CYP 3A inhibition were simulated, and the results were compared with data gathered from the literature. Using this approach, nifedipine plasma profiles could be simulated well both with and without enzyme inhibition. A reduction in small intestinal CYP 3A levels by 60% was found to yield the best results, with simulated nifedipine concentration-time profiles within 20% of the in vivo observed results. By additionally varying the dissolution input of the PBPK model, a link between the dissolution characteristics of the formulation and its in vivo performance could be established.

Assessment of juvenile pigs to serve as human pediatric surrogates for preclinical formulation pharmacokinetic testing

Pediatric drug development is hampered by biological, clinical, and formulation challenges associated with age-based populations. A primary cause for this lack of development is the inability to accurately predict ontogenic changes that affect pharmacokinetics (PK) in children using traditional preclinical animal models. In response to this issue, our laboratory has conducted a proof-of-concept study to investigate the potential utility of juvenile pigs to serve as surrogates for children during preclinical PK testing of selected rifampin dosage forms. Pigs were surgically modified with jugular vein catheters that were externalized in the dorsal scapular region and connected to an automated blood sampling system (PigTurn-Culex-L). Commercially available rifampin capsules were administered to both 20 and 40 kg pigs to determine relevant PK parameters. Orally disintegrating tablet formulations of rifampin were also developed and administered to 20 kg pigs. Plasma samples were prepared from whole blood by centrifugation and analyzed for rifampin content by liquid chromatography-tandem mass spectrometry. Porcine PK parameters were determined from the resultant plasma-concentration time profiles and contrasted with published rifampin PK data in human adults and children. Results indicated significant similarities in dose-normalized absorption and elimination parameters between pigs and humans. Moreover, ontogenic changes observed in porcine PK parameters were consistent with ontogenic changes reported for human PK. These results demonstrate the potential utility of the juvenile porcine model for predicting human pediatric PK for rifampin. Furthermore, utilization of juvenile pigs during formulation testing may provide an alternative approach to expedite reformulation efforts during pediatric drug development.

Integrating drug permeability with dissolution profile to develop IVIVC

In this review article, three different approaches to predict in vivo oral absorption based on the in vitro data of drug permeability, solubility and dissolution were introduced. At the drug discovery stage, the absorption potential of each candidate is most important to select better compounds for further development. The concept of maximum absorbable dose is applied widely, not only to evaluate the absorption potential but also to elucidate the rate-limiting process of oral absorption that helps us to understand the cause of poor absorption. To integrate the permeability of the drug with its dissolution profile, two different approaches, in vitro dissolution/permeation system (D/P system) and in silico model and simulation method, are proposed. In the D/P system, by mimicking the in vivo process of drug absorption, the permeated amount of drugs, that is the total output of dissolution and permeation processes, are correlated with the fraction absorbed in human (F(a)). This system is powerful for evaluating the improved absorption by various formulations and the effect of food intake. On the other hand, in the model and simulation approach, an intrinsic dissolution parameter of drug particle, z, was extracted from the small scale in vitro test and the process of intestinal absorption was re-constructed in silico by incorporating the physiological parameters in human. The effective use of these approaches for the development of oral drug products is discussed through various case studies.

Predicting the oral absorption of a poorly soluble, poorly permeable weak base using biorelevant dissolution and transfer model tests coupled with a physiologically based pharmacokinetic model

For predicting food effects and simulating plasma profiles of poorly soluble drugs, physiologically based pharmacokinetic models have become a widely accepted tool in academia and the pharmaceutical industry. Up till now, however, simulations appearing in the open literature have mainly focused on BCS class II compounds, and many of these simulations tend to have more of a "retrospective" than a prognostic, predictive character. In this work, investigations on the absorption of a weakly basic BCS class IV drug, "Compound A", were performed. The objective was to predict the plasma profiles of an immediate release (IR) formulation of Compound A in the fasted and fed state. For this purpose, in vitro biorelevant dissolution tests and transfer model experiments were conducted. Dissolution and precipitation kinetics were then combined with in vivo post-absorptive disposition parameters using STELLA® software. As Compound A not only exhibits poor solubility but also poor permeability, a previously developed STELLA® model was revised to accommodate the less than optimal permeability characteristics as well as precipitation of the drug in the fasted state small intestine. Permeability restrictions were introduced into the model using an absorption rate constant calculated from the Caco-2 permeability value of Compound A, the effective intestinal surface area and appropriate intestinal fluid volumes. The results show that biorelevant dissolution tests are a helpful tool to predict food effects of Compound A qualitatively. However, the plasma profiles of Compound A could only be predicted quantitatively when the results of biorelevant dissolution test were coupled with the newly developed PBPK model.

BioDMET: a physiologically based pharmacokinetic simulation tool for assessing proposed solutions to complex biological problems

We developed a detailed, whole-body physiologically based pharmacokinetic (PBPK) modeling tool for calculating the distribution of pharmaceutical agents in the various tissues and organs of a human or animal as a function of time. Ordinary differential equations (ODEs) represent the circulation of body fluids through organs and tissues at the macroscopic level, and the biological transport mechanisms and biotransformations within cells and their organelles at the molecular scale. Each major organ in the body is modeled as composed of one or more tissues. Tissues are made up of cells and fluid spaces. The model accounts for the circulation of arterial and venous blood as well as lymph. Since its development was fueled by the need to accurately predict the pharmacokinetic properties of imaging agents, BioDMET is more complex than most PBPK models. The anatomical details of the model are important for the imaging simulation endpoints. Model complexity has also been crucial for quickly adapting the tool to different problems without the need to generate a new model for every problem. When simpler models are preferred, the non-critical compartments can be dynamically collapsed to reduce unnecessary complexity. BioDMET has been used for imaging feasibility calculations in oncology, neurology, cardiology, and diabetes. For this purpose, the time concentration data generated by the model is inputted into a physics-based image simulator to establish imageability criteria. These are then used to define agent and physiology property ranges required for successful imaging. BioDMET has lately been adapted to aid the development of antimicrobial therapeutics. Given a range of built-in features and its inherent flexibility to customization, the model can be used to study a variety of pharmacokinetic and pharmacodynamic problems such as the effects of inter-individual differences and disease-states on drug pharmacokinetics and pharmacodynamics, dosing optimization, and inter-species scaling. While developing a tool to aid imaging agent and drug development, we aimed at accelerating the acceptance and broad use of PBPK modeling by providing a free mechanistic PBPK software that is user friendly, easy to adapt to a wide range of problems even by non-programmers, provided with ready-to-use parameterized models and benchmarking data collected from the peer-reviewed literature.

Prediction of pharmacokinetic parameters

In silico tools specifically developed for prediction of pharmacokinetic parameters are of particular interest to pharmaceutical industry because of the high potential of discarding inappropriate molecules during an early stage of drug development itself with consequent saving of vital resources and valuable time. The ultimate goal of the in silico models of absorption, distribution, metabolism, and excretion (ADME) properties is the accurate prediction of the in vivo pharmacokinetics of a potential drug molecule in man, whilst it exists only as a virtual structure. Various types of in silico models developed for successful prediction of the ADME parameters like oral absorption, bioavailability, plasma protein binding, tissue distribution, clearance, half-life, etc. have been briefly described in this chapter.

Human tissue in the evaluation of safety and efficacy of new medicines: a viable alternative to animal models?

The pharma Industry's ability to develop safe and effective new drugs to market is in serious decline. Arguably, a major contributor to this is the Industry's extensive reliance on nonhuman biology-based test methods to determine potential safety and efficacy, objective analysis of which reveals poor predictive value. An obvious alternative approach is to use human-based tests, but only if they are available, practical, and effective. While in vivo (phase 0 microdosing with high sensitivity mass spectroscopy) and in silico (using established human biological data), technologies are increasingly being used, in vitro human approaches are more rarely employed. However, not only are increasingly sophisticated in vitro test methods now available or under development, but the basic ethically approved infrastructure through which human cells and tissues may be acquired is established. Along with clinical microdosing and in silico approaches, more effective access to and use of human cells and tissues in vitro provide exciting and potentially more effective opportunities for the assessment of safety and efficacy of new medicines.

Physiologically based pharmacokinetic modeling: methodology, applications, and limitations with a focus on its role in pediatric drug development

The concept of physiologically based pharmacokinetic (PBPK) modeling was introduced years ago, but it has not been practiced significantly. However, interest in and implementation of this modeling technique have grown, as evidenced by the increased number of publications in this field. This paper demonstrates briefly the methodology, applications, and limitations of PBPK modeling with special attention given to discuss the use of PBPK models in pediatric drug development and some examples described in detail. Although PBPK models do have some limitations, the potential benefit from PBPK modeling technique is huge. PBPK models can be applied to investigate drug pharmacokinetics under different physiological and pathological conditions or in different age groups, to support decision-making during drug discovery, to provide, perhaps most important, data that can save time and resources, especially in early drug development phases and in pediatric clinical trials, and potentially to help clinical trials become more “confirmatory” rather than “exploratory”.

WebPK, a web-based tool for custom pharmacokinetic simulation

Drug bioavailability is a major failing point of new pharmaceuticals i.e. drugs fail to reach their target or fail to stay there long enough for therapeutic effect. Compounding this issue, significant variability exists between patients and how they metabolize and distribute a drug. We present WebPK, a web-based tool for simulation of custom pharmacokinetic models. Model parameters can be entered manually or uploaded as a file. Simulation computations are performed on the server side, and thus require minimal client resources, which makes WebPK suitable for mobile devices. Time series biodistribution data are returned to the user in graphical and numerical form for quick interpretation or archiving. Results generated from WebPK are consistent with previously published pharmacokinetic models. This work is expected to provide physicians with access to easy simulation of patient pharmacokinetic profiles, which will allow for the prescription of more efficient and personalized drug regimens. URL: http://webpk.bme.gatech.edu.

Sensitivity and proportionality assessment of metabolites from microdose to high dose in rats using LC-MS/MS

BACKGROUND

The objective of this study was to evaluate the sensitivity requirement for LC-MS/MS as an analytical tool to characterize metabolites in plasma and urine at microdoses in rats and to investigate proportionality of metabolite exposure from a microdose of 1.67 µg/kg to a high dose of 5000 µg/kg for atorvastatin, ofloxacin, omeprazole and tamoxifen.

RESULTS

Only the glucuronide metabolite of ofloxacin, the hydroxylation metabolite of omeprazole and the hydration metabolite of tamoxifen were characterized in rat plasma at microdose by LC-MS/MS. The exposure of detected metabolites of omeprazole and tamoxifen appeared to increase in a nonproportional manner with increasing doses. Exposure of ortho- and para-hydroxyatorvastatin, but not atorvastatin and lactone, increased proportionally with increasing doses.

CONCLUSION

LC-MS/MS has demonstrated its usefulness for detecting and characterizing the major metabolites in plasma and urine at microdosing levels in rats. The exposure of metabolites at microdose could not simply be used to predict their exposure at higher doses.

A new definition of pharmaceutical quality: assembly of a risk simulation platform to investigate the impact of manufacturing/product variability on clinical performance

The absence of a unanimous, industry-specific definition of quality is, to a certain degree, impeding the progress of ongoing efforts to "modernize" the pharmaceutical industry. This work was predicated on requests by Dr. Woodcock (FDA) to re-define pharmaceutical quality in terms of risk by linking production characteristics to clinical attributes. A risk simulation platform that integrates population statistics, drug delivery system characteristics, dosing guidelines, patient compliance estimates, production metrics, and pharmacokinetic, pharmacodynamic, and in vitro-in vivo correlation models to investigate the impact of manufacturing variability on clinical performance of a model extended-release theophylline solid oral dosage system was developed. Manufacturing was characterized by inter- and intra-batch content uniformity and dissolution variability metrics, while clinical performance was described by a probabilistic pharmacodynamic model that expressed the probability of inefficacy and toxicity as a function of plasma concentrations. Least-squares regression revealed that both patient compliance variables, percent of doses taken and dosing time variability, significantly impacted efficacy and toxicity. Additionally, intra-batch content uniformity variability elicited a significant change in risk scores for the two adverse events and, therefore, was identified as a critical quality attribute. The proposed methodology demonstrates that pharmaceutical quality can be recast to explicitly reflect clinical performance.