Nigel J. Waters

TREND ANALYSIS OF A DATABASE OF INTRAVENOUS PHARMACOKINETIC PARAMETERS IN HUMANS FOR 670 DRUG COMPOUNDS

We present herein a compilation and trend analysis of human i.v. pharmacokinetic data on 670 drugs representing, to our knowledge, the largest publicly available set of human clinical pharmacokinetic data. This data set provides the drug metabolism scientist with a robust and accurate resource suitable for a number of applications, including in silico modeling, in vitro-in vivo scaling, and physiologically based pharmacokinetic approaches. Clearance, volume of distribution at steady state, mean residence time, and terminal phase half-life were obtained or derived from original references exclusively from studies utilizing i.v. administration. Plasma protein binding data were collected from other sources to supplement these pharmacokinetic data. These parameters were analyzed concurrently with a range of simple physicochemical descriptors, and resultant trends and patterns within the data are presented. Our findings with this much expanded data set were consistent with earlier described notions of trends between physicochemical properties and pharmacokinetic behavior. These observations and analyses, along with the large database of human pharmacokinetic data, should enable future efforts aimed toward developing quantitative structure-pharmacokinetic relationships and improving our understanding of the relationship between fundamental chemical characteristics and drug disposition.

Identification of NVP-TNKS656: The Use of Structure-Efficiency Relationships To Generate a Highly Potent, Selective, and Orally Active Tankyrase Inhibitor.

Tankyrase 1 and 2 have been shown to be redundant, druggable nodes in the Wnt pathway. As such, there has been intense interest in developing agents suitable for modulating the Wnt pathway in vivo by targeting this enzyme pair. By utilizing a combination of structure-based design and LipE-based structure efficiency relationships, the core of XAV939 was optimized into a more stable, more efficient, but less potent dihydropyran motif 7. This core was combined with elements of screening hits 2, 19, and 33 and resulted in highly potent, selective tankyrase inhibitors that are novel three pocket binders. NVP-TNKS656 (43) was identified as an orally active antagonist of Wnt pathway activity in the MMTV-Wnt1 mouse xenograft model. With an enthalpy-driven thermodynamic signature of binding, highly favorable physicochemical properties, and high lipophilic efficiency, NVP-TNKS656 is a novel tankyrase inhibitor that is well suited for further in vivo validation studies.

In Silico Prediction of Volume of Distribution in Human Using Linear and Nonlinear Models on a 669 Compound Data Set

The prediction of human pharmacokinetics early in the drug discovery cycle has become of paramount importance, aiding candidate selection and benefit-risk assessment. We present herein computational models to predict human volume of distribution at steady state (VD(ss)) entirely from in silico structural descriptors. Using both linear and nonlinear statistical techniques, partial least-squares (PLS), and random forest (RF) modeling, a data set of human VD(ss) values for 669 drug compounds recently published ( Drug Metab. Disp. 2008 , 36 , 1385 - 1405 ) was explored. Descriptors covering 2D and 3D molecular topology, electronics, and physical properties were calculated using MOE and Volsurf+. Model evaluation was accomplished using a leave-class-out approach on nine therapeutic or structural classes. The models were assessed using an external test set of 29 additional compounds. Our analysis generated models, both via a single method or consensus which were able to predict human VD(ss) within geometric mean 2-fold error, a predictive accuracy considered good even for more resource-intensive approaches such as those requiring data generated from studies in multiple animal species.

Integrated in Vitro Analysis for the in Vivo Prediction of Cytochrome P450-Mediated Drug-Drug Interactions

Unbound IC50 (IC50,u) values of 15 drugs were determined in eight recombinantly expressed human cytochromes P450 (P450s) and human hepatocytes, and the data were used to simulate clinical area under the plasma concentration-time curve changes (δAUC) on coadministration with prototypic CYP2D6 substrates. Significant differences in IC50,u values between enzyme sources were observed for quinidine (0.02 μM in recombinant CYP2D6 versus 0.5 μM in hepatocytes) and propafenone (0.02 versus 4.1 μM). The relative contribution of individual P450s toward the oxidative metabolism of clinical probes desipramine, imipramine, tolterodine, propranolol, and metoprolol was estimated via determinations of intrinsic clearance using recombinant P450s (rP450s). Simulated δAUC were compared with those observed in vivo via the ratios of unbound inhibitor concentration at the entrance to the liver to inhibition constants determined against rP450s ([I]in,u/Ki) and incorporating parallel substrate elimination pathways. For this dataset, there were 20% false negatives (observed δAUC ≥ 2, predicted δAUC < 2), 77% correct predictions, and 3% false positives. Thus, the [I]in,u/Ki approach appears relatively successful at estimating the degree of clinical interactions and can be incorporated into drug discovery strategies. Using a Simcyp ADME (absorption, metabolism, distribution, elimination) simulator (Simcyp Ltd., Sheffield, UK), there were 3% false negatives, 94% correct simulations, and 3% false positives. False-negative predictions were rationalized as a result of mechanism-based inhibition, production of inhibitory metabolites, and/or hepatic uptake. Integrating inhibition and reaction phenotyping data from automated rP450 screens have shown applicability to predict the occurrence and degree of in vivo drug-drug interactions, and such data may identify the clinical consequences for candidate drugs as both “perpetrators” and “victims” of P450-mediated interactions.

Novel Oxindole Sulfonamides and Sulfamides: EPZ031686, the First Orally Bioavailable Small Molecule SMYD3 Inhibitor.

SMYD3 has been implicated in a range of cancers; however, until now no potent selective small molecule inhibitors have been available for target validation studies. A novel oxindole series of SMYD3 inhibitors was identified through screening of the Epizyme proprietary histone methyltransferase-biased library. Potency optimization afforded two tool compounds, sulfonamide EPZ031686 and sulfamide EPZ030456, with cellular potency at a level sufficient to probe the in vitro biology of SMYD3 inhibition. EPZ031686 shows good bioavailability following oral dosing in mice making it a suitable tool for potential in vivo target validation studies.

Structure and Property Guided Design in the Identification of PRMT5 Tool Compound EPZ015666

The recent publication of a potent and selective inhibitor of protein methyltransferase 5 (PRMT5) provides the scientific community with in vivo-active tool compound EPZ015666 (GSK3235025) to probe the underlying pharmacology of this key enzyme. Herein, we report the design and optimization strategies employed on an initial hit compound with poor in vitro clearance to yield in vivo tool compound EPZ015666 and an additional potent in vitro tool molecule EPZ015866 (GSK3203591).

Use of the Øie-Tozer Model in Understanding Mechanisms and Determinants of Drug Distribution

Volume of distribution (VD) is a key pharmacokinetic property that together with clearance determines the half-life or residence time of drug in the body. It is commonly expressed as steady-state volume of distribution VDss with a physiological basis for its understanding developed by Øie and Tozer in 1979. The Øie-Tozer equation uses terms for plasma protein binding (fup), tissue binding (fut), and the extravascular/intravascular ratio of albumin as well as constants for the volumes of plasma, extracellular fluid, and tissue. We explored this model using a data set of 553 drugs for which VDss and plasma protein binding were available in humans. Eighteen percent of cases (102 compounds) did not obey the Øie-Tozer model, with the rearranged equation giving an aberrant fut value (fut < 0 or fut > 1), in particular for compounds with VDss < 0.6 l/kg and fup > 0.1. Further analysis of this group of compounds revealed patterns in physicochemical attributes with a high proportion exemplified by logP less than 0 (i.e., very hydrophilic), polar surface area >150 Å2, and a difference between logP and logD >2.5. In addition there was a high representation of certain drug classes including anti-infectives as well as neuromuscular blockers and contrast agents. The majority of compounds were also found to have literature evidence, implicating active transport processes in their disposition. This analysis provides some important insights for pharmacokinetic optimization in this particular chemical space, as well as in the application of the Øie-Tozer model for predicting volume of distribution in humans.

Structure–Efficiency Relationship of [1,2,4]Triazol-3-ylamines as Novel Nicotinamide Isosteres that Inhibit Tankyrases

Tankyrases 1 and 2 are members of the poly(ADP-ribose) polymerase (PARP) family of enzymes that modulate Wnt pathway signaling. While amide- and lactam-based nicotinamide mimetics that inhibit tankyrase activity, such as XAV939, are well-known, herein we report the discovery and evaluation of a novel nicotinamide isostere that demonstrates selectivity over other PARP family members. We demonstrate the utilization of lipophilic efficiency-based structure-efficiency relationships (SER) to rapidly drive the evaluation of this series. These efforts led to a series of selective, cell-active compounds with solubility, physicochemical, and in vitro properties suitable for further optimization.

Physiologically Based Pharmacokinetic Modeling in Pediatric Oncology Drug Development

Childhood cancer represents more than 100 rare and ultra-rare diseases, with an estimated 12,400 new cases diagnosed each year in the United States. As such, this much smaller patient population has led to pediatric oncology drug development lagging behind that for adult cancers. Developing drugs for pediatric malignancies also brings with it a number of unique trial design considerations, including flexible enrollment approaches, age-appropriate formulation, acceptable sampling schedules, and balancing the need for age-stratified dosing regimens, given the smaller patient populations. The regulatory landscape for pediatric pharmacotherapy has evolved with U.S. Food and Drug Administration (FDA) legislation such as the 2012 FDA Safety and Innovation Act. In parallel, regulatory authorities have recommended the application of physiologically based pharmacokinetic (PBPK) modeling, for example, in the recently issued FDA Strategic Plan for Accelerating the Development of Therapies for Pediatric Rare Diseases. PBPK modeling provides a quantitative and systems-based framework that allows the effects of intrinsic and extrinsic factors on drug exposure to be modeled in a mechanistic fashion. The application of PBPK modeling in drug development for pediatric cancers is relatively nascent, with several retrospective analyses of cytotoxic therapies, and latterly for targeted agents such as obatoclax and imatinib. More recently, we have employed PBPK modeling in a prospective manner to inform the first pediatric trials of pinometostat and tazemetostat in genetically defined populations (mixed lineage leukemia–rearranged and integrase interactor-1–deficient sarcomas, respectively). In this review, we evaluate the application of PBPK modeling in pediatric cancer drug development and discuss the important challenges that lie ahead in this field.

Species differences in metabolism of EPZ015666, an oxetane-containing protein arginine methyltransferase-5 (PRMT5) inhibitor

Abstract 1. Metabolite profiling and identification studies were conducted to understand the cross-species differences in the metabolic clearance of EPZ015666, a first-in-class protein arginine methyltransferase-5 (PRMT5) inhibitor, with anti-proliferative effects in preclinical models of Mantle Cell Lymphoma. EPZ015666 exhibited low clearance in human, mouse and rat liver microsomes, in part by introduction of a 3-substituted oxetane ring on the molecule. In contrast, a higher clearance was observed in dog liver microsomes (DLM) that translated to a higher in vivo clearance in dog compared with rodent. 2. Structure elucidation via high resolution, accurate mass LC-MSn revealed that the prominent metabolites of EPZ015666 were present in hepatocytes from all species, with the highest turnover rate in dogs. M1 and M2 resulted from oxidative oxetane ring scission, whereas M3 resulted from loss of the oxetane ring via an N-dealkylation reaction. 3. The formation of M1 and M2 in DLM was significantly abrogated in the presence of the specific CYP2D inhibitor, quinidine, and to a lesser extent by the CYP3A inhibitor, ketoconazole, corroborating data from human recombinant isozymes. 4. Our data indicate a marked species difference in the metabolism of the PRMT5 inhibitor EPZ015666, with oxetane ring scission the predominant metabolic pathway in dog mediated largely by CYP2D.