Quantitative Model-Based Assessment of Multiple Sickle Cell Disease Therapeutic Approaches Alone and in Combination.

Three sickle cell disease (SCD) treatment strategies, stabilizing oxygenated hemoglobin (oxyHb), lowering 2,3-BPG, and inducing fetal hemoglobin (HbF) expression aim to prevent red blood cell (RBC) sickling by reducing tense-state sickle hemoglobin that contributes to polymer formation. Induction of 30% HbF is seen as the gold standard because 30% endogenous expression is associated with a lack of symptoms. However, the level of intervention required to achieve equivalent polymerization protection by the other strategies is uncertain, and there is little understanding of how these approaches could work in combination. We sought to develop an oxygen saturation model that could assess polymerization protection of all three approaches alone or in combination by extending the Monod-Wymann-Changeux model to include additional mechanisms. Applying the model to monotherapies suggests 51% sickle hemoglobin (HbS) occupancy with an oxyHb stabilizer or lowering RBC 2,3 BPG concentrations to 1.8 mM would produce comparable polymerization protection as 30% HbF. The model predictions are consistent with observed clinical response to the oxyHb stabilizer voxelotor and the 2,3-BPG reducer etavopivat. The model also suggests combination therapy will have added benefit in the case of dose limitations, as is the case for voxelotor, which the model predicts could be combined with 20% HbF or 2,3-BPG reduction to 3.75 mM to reach equivalent protection as 30% HbF. The proposed model represents a unified framework that is useful in supporting decisions in preclinical and early clinical development and capable of evolving with clinical experience to gain new and increasingly confident insights into treatment strategies for SCD.

Relationship of binding-site occupancy, transthyretin stabilisation and disease modification in patients with tafamidis-treated transthyretin amyloid cardiomyopathy.

BACKGROUND: Tafamidis inhibits progression of transthyretin (TTR) amyloid cardiomyopathy (ATTR-CM) by binding TTR tetramer and inhibiting dissociation to monomers capable of denaturation and deposition in cardiac tissue. While the phase 3 ATTR-ACT trial demonstrated the efficacy of tafamidis, the degree to which the approved dose captures the full potential of the mechanism has yet to be assessed. METHODS: We developed a model of dynamic TTR concentrations in plasma to relate TTR occupancy by tafamidis to TTR stabilisation. We then developed population pharmacokinetic-pharmacodynamic models to characterise the relationship between stabilisation and measures of disease progression. RESULTS: Modelling individual patient data of tafamidis exposure and increased plasma TTR confirmed that single-site binding provides complete tetramer stabilisation in vivo. The approved dose was estimated to reduce unbound TTR tetramer by 92%, and was associated with 53%, 56% and 49% decreases in the rate of change in NT-proBNP, KCCQ-OS, and six-minute walk test disease progression measures, respectively. Simulating complete TTR stabilisation predicted slightly greater reductions of 58%, 61% and 54%, respectively. CONCLUSIONS: These findings support the value of TTR stabilisation as a clinically beneficial treatment option in ATTR-CM and the ability of tafamidis to realise nearly the full therapeutic benefit of this mechanism. CLINICALTRIALS.GOV IDENTIFIER: NCT01994889.

Unbound Brain-to-Plasma Partition Coefficient, Kp,uu,brain-a Game Changing Parameter for CNS Drug Discovery and Development.

PURPOSE: More than 15 years have passed since the first description of the unbound brain-to-plasma partition coefficient (Kp,uu,brain) by Prof. Margareta Hammarlund-Udenaes, which was enabled by advancements in experimental methodologies including cerebral microdialysis. Since then, growing knowledge and data continue to support the notion that the unbound (free) concentration of a drug at the site of action, such as the brain, is the driving force for pharmacological responses. Towards this end, Kp,uu,brain is the key parameter to obtain unbound brain concentrations from unbound plasma concentrations. METHODS: To understand the importance and impact of the Kp,uu,brain concept in contemporary drug discovery and development, a survey has been conducted amongst major pharmaceutical companies based in Europe and the USA. Here, we present the results from this survey which consisted of 47 questions addressing: 1) Background information of the companies, 2) Implementation, 3) Application areas, 4) Methodology, 5) Impact and 6) Future perspectives. RESULTS AND CONCLUSIONS: From the responses, it is clear that the majority of the companies (93%) has established a common understanding across disciplines of the concept and utility of Kp,uu,brain as compared to other parameters related to brain exposure. Adoption of the Kp,uu,brain concept has been mainly driven by individual scientists advocating its application in the various companies rather than by a top-down approach. Remarkably, 79% of all responders describe the portfolio impact of Kp,uu,brain implementation in their companies as 'game-changing'. Although most companies (74%) consider the current toolbox for Kp,uu,brain assessment and its validation satisfactory for drug discovery and early development, areas of improvement and future research to better understand human brain pharmacokinetics/pharmacodynamics translation have been identified.

Designing small molecules for therapeutic success: A contemporary perspective.

Successful small-molecule drug design requires a molecular target with inherent therapeutic potential and a molecule with the right properties to unlock its potential. Present-day drug design strategies have evolved to leave little room for improvement in drug-like properties. As a result, inadequate safety or efficacy associated with molecular targets now constitutes the primary cause of attrition in preclinical development through Phase II. This finding has led to a deeper focus on target selection. In this current reality, design tactics that enable rapid identification of risk-balanced clinical candidates, translation of clinical experience into meaningful differentiation strategies, and expansion of the druggable proteome represent significant levers by which drug designers can accelerate the discovery of the next generation of medicines.

Harnessing Preclinical Data as a Predictive Tool for Human Brain Tissue Targeting.

One of the objectives within the medicinal chemistry discipline is to design tissue targeting molecules. The objective of tissue specificity can be either to gain drug access to the compartment of interest (e.g., the CNS) for Neuroscience targets or to restrict drug access to the CNS for all other therapeutic areas. Both neuroscience and non-neuroscience therapeutic areas have struggled to quantitatively estimate brain penetration or the lack thereof with compounds that are substrates of efflux transport proteins such as P-glycoprotein (P-gp) and breast cancer resistant protein (BCRP) that are key components of the blood-brain barrier (BBB). It has been well established that drug candidates with high efflux ratios (ER) of these transporters have poor penetration into brain tissue. In the current work, we outline a parallel analysis to previously published models for the prediction of brain penetration that utilize an alternate MDR1-MDCK cell line as a better predictor of brain penetration and whether a correlation between in vitro, rodent data, non-human primate (NHP), and human in vivo brain penetration data could be established. Analysis of structural and physicochemical properties in conjunction with in vitro parameters and preclinical in vivo data has been highlighted in this manuscript as a continuation of the previously published work.

The advantages of describing covalent inhibitor in vitro potencies by IC50 at a fixed time point. IC50 determination of covalent inhibitors provides meaningful data to medicinal chemistry for SAR optimization.

Recent years have seen a resurgence in drug discovery efforts aimed at the identification of covalent inhibitors which has led to an explosion of literature reports in this area and most importantly new approved therapies. These reports and breakthroughs highlight the significant investments made across the industry in SAR campaigns to optimize inhibitors. The potency of covalent inhibitors is generally considered to be more accurately described by the time-independent kinetic parameter kinact/Ki rather than a by a simple IC50 since the latter is a time-dependent parameter. Enzyme substrate concentrations are an additional important factor to consider when attempting to translate parameters derived from enzymology experiments to phenotypic behavior in a physiologically relevant cell-based system. Theoretical and experimental investigations into the relationship between IC50, time, substrate concentration and Kinact/Ki provided us with an effective approach to provide meaningful data for SAR optimization. The data we generated for our JAK3 irreversible covalent inhibitor program using IC50 values provided by enzyme assays with long incubations (>1h) coupled with physiological substrate concentration provided the medicinal chemist with optimal information in a rapid and efficient manner. We further document the wide applicability of this method by applying it to other enzymes systems where we have run covalent inhibitor programs.

A Microfluidic Perfusion Platform for In Vitro Analysis of Drug Pharmacokinetic-Pharmacodynamic (PK-PD) Relationships.

Static in vitro cell culture studies cannot capture the dynamic concentration profiles of drugs, nutrients, and other factors that cells experience in physiological systems. This limits the confidence in the translational relevance of in vitro experiments and increases the reliance on empirical testing of exposure-response relationships and dose optimization in animal models during preclinical drug development, introducing additional challenges owing to species-specific differences in drug pharmacokinetics (PK) and pharmacodynamics (PD). Here, we describe the development of a microfluidic cell culture device that enables perfusion of cells under 2D or 3D culture conditions with temporally programmable concentration profiles. Proof-of-concept studies using doxorubicin and gemcitabine demonstrated the ability of the microfluidic PK-PD device to examine dose- and time-dependent effects of doxorubicin as well as schedule-dependent effects of doxorubicin and gemcitabine combination therapy on cell viability using both step-wise drug concentration profiles and species-specific (i.e., mouse, human) drug PK profiles. The results demonstrate the importance of including physiologically relevant dynamic drug exposure profiles during in vitro drug testing to more accurately mimic in vivo drug effects, thereby improving translatability across nonclinical studies and reducing the reliance on animal models during drug development.

A Physiologically Based in Silico Tool to Assess the Risk of Drug-Related Crystalluria.

Drug precipitation in the nephrons of the kidney can cause drug-induced crystal nephropathy (DICN). To aid mitigation of this risk in early drug discovery, we developed a physiologically based in silico model to predict DICN in rats, dogs, and humans. At a minimum, the likelihood of DICN is determined by the level of systemic exposure to the molecule, the molecule's physicochemical properties and the unique physiology of the kidney. Accordingly, the proposed model accounts for these properties in order to predict drug exposure relative to solubility along the nephron. Key physiological parameters of the kidney were codified in a manner consistent with previous reports. Quantitative structure-activity relationship models and in vitro assays were used to estimate drug-specific physicochemical inputs to the model. The proposed model was calibrated against urinary excretion data for 42 drugs, and the utility for DICN prediction is demonstrated through application to 20 additional drugs.

Dose Predictions for Drug Design.

The efficacious dose of a drug is perhaps the most holistic metric reflecting its therapeutic potential. Dose is predicted at many stages in drug discovery and development. Prior to the 1990s, dose prediction was limited to the drug "working" at a reasonable dose and dose regimen in an animal model. Through the early 2000s, dose predictions were generated at candidate nomination and then refined during clinical development. Currently, dose predictions can be made early in drug discovery to enable drug design. Dose predictions at this stage can identify critical drug properties for a viable dose regimen and provide clinically relevant context to lead optimization. In this paper, we give an overview of the opportunities and challenges associated with dose prediction for drug design. A number of general considerations, approaches, and case examples are discussed.

Theoretical Considerations for Direct Translation of Unbound Liver-to-Plasma Partition Coefficient from In Vitro to In Vivo.

There is considerable interest in developing methods to predict the asymmetric distribution of unbound drug into tissues. The liver is of particular interest due to the multitude of expressed transporters with potential implications for pharmacokinetics, pharmacodynamics, and toxicology. Empirical correlations of in vitro unbound hepatocyte-to-media partition coefficient (in vitro Kpuu) and in vivo unbound liver-to-plasma partition coefficient (in vivo Kpuu) have been reported without considering the theoretical aspects which might confound the interpretation of such observations. To understand the theoretical basis for the translation of Kpuu between in vitro and in vivo systems, we simulated in vitro hepatocyte and in vivo liver Kpuu values using mechanistic mathematical models of these systems. Theoretical comparisons of steady-state Kpuu between in vitro and in vivo systems were performed using liver models which assumed a number of segments ranging from one (i.e., a permeability-limited well-stirred model) to infinity (i.e., a permeability-limited parallel tube model). Using a five-segment model, the effect of zonal differences in metabolism was also explored in this context. The results across the range of examined models indicated that theoretical differences between in vitro and in vivo Kpuu estimates exist and are expected to increase with an increasing degree of extraction across the liver. However, differences were relatively small using what is perhaps the most physiologically relevant, permeability-limited parallel tube model, suggesting that direct correlations are reasonably valid and that the permeability-limited parallel tube model is perhaps the most appropriate physiologically based pharmacokinetic (PBPK) construct for supporting studies of this nature.

Modeling Exposure to Understand and Predict Kidney Injury.

Exposure is a critically important aspect to consider in the study and management of drug-induced kidney injury. Although blood concentrations of kidney toxicants often may provide a valid surrogate measure of kidney exposure, the kidney has several unique physiological and biochemical properties that lend themselves to accumulation or exclusion of some drugs at sites of toxicity. In such cases, an understanding of these pharmacokinetic mechanisms can be as important as understanding the underlying mechanisms of toxicity. Physiologically based pharmacokinetic models, which mathematically codify such mechanisms in a biologically plausible form, increasingly are being used for developing an understanding of pharmacokinetics across patient populations, drug-drug interactions, and pharmacokinetic-pharmacodynamic relationships. This perspective provides a review of the physiological and biochemical mechanisms as well as the physiochemical properties that theoretically could drive drug accumulation or exclusion within the kidney, along with examples in which these mechanisms have proven important in driving the manifestation of toxicity in vivo. In addition, an overview of the structure, applications, and limitations of existing kidney physiologically based pharmacokinetic models is provided. Finally, a perspective on gaps and associated challenges to such models in the field of toxicology is discussed briefly.

In Vitro-In Vivo Extrapolation of Key Transporter Activity at the Blood-Brain Barrier.

Understanding the quantitative implications of P-glycoprotein and breast cancer resistance protein efflux is a key hurdle in the design of effective, centrally acting or centrally restricted therapeutics. Previously, a comprehensive physiologically based pharmacokinetic model was developed to describe the in vivo unbound brain-to-plasma concentration ratio as a function of efflux activity measured in vitro. In the present work, the predictive utility of this framework was examined through application to in vitro and in vivo data generated on 133 unique compounds across three preclinical species. Two approaches were examined for the scaling of efflux activity to in vivo, namely relative expression as determined by independent proteomics measurements and relative activity as determined via fitting the in vivo neuropharmacokinetic data. The results with both approaches indicate that in vitro efflux data can be used to accurately predict the degree of brain penetration across species within the context of the proposed physiologically based pharmacokinetic framework.

Clearance in Drug Design.

Due to its implications for both dose level and frequency, clearance rate is one of the most important pharmacokinetic parameters to consider in the design of drug candidates. Clearance can be classified into three general categories, namely, metabolic transformation, renal excretion, and hepatobiliary excretion. Within each category, there are a host of biochemical and physiological mechanisms that ultimately determine the clearance rate. Physiochemical properties are often indicative of the rate-determining mechanism, with lipophilic molecules tending toward metabolism and hydrophilic, polar molecules tending toward passive or active excretion. Optimization of clearance requires recognition of the major clearance mechanisms and use of the most relevant in vitro and in vivo tools to develop structure-clearance relationships. The reliability of methods to detect and predict human clearance varies across mechanisms. While methods for metabolic and passive renal clearance have proven reasonably robust, there is a clear need for better tools to support the optimization of transporter-mediated clearance.

Quantitative Translational Analysis of Brain Kynurenic Acid Modulation via Irreversible Kynurenine Aminotransferase II Inhibition.

Kynurenic acid (KYNA) plays a significant role in maintaining normal brain function, and abnormalities in KYNA levels have been associated with various central nervous system disorders. Confirmation of its causality in human diseases requires safe and effective modulation of central KYNA levels in the clinic. The kynurenine aminotransferases (KAT) II enzyme represents an attractive target for pharmacologic modulation of central KYNA levels; however, KAT II and KYNA turnover kinetics, which could contribute to the duration of pharmacologic effect, have not been reported. In this study, the kinetics of central KYNA-lowering effect in rats and nonhuman primates (NHPs, Cynomolgus macaques) was investigated using multiple KAT II irreversible inhibitors as pharmacologic probes. Mechanistic pharmacokinetic-pharmacodynamic analysis of in vivo responses to irreversible inhibition quantitatively revealed that 1) KAT II turnover is relatively slow [16-76 hours' half-life (t1/2)], whereas KYNA is cleared more rapidly from the brain (<1 hour t1/2) in both rats and NHPs, 2) KAT II turnover is slower in NHPs than in rats (76 hours vs. 16 hours t1/2, respectively), and 3) the percent contribution of KAT II to KYNA formation is constant (∼80%) across rats and NHPs. Additionally, modeling results enabled establishment of in vitro-in vivo correlation for both enzyme turnover rates and drug potencies. In summary, quantitative translational analysis confirmed the feasibility of central KYNA modulation in humans. Model-based analysis, where system-specific properties and drug-specific properties are mechanistically separated from in vivo responses, enabled quantitative understanding of the KAT II-KYNA pathway, as well as assisted development of promising candidates to test KYNA hypothesis in humans.

A Study on Pharmacokinetics of Bosentan with Systems Modeling, Part 1: Translating Systemic Plasma Concentration to Liver Exposure in Healthy Subjects.

Understanding liver exposure of hepatic transporter substrates in clinical studies is often critical, as it typically governs pharmacodynamics, drug-drug interactions, and toxicity for certain drugs. However, this is a challenging task since there is currently no easy method to directly measure drug concentration in the human liver. Using bosentan as an example, we demonstrate a new approach to estimate liver exposure based on observed systemic pharmacokinetics from clinical studies using physiologically based pharmacokinetic modeling. The prediction was verified to be both accurate and precise using sensitivity analysis. For bosentan, the predicted pseudo steady-state unbound liver-to-unbound systemic plasma concentration ratio was 34.9 (95% confidence interval: 4.2, 50). Drug-drug interaction (i.e., CYP3A and CYP2B6 induction) and inhibition of hepatic transporters (i.e., bile salt export pump, multidrug resistance-associated proteins, and sodium-taurocholate cotransporting polypeptide) were predicted based on the estimated unbound liver tissue or plasma concentrations. With further validation and refinement, we conclude that this approach may serve to predict human liver exposure and complement other methods involving tissue biopsy and imaging.

Relevance of Half-Life in Drug Design.

Drug half-life has important implications for dosing regimen and peak-to-trough ratio at the steady state. A half-life of 12-48 h is generally ideal for once daily dosing of oral drugs. If the half-life is too short, it may require more frequent dosing in order to maintain desired exposures and avoid unnecessarily high peak concentrations. This may pose challenges to achieving optimal efficacy, safety, and patient compliance. If the half-life is too long, the time over which accumulation and subsequent elimination occur may be prolonged. This may pose problems with managing adverse effects and the design of efficient clinical trials. Half-life is a key parameter for optimization in research and development. Structural modification to affect clearance, and to a lesser extent volume of distribution, is the preferred means of modulating half-life. An effective approach to half-life optimization requires an understanding of the many pitfalls associated with its estimation and interpretation.

In Vitro-In Vivo Extrapolation of Intestinal Availability for Carboxylesterase Substrates Using Portal Vein-Cannulated Monkey.

Prediction of intestinal availability (FaFg) of carboxylesterase (CES) substrates is of critical importance in designing oral prodrugs with optimal properties, projecting human pharmacokinetics and dose, and estimating drug-drug interaction potentials. A set of ester prodrugs were evaluated using in vitro permeability (parallel artificial membrane permeability assay and Madin-Darby canine kidney cell line-low efflux) and intestinal stability (intestine S9) assays, as well as in vivo portal vein-cannulated cynomolgus monkey. In vitro-in vivo extrapolation (IVIVE) of FaFg was developed with a number of modeling approaches, including a full physiologically based pharmacokinetic (PBPK) model as well as a simplified competitive-rate analytical solution. Both methods converged as in the PBPK simulations enterocyte blood flow behaved as a sink, a key assumption in the competitive-rate analysis. For this specific compound set, the straightforward analytical solution therefore can be used to generate in vivo predictions. Strong IVIVE of FaFg was observed for cynomolgus monkey with R2 of 0.71-0.93. The results suggested in vitro assays can be used to predict in vivo FaFg for CES substrates with high confidence.

Projecting ADME Behavior and Drug-Drug Interactions in Early Discovery and Development: Application of the Extended Clearance Classification System.

PURPOSE: To assess the utility of Extended Clearance Classification System (ECCS) in understanding absorption, distribution, metabolism, and elimination (ADME) attributes and enabling victim drug-drug interaction (DDI) predictions. METHODS: A database of 368 drugs with relevant ADME parameters, main metabolizing enzymes, uptake transporters, efflux transporters, and highest change in exposure (%AUC) in presence of inhibitors was developed using published literature. Drugs were characterized according to ECCS using ionization, molecular weight and estimated permeability. RESULTS: Analyses suggested that ECCS class 1A drugs are well absorbed and systemic clearance is determined by metabolism mediated by CYP2C, esterases, and UGTs. For class 1B drugs, oral absorption is high and the predominant clearance mechanism is hepatic uptake mediated by OATP transporters. High permeability neutral/basic drugs (class 2) showed high oral absorption, with metabolism mediated generally by CYP3A, CYP2D6 and UGTs as the predominant clearance mechanism. Class 3A/4 drugs showed moderate absorption with dominant renal clearance involving OAT/OCT2 transporters. Class 3B drugs showed low to moderate absorption with hepatic uptake (OATPs) and/or renal clearance as primary clearance mechanisms. The highest DDI risk is typically seen with class 2/1B/3B compounds manifested by inhibition of either CYP metabolism or active hepatic uptake. Class 2 showed a wider range in AUC change likely due to a variety of enzymes involved. DDI risk for class 3A/4 is small and associated with inhibition of renal transporters. CONCLUSIONS: ECCS provides a framework to project ADME profiles and further enables prediction of victim DDI liabilities in drug discovery and development.