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.

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.

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.

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.

Rapid Method To Determine Intracellular Drug Concentrations in Cellular Uptake Assays: Application to Metformin in Organic Cation Transporter 1-Transfected Human Embryonic Kidney 293 Cells.

Because of the importance of intracellular unbound drug concentrations in the prediction of in vivo concentrations that are determinants of drug efficacy and toxicity, a number of assays have been developed to assess in vitro unbound concentrations of drugs. Here we present a rapid method to determine the intracellular unbound drug concentrations in cultured cells, and we apply the method along with a mechanistic model to predict concentrations of metformin in subcellular compartments of stably transfected human embryonic kidney 293 (HEK293) cells. Intracellular space (ICS) was calculated by subtracting the [(3)H]-inulin distribution volume (extracellular space, ECS) from the [(14)C]-urea distribution volume (total water space, TWS). Values obtained for intracellular space (mean ± S.E.M.; µl/10(6) cells) of monolayers of HEK cells (HEK-empty vector [EV]) and cells overexpressing human organic cation transporter 1 (HEK-OCT1), 1.21± 0.07 and 1.25±0.06, respectively, were used to determine the intracellular metformin concentrations. After incubation of the cells with 5 µM metformin, the intracellular concentrations were 26.4 ± 7.8 µM and 268 ± 11.0 µM, respectively, in HEK-EV and HEK-OCT1. In addition, intracellular metformin concentrations were lower in high K(+) buffer (140 mM KCl) compared with normal K(+) buffer (5.4 mM KCl) in HEK-OCT1 cells (54.8 ± 3.8 µM and 198.1 ± 11.2 µM, respectively; P < 0.05). Our mechanistic model suggests that, depending on the credible range of assumed physiologic values, the positively charged metformin accumulates to particularly high levels in endoplasmic reticulum and/or mitochondria. This method together with the computational model can be used to determine intracellular unbound concentrations and to predict subcellular accumulation of drugs in other complex systems such as primary cells.

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.

PF-1355, a mechanism-based myeloperoxidase inhibitor, prevents immune complex vasculitis and anti-glomerular basement membrane glomerulonephritis.

Small vessel vasculitis is a life-threatening condition and patients typically present with renal and pulmonary injury. Disease pathogenesis is associated with neutrophil accumulation, activation, and oxidative damage, the latter being driven in large part by myeloperoxidase (MPO), which generates hypochlorous acid among other oxidants. MPO has been associated with vasculitis, disseminated vascular inflammation typically involving pulmonary and renal microvasculature and often resulting in critical consequences. MPO contributes to vascular injury by 1) catabolizing nitric oxide, impairing vasomotor function; 2) causing oxidative damage to lipoproteins and endothelial cells, leading to atherosclerosis; and 3) stimulating formation of neutrophil extracellular traps, resulting in vessel occlusion and thrombosis. Here we report a selective 2-thiouracil mechanism-based MPO inhibitor (PF-1355 [2-(6-(2,5-dimethoxyphenyl)-4-oxo-2-thioxo-3,4-dihydropyrimidin-1(2H)-yl)acetamide) and demonstrate that MPO is a critical mediator of vasculitis in mouse disease models. A pharmacokinetic/pharmacodynamic response model of PF-1355 exposure in relation with MPO activity was derived from mouse peritonitis. The contribution of MPO activity to vasculitis was then examined in an immune complex model of pulmonary disease. Oral administration of PF-1355 reduced plasma MPO activity, vascular edema, neutrophil recruitment, and elevated circulating cytokines. In a model of anti-glomerular basement membrane disease, formerly known as Goodpasture disease, albuminuria and chronic renal dysfunction were completely suppressed by PF-1355 treatment. This study shows that MPO activity is critical in driving immune complex vasculitis and provides confidence in testing the hypothesis that MPO inhibition will provide benefit in treating human vasculitic diseases.

Physiologically based pharmacokinetic prediction of telmisartan in human.

A previously developed physiologically based pharmacokinetic model for hepatic transporter substrates was extended to an organic anion transporting polypeptide substrate, telmisartan. Predictions used in vitro data from sandwich culture human hepatocyte and human liver microsome assays. We have developed a novel method to calibrate partition coefficients (Kps) between nonliver tissues and plasma on the basis of published human positron emission tomography (PET) data to decrease the uncertainty in tissue distribution introduced by in silico-predicted Kps. With in vitro data-predicted hepatic clearances, published empirical scaling factors, and PET-calibrated Kps, the model could accurately recapitulate telmisartan pharmacokinetic (PK) behavior before 2.5 hours. Reasonable predictions also depend on having a model structure that can adequately describe the drug disposition pathways. We showed that the elimination phase (2.5-12 hours) of telmisartan PK could be more accurately recapitulated when enterohepatic recirculation of parent compound derived from intestinal deconjugation of glucuronide metabolite was incorporated into the model. This study demonstrated the usefulness of the previously proposed physiologically based modeling approach for purely predictive intravenous PK simulation and identified additional biologic processes that can be important in prediction.

Toward a unified model of passive drug permeation II: the physiochemical determinants of unbound tissue distribution with applications to the design of hepatoselective glucokinase activators.

In this work, we leverage a mathematical model of the underlying physiochemical properties of tissues and physicochemical properties of molecules to support the development of hepatoselective glucokinase activators. Passive distribution is modeled via a Fick-Nernst-Planck approach, using in vitro experimental data to estimate the permeability of both ionized and neutral species. The model accounts for pH and electrochemical potential across cellular membranes, ionization according to Henderson-Hasselbalch, passive permeation of the neutral species using Fick's law, and passive permeation of the ionized species using the Nernst-Planck equation. The mathematical model of the physiochemical system allows derivation of a single set of parameters governing the distribution of drug molecules across multiple conditions both in vitro and in vivo. A case study using this approach in the development of hepatoselective glucokinase activators via organic anion-transporting polypeptide-mediated hepatic uptake and impaired passive distribution to the pancreas is described. The results for these molecules indicate the permeability penalty of the ionized form is offset by its relative abundance, leading to passive pancreatic exclusion according to the Nernst-Planck extension of Fickian passive permeation. Generally, this model serves as a useful construct for drug discovery scientists to understand subcellular exposure of acids or bases using specific physiochemical properties.

A "middle-out" approach to human pharmacokinetic predictions for OATP substrates using physiologically-based pharmacokinetic modeling.

Physiologically based pharmacokinetic (PBPK) models provide a framework useful for generating credible human pharmacokinetic predictions from data available at the earliest, preclinical stages of pharmaceutical research. With this approach, the pharmacokinetic implications of in vitro data are contextualized via scaling according to independent physiological information. However, in many cases these models also require model-based estimation of additional empirical scaling factors (SFs) in order to accurately recapitulate known human pharmacokinetic behavior. While this practice clearly improves data characterization, the introduction of empirically derived SFs may belie the extrapolative power commonly attributed to PBPK. This is particularly true when such SFs are compound dependent and/or when there are issues with regard to identifiability. As such, when empirically-derived SFs are necessary, a critical evaluation of parameter estimation and model structure are prudent. In this study, we applied a global optimization method to support model-based estimation of a single set of empirical SFs from intravenous clinical data on seven OATP substrates within the context of a previously published PBPK model as well as a revised PBPK model. The revised model with experimentally measured unbound fraction in liver, permeability between liver compartments, and permeability limited distribution to selected tissues improved data characterization. We utilized large-sample approximation and resampling approaches to estimate confidence intervals for the revised model in support of forward predictions that reflect the derived uncertainty. This work illustrates an objective approach to estimating empirically-derived SFs, systematically refining PBPK model performance and conveying the associated confidence in subsequent forward predictions.

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.

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.

Discovery and evaluation of pyrazolo[1,5-a]pyrimidines as neuropeptide Y1 receptor antagonists.

A novel series of pyrazolo[1,5-a]pyrimidine derivatives was synthesized and evaluated as NPY Y1R antagonists. High binding affinity and selectivity were achieved with C3 trisubstituted aryl groups and C7 substituted 2-(tetrahydro-2H-pyran-4-ylamino)ethylamine moieties. Efforts to find close analogs with low plasma clearance in the rat and minimal p-glycoprotein efflux in the mouse were unsuccessful. Compound 2f (CP-671906) inhibited NPY-induced increases in blood pressure and food intake after iv and icv administration, respectively, in Sprague-Dawley (SD) rat models. Oral administration of compound 2f resulted in a modest, but statistically significant, reduction in food intake in a Wistar rat model of feeding behavior. Small inhibitions of food intake were also observed in an overnight fasting/refeeding model in SD rats. These data suggest a potential role for Y1R in the regulation of food intake in rodents.

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.

Design and synthesis of orally-active and selective azaindane 5HT2c agonist for the treatment of obesity.

Based on our original pyrazine hit, CP-0809101, novel conformationally-restricted 5HT2c receptor agonists with 2-piperazin-azaindane scaffold were designed. Synthesis and structure-activity relationship (SAR) studies are described with emphasis on optimization of the selectivity against 5HT2a and 5HT2b receptors with excellent 2c potency. Orally-active and selective compounds were identified with dose-responsive in vivo efficacy in our pre-clinical food intake model.

C-Aryl glycoside inhibitors of SGLT2: Exploration of sugar modifications including C-5 spirocyclization.

Modifications to the sugar portion of C-aryl glycoside sodium glucose transporter 2 (SGLT2) inhibitors were explored, including systematic deletion and modification of each of the glycoside hydroxyl groups. Based on results showing activity to be quite tolerant of structural change at the C-5 position, a series of novel C-5 spiro analogues was prepared. Some of these analogues exhibit low nanomolar potency versus SGLT2 and promote urinary glucose excretion (UGE) in rats. However, due to sub-optimal pharmacokinetic parameters (in particular half-life), predicted human doses did not meet criteria for further advancement.

Discovery of N-benzyl-2-[(4S)-4-(1H-indol-3-ylmethyl)-5-oxo-1-phenyl-4,5-dihydro-6H-[1,2,4]triazolo[4,3-a][1,5]benzodiazepin-6-yl]-N-isopropylacetamide, an orally active, gut-selective CCK1 receptor agonist for the potential treatment of obesity.

We describe the design, synthesis, and structure-activity relationships of triazolobenzodiazepinone CCK1 receptor agonists. Analogs in this series demonstrate potent agonist activity as measured by in vitro and in vivo assays for CCK1 agonism. Our efforts resulted in the identification of compound 4a which significantly reduced food intake with minimal systemic exposure in rodents.

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.