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Understanding a drug's whole-body biodistribution and tumor targeting can provide important information regarding efficacy, safety, and dosing parameters. Current methods to evaluate biodistribution include in vivo imaging technologies like positron electron tomography and single-photon emission computed tomography or ex vivo quantitation of drug concentrations in tissues using autoradiography and standard biochemical assays. These methods use radioactive compounds or are cumbersome and do not give whole-body information. Here, for the first time, we show the utility of fluorescence molecular tomography (FMT) imaging to determine the biodistribution and targeting of an antibody–drug conjugate (ADC). An anti–5T4-antibody (5T4-Ab) and 5T4-ADC were conjugated with a near-infrared (NIR) fluorophore VivoTag 680XL (VT680). Both conjugated compounds were stable as determined by SEC-HPLC and plasma stability studies. Flow cytometry and fluorescence microscopy studies showed that VT680-conjugated 5T4-ADC specifically bound 5T4-expressing cells in vitro and also exhibited a similar cytotoxicity profile as the unconjugated 5T4-ADC. In vivo biodistribution and tumor targeting in an H1975 subcutaneous xenograft model demonstrated no significant differences between accumulation of VT680-conjugated 5T4-Ab or 5T4-ADC in either normal tissues or tumor. In addition, quantitation of heart signal from FMT imaging showed good correlation with the plasma pharmacokinetic profile suggesting that it (heart FMT imaging) may be a surrogate for plasma drug clearance. These results demonstrate that conjugation of VT680 to 5T4-Ab or 5T4-ADC does not change the behavior of native biologic, and FMT imaging can be a useful tool to understand biodistribution and tumor-targeting kinetics of antibodies, ADCs, and other biologics. Mol Cancer Ther; 15(10); 2530–40. ©2016 AACR.

Supplemental Figure 1: Standard curve of VT680 showing the 3-D quantitation and linearity by FMT imaging; Supplemental Figure 2: Evaluation of VT680 conjugated 5T4-Ab and 5T4-ADC; Supplemental Figure 3: Determination of antibody binding capacity (ABC) and receptor saturation in H1975 and MDA-MB-468 cells by flow cytometry; Supplemental Figure 4: Ex vivo FMT imaging showing the accumulation of 5T4-Ab-VT680, 5T4-ADC-VT680, Isotype control-Ab-VT680 and VT680 alone 48 h post-injection in tumor (A) and liver (B).

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Trastuzumab CRD Calculation Details

Description of common pharmacokinetic parameters used in the CRD calculations.

Dasatinib CRD Calculation Details

Vismodegib CRD Calculation Details

Purpose: The translation of nonclinical oncology studies is a subject of continuous debate. We propose that translational oncology studies need to optimize both pharmacokinetic (drug exposure) and pharmacodynamic (xenograft model) aspects. While improvements in pharmacodynamic translatability can be obtained by choosing cell lines or patient-derived xenograft models closer to the clinical indication, significant ambiguity and variability exists when optimizing the pharmacokinetic translation of small molecule and biotherapeutic agents.Experimental Design and Results: In this work, we propose a pharmacokinetic-based strategy to select nonclinical doses for approved drug molecules. We define a clinically relevant dose (CRD) as the dosing regimen in mice that most closely approximates the relevant pharmacokinetic metric in humans. Such metrics include area under the time–concentration curve and maximal or minimal concentrations within the dosing interval. The methodology is applied to six drugs, including targeted agents and chemotherapeutics, small and large molecules (erlotinib, dasatinib, vismodegib, trastuzumab, irinotecan, and capecitabine). The resulting efficacy response at the CRD is compared with clinical responses.Conclusions: We conclude that nonclinical studies designed with the appropriate CRDs of approved drug molecules will maximize the translatability of efficacy results, which is critical when testing approved and investigational agents in combination. Clin Cancer Res; 23(4); 1080–90. ©2016 AACR.

Full Description with references for the data included in Figure 4.

Nanoparticle (NP) technology holds significant promise to mediate targeted drug delivery to specific organs in the body. Understanding the 3D biodistribution of NPs in heterogeneous environments such as the tumor tissue can provide crucial information on efficacy, safety and potential clinical outcomes. Here we present a novel end-to-end workflow, VIOLA, which makes use of tissue clearing methodology in conjunction with high resolution imaging and advanced 3D image processing to quantify the spatiotemporal 3D biodistribution of fluorescently labeled ACCURIN® NPs. Specifically, we investigate the spatiotemporal biodistribution of NPs in three different murine tumor models (CT26, EMT6, and KPC-GEM) of increasing complexity and translational relevance. We have developed new endpoints to characterize NP biodistribution at multiple length scales. Our observations reveal that the macroscale NP biodistribution is spatially heterogeneous and exhibits a gradient with relatively high accumulation at the tumor periphery that progressively decreases towards the tumor core in all the tumor models. Microscale analysis revealed that NP extravasation from blood vessels increases in a time dependent manner and plateaus at 72 h post injection. Volumetric analysis and pharmacokinetic modeling of NP biodistribution in the vicinity of the blood vessels revealed that the local NP density exhibits a distance dependent spatiotemporal biodistribution which provide insights into the dynamics of NP extravasation in the tumor tissue. Our data represents a comprehensive analysis of NP biodistribution at multiple length scales in different tumor models providing unique insights into their spatiotemporal dynamics. Specifically, our results show that NPs exhibit a dynamic equilibrium with macroscale heterogeneity combined with microscale homogeneity.

Neutropenia is one of the most common dose-limiting toxocities associated with anticancer drug therapy. The ability to predict the probability and severity of neutropenia based on in vitro studies of drugs in early drug development will aid in advancing safe and efficacious compounds to human testing. Toward this end, a physiological model of granulopoiesis and its regulation is presented that includes the bone marrow progenitor cell cycle, allowing for a mechanistic representation of the action of relevant anticancer drugs based on in vitro studies. Model development used data from previously reported tracer kinetic studies of granulocyte disposition in healthy humans to characterize the dynamics of neutrophil margination in the presence of endogenous granulocyte-colony stimulating factor (G-CSF). In addition, previously published data from healthy volunteers following pegfilgrastim and filgrastim were used to quantify the regulatory effects of support G-CSF therapies on granulopoiesis. The model was evaluated for the cell cycle inhibitor palbociclib, using an in vitro system of human bone marrow mononuclear cells to quantify the action of palbociclib on proliferating progenitor cells, including its inhibitory effect on G1 to S phase transition. The in vitro results were incorporated into the physiological model of granulopoiesis and used to predict the time course of absolute neutrophil count (ANC) and the incidence of neutropenia observed in three previously reported clinical trials of palbociclib. The model was able to predict grade 3 and 4 neutropenia due to palbociclib treatment with 86% accuracy based on in vitro data.

The role of plasticity and epigenetics in shaping cancer evolution and response to therapy has taken center stage with recent technological advances including single cell sequencing. This roadmap article is focused on state-of-the-art mathematical and experimental approaches to interrogate plasticity in cancer, and addresses the following themes and questions: is there a formal overarching framework that encompasses both non-genetic plasticity and mutation-driven somatic evolution? How do we measure and model the role of the microenvironment in influencing/controlling non-genetic plasticity? How can we experimentally study non-genetic plasticity? Which mathematical techniques are required or best suited? What are the clinical and practical applications and implications of these concepts?

Quantitative systems pharmacology (QSP) approaches have been increasingly applied in the pharmaceutical since the landmark white paper published in 2011 by a National Institutes of Health working group brought attention to the discipline. In this perspective, we discuss QSP in the context of other modeling approaches and highlight the impact of QSP across various stages of drug development and therapeutic areas. We discuss challenges to the field as well as future opportunities.

Metabolomics activity screening can identify small-molecule metabolites that are readily available and can be used to alter phenotypes, including stem cell differentiation, T-cell survival, oligodendrocyte maturation, and insulin signaling. Metabolomics, in which small-molecule metabolites (the metabolome) are identified and quantified, is broadly acknowledged to be the omics discipline that is closest to the phenotype1,2,3. Although appreciated for its role in biomarker discovery programs, metabolomics can also be used to identify metabolites that could alter a cell's or an organism's phenotype. Metabolomics activity screening (MAS) as described here integrates metabolomics data with metabolic pathways and systems biology information, including proteomics and transcriptomics data, to produce a set of endogenous metabolites that can be tested for functionality in altering phenotypes. A growing literature reports the use of metabolites to modulate diverse processes, such as stem cell differentiation, oligodendrocyte maturation, insulin signaling, T-cell survival and macrophage immune responses. This opens up the possibility of identifying and applying metabolites to affect phenotypes. Unlike genes or proteins, metabolites are often readily available, which means that MAS is broadly amenable to high-throughput screening of virtually any biological system.

A cross-industry survey was conducted to assess the landscape of preclinical quantitative systems pharmacology (QSP) modeling within pharmaceutical companies. This article presents the survey results, which provide insights on the current state of preclinical QSP modeling in addition to future opportunities. Our results call attention to the need for an aligned definition and consistent terminology around QSP, yet highlight the broad applicability and benefits preclinical QSP modeling is currently delivering.

// Parul Gupta 1 , Jo-Ann Wentland 2 , Mauricio Leal 2 , Dangshe Ma 3, 6 , Rachel Roach 4 , Antonio Esparza 5 , Lindsay King 2 , Mary E. Spilker 2 , Cedo Bagi 1 , Christopher T. Winkelmann 1 and Anand Giddabasappa 1 1 Global Science and Technology, Comparative Medicine, Pfizer, Inc., La Jolla, CA, USA 2 Pharmacokinetics and Drug Metabolism, Pfizer, Inc., New York NY, USA 3 Oncology Research Unit, Pfizer, Inc., Pearl River, NY, USA 4 Center for Therapeutic Innovation, Pfizer, Inc., La Jolla, CA, USA 5 Comparative Medicine, Pfizer, Inc., La Jolla, CA, USA 6 Current affiliation: Regeneron Pharmaceuticals, Tarrytown, NY, USA Correspondence to: Anand Giddabasappa, email: anand.giddabasappa@pfizer.com Keywords: biotherapeutics, tumor targeting, biodistribution, fluorescence molecular tomography (FMT), molecular imaging Received: January 16, 2017 Accepted: July 03, 2017 Published: July 26, 2017 ABSTRACT Non-invasive imaging using radiolabels is a common technique used to study the biodistribution of biologics. Due to the limited shelf-life of radiolabels and the requirements of specialized labs, non-invasive optical imaging is an attractive alternative for preclinical studies. Previously, we demonstrated the utility of fluorescence molecular tomography (FMT) an optical imaging modality in evaluating the biodistribution of antibody-drug conjugates. As FMT is a relatively new technology, few fluorophores have been validated for in vivo imaging. The goal of this study was to characterize and determine the utility of near-infrared (NIR) fluorophores for biodistribution studies using interleukin-13 receptor subunit alpha-2 antibody (IL13Rα2-Ab). Eight fluorophores ( ex/em : 630/800 nm) with an N-hydroxysuccinimide (NHS) linker were evaluated for Ab conjugation. The resulting antibody-fluorophore (Ab-F) conjugates were evaluated in vitro for degree of conjugation, stability and target-binding, followed by in vivo / ex vivo FMT imaging to determine biodistribution in a xenograft model. The Ab-F conjugates (except Ab-DyLight800) showed good in vitro stability and antigen binding. All Ab-F conjugates (except for Ab-BOD630) resulted in a quantifiable signal in vivo and had similar biodistribution profiles, with peak tumor accumulation between 6 and 24 h post-injection. In vivo / ex vivo FMT imaging showed 17–34% ID/g Ab uptake by the tumor at 96 h. Overall, this is the first study to characterize the biodistribution of an Ab using eight NIR fluorophores. Our results show that 3-dimensional optical imaging is a valuable technology to understand biodistribution and targeting, but a careful selection of the fluorophore for each Ab is warranted.

The chemokine receptor CXCR4 is highly expressed and associated with poor prognosis in multiple malignancies. Upon engagement by its ligand, CXCL12, CXCR4 triggers intracellular signaling pathways that control trafficking of cells to tissues where the ligand is expressed, such as the bone marrow (BM). In hematologic cancers, CXCR4-driven homing of malignant cells to the BM protective niche is a key mechanism driving disease and therapy resistance. We developed a humanized CXCR4 immunoglobulin G1 (IgG1) antibody (Ab), PF-06747143, which binds to CXCR4 and inhibits CXCL12-mediated signaling pathways, as well as cell migration. In in vivo preclinical studies, PF-06747143 monotherapy rapidly and transiently mobilized cells from the BM into the peripheral blood. In addition, PF-06747143 effectively induced tumor cell death via its Fc constant region-mediated effector function. This Fc-mediated cell killing mechanism not only enhanced antitumor efficacy, but also played a role in reducing the duration of cell mobilization, when compared with an IgG4 version of the Ab, which does not have Fc-effector function. PF-06747143 treatment showed strong antitumor effect in multiple hematologic tumor models including non-Hodgkin lymphoma (NHL), acute myeloid leukemia (AML), and multiple myeloma (MM). Importantly, PF-06747143 synergized with standard-of-care agents in a chemoresistant AML patient-derived xenograft model and in an MM model. These findings suggest that PF-06747143 is a potential best-in-class anti-CXCR4 antagonist for the treatment of hematologic malignancies, including in the resistant setting. PF-06747143 is currently in phase 1 clinical trial evaluation (registered at www.clinicaltrials.gov as #NCT02954653).

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.

Recent advances in molecular biology have enabled personalized cancer therapies with molecularly targeted agents (MTAs), which offer a promising future for cancer therapy. Dynamic modeling and simulation (MS) is a powerful mathematical approach linking drug exposures to pharmacological responses, providing a quantitative assessment of in vivo drug potency. Accordingly, a growing emphasis is being placed upon MS to quantitatively understand therapeutic exposure-response relationships of MTAs in nonclinical models.An overview of MS approaches for MTAs in nonclinical models is presented with discussion about mechanistic extrapolation of antitumor efficacy from bench to bedside. Emphasis is placed upon recent advances in MS approaches linking drug exposures, biomarker responses (e.g. target modulation) and pharmacological outcomes (e.g. antitumor efficacy).For successful personalized cancer therapies with MTAs, it is critical to mechanistically and quantitatively understand their exposure-response relationships in nonclinical models, and to logically and properly apply such knowledge to the clinic. Particularly, MS approaches to predict pharmacologically active concentrations of MTAs in patients based upon nonclinical data would be highly valuable in guiding the design and execution of clinical trials. Proactive approaches to understand their exposure-response relationships could substantially increase probability of achieving a positive proof-of-concept in the clinic.

Gedatolisib, a PI3K/mTOR dual inhibitor delivered intravenously, is in early clinical trials in women with metastatic ER+ breast cancer. We reasoned that the therapeutic index could be further maximized by encapsulation of gedatolisib in nanoparticles (NP), thereby providing longer half-life, sustained release, blunting of Cmax and associated toxicity, asymmetric distribution to leaky tumor vasculature and the possibility of less frequent dosing. PF-07034663 is a polymeric NP encapsulating gedatolisib, targeted to prostate-specific membrane antigen (PSMA), a clinically validated tumor antigen expressed on prostate cancer cells and the neovasculature of some nonprostate solid tumors. Studies in mice, rats, and cynomolgus monkeys demonstrated that the terminal half-life of PF-07034663 following intravenous administration increased by ~1.5 fold and the Cmax of released gedatolisib from PF-07034663 decreased by ~75 fold compared to gedatolisib delivered by the same route. Gedatolisib released from PF-07034663 exhibited markedly enhanced intratumoral accumulation compared to gedatolisib (~40 fold), indicating enhanced tissue delivery and/or prolonged retention. In exploratory toxicology studies, PF-07034663 caused no hyper-insulinemic spike in rats, in contrast to gedatolisib. To evaluate the antitumor activity of PF-07034663, we performed tumor growth inhibition (TGI) studies in PSMA-positive C4-2 prostate and in PSMA-negative MDAMB361 ER+ breast and A549 lung xenograft tumor models. In the C4-2 model, PF-07034663 showed dose-dependent antitumor efficacy as a single agent, and, in combination with enzalutamide, exhibited enhanced activity leading to tumor regressions. PF 07034663 also exhibited prolonged, dose-dependent inhibition of phosphorylation of S6 (pS6) in the C4-2 model compared to gedatolisib. Interestingly, increased pharmacodynamics (PD) responses compared to gedatolisib were not restricted to PSMA-positive tumors. Moreover, TGI responses were increased in the PSMA-negative A549 lung cancer model, relative to those observed with gedatolisib. PF 07034663 treatment in spontaneous prostate tumors in PTENnullp53mut GEM mice and in subcutaneous allografts of these spontaneous tumors in wild-type mice showed that treatment of PF-07034663 caused similar pS6 inhibition in both models, suggesting that PD modulation is independent of tumor origin or milieu and is less likely due to altered enhanced permeability and retention (EPR) effect. Taken together, PF-07034663 exhibits potential for improved tolerability, sustained tumor PK, prolonged PD modulation, and less frequent dosing schedule compared to gedatolisib. These results support further exploration of gedatolisib in tumor-targeted or non-tumor-targeted nanoparticles in clinical trials as a promising vehicle for delivery of PI3K/mTOR inhibitors to advanced cancer patients. Citation Format: Lianglin Zhang, Gabriel Troche, Ravi Visswanathan, Wenhu Huang, Young-Ho Song, Mary E. Spilker, Zhenxiong Wang, Hui Wang, Anand Giddabasappa, Louise Cadzow, Susan Low, Greg Troiano, Jennifer Lafontaine, Valeria Fantin, Robert T. Abraham, Shubha Bagrodia. Development of a nanoparticle containing the PI3K/mTOR dual Inhibitor, gedatolisib, for cancer therapy [abstract]. In: Proceedings of the AACR Special Conference on Targeting PI3K/mTOR Signaling; 2018 Nov 30-Dec 8; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(10_Suppl):Abstract nr B25.

METLIN originated as a database to characterize known metabolites and has since expanded into a technology platform for the identification of known and unknown metabolites and other chemical entities. Through this effort it has become a comprehensive resource containing over 1 million molecules including lipids, amino acids, carbohydrates, toxins, small peptides, and natural products, among other classes. METLIN's high-resolution tandem mass spectrometry (MS/MS) database, which plays a key role in the identification process, has data generated from both reference standards and their labeled stable isotope analogues, facilitated by METLIN-guided analysis of isotope-labeled microorganisms. The MS/MS data, coupled with the fragment similarity search function, expand the tool's capabilities into the identification of unknowns. Fragment similarity search is performed independent of the precursor mass, relying solely on the fragment ions to identify similar structures within the database. Stable isotope data also facilitate characterization by coupling the similarity search output with the isotopic m/ z shifts. Examples of both are demonstrated here with the characterization of four previously unknown metabolites. METLIN also now features in silico MS/MS data, which has been made possible through the creation of algorithms trained on METLIN's MS/MS data from both standards and their isotope analogues. With these informatic and experimental data features, METLIN is being designed to address the characterization of known and unknown molecules.

Background In drug development, in vivo assessment of target engagement provides confidence when testing the drug's mechanism of action and improves the likelihood of clinical success. For biologics, receptor occupancy (RO) determined from circulating cells can provide evidence of target engagement. Integrating this information with mathematical modeling can further enhance the understanding of drug-target interactions and the biological factors that are critical to the successful modulation of the target and ultimately the disease state. Methods This mini-review presents two specific types of mathematical models used to describe antibody-receptor systems and highlights how experimental data can inform the model parameters. Simulations are used to illustrate how various mechanisms influence RO, PK and total cellular receptor profiles. Results The simulations demonstrate the effect antibody-receptor internalization, affinity and receptor turnover have on commonly acquired data in drug development. Conclusions Integrating RO data with mathematical models such as the two presented here (target-mediated drug disposition and site-of-action models) can provide a more comprehensive view of the biological system, which can be used to test hypotheses, extrapolate preclinical findings to humans and impact clinical study designs and risk assessments for the successful development of biotherapeutics. © 2015 International Clinical Cytometry Society

Motivation: Metabolite databases provide a unique window into metabolome research allowing the most commonly searched biomarkers to be catalogued. Omic scale metabolite profiling, or metabolomics, is finding increased utility in biomarker discovery largely driven by improvements in analytical technologies and the concurrent developments in bioinformatics. However, the successful translation of biomarkers into clinical or biologically relevant indicators is limited. Results: With the aim of improving the discovery of translatable metabolite biomarkers, we present search analytics for over one million METLIN metabolite database queries. The most common metabolites found in METLIN were cross-correlated against XCMS Online, the widely used cloud-based data processing and pathway analysis platform. Analysis of the METLIN and XCMS common metabolite data has two primary implications: these metabolites, might indicate a conserved metabolic response to stressors and, this data may be used to gauge the relative uniqueness of potential biomarkers. Availability and implementation. METLIN can be accessed by logging on to: https://metlin.scripps.edu Contact: siuzdak@scripps.edu Supplementary information: Supplementary data are available at Bioinformatics online.

A cross‐industry survey was conducted to assess the landscape of preclinical quantitative systems pharmacology (QSP) modeling within pharmaceutical companies. This article presents the survey results, which provide insights on the current state of preclinical QSP modeling in addition to future opportunities. Our results call attention to the need for an aligned definition and consistent terminology around QSP, yet highlight the broad applicability and benefits preclinical QSP modeling is currently delivering.

The protein kinase ataxia telangiectasia mutated and Rad3-related ATR is one of the key mediators of the DNA damage response. ATR is recruited to regions of single-stranded DNA, which most commonly arise during replication stress (RS). RS occurs during S-phase when the cell’s DNA replication machinery encounters problems such as unresolved DNA lesions. In addition, treatment of cells with DNA-damaging agents can lead to RS as cells progress to S-phase without resolving damage incurred by such agents. Elevated levels of RS are evident in some cancer cells, even in the absence of a DNA-damaging agent resulting from expression of oncogenes that drive dysregulated replication, a hypoxic environment, or from defects in other repair pathways. RS in cancer cells can drive reliance on ATR for survival and, accordingly, ATR inhibitors may have benefit as monotherapy. M4344 was determined to be an adenosine triphosphate (ATP)-competitive, highly potent, and tight-binding inhibitor of ATR with a Ki of < 150 pM. Minimal inhibitory activity was observed against a large panel of unrelated protein kinases, with 308 of 312 kinases tested having a measured Ki corresponding to more than 100-fold selectivity. M4344 potently inhibits ATR-driven phosphorylated checkpoint kinase-1 (P-Chk1) phosphorylation with an IC50 of 8 nM. Profiling on a selected set of cancer cell lines showed synergy with several types of DNA damaging chemotherapeutics as well as PARP1/2 and CHK1 inhibitors. In monotherapy efficacy studies M4344 showed tumor stasis to regression in tumor models with alternative lengthening of telomeres (ALT). In combination with PARP inhibitors, tumor regression could be observed in triple-negative breast cancer xenograft models. A dose-escalation phase 1 study in patients with advanced solid tumors is currently ongoing. Citation Format: Frank T. Zenke, Astrid Zimmermann, Heike Dahmen, Brian Elenbaas, John Pollard, Philip Reaper, S Bagrodia, M E. Spilker, C Amendt, Andree Blaukat. Antitumor activity of M4344, a potent and selective ATR inhibitor, in monotherapy and combination therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 369.

1. Leukotriene B4 (LTB4) is a proinflammatory mediator important in the progression of a number of inflammatory diseases. Preclinical models can explore the role of LTB4 in pathophysiology using tool compounds, such as CP-105696, that modulate its activity. To support preclinical pharmacology studies, micro-sampling techniques and mathematical modeling were used to determine the pharmacokinetics of CP-105696 in mice within the context of systemic inflammation induced by a high-fat diet (HFD). 2. Following oral administration of doses > 35 mg/kg, CP-105696 kinetics can be described by a one-compartment model with first order absorption. The compound's half-life is 44-62 h with an apparent volume of distribution of 0.51-0.72 L/kg. Exposures in animals fed an HFD are within 2-fold of those fed a normal chow diet. Daily dosing at 100 mg/kg was not tolerated and resulted in a >20% weight loss in the mice. 3. CP-105696's long half-life has the potential to support a twice weekly dosing schedule. Given that most chronic inflammatory diseases will require long-term therapies, these results are useful in determining the optimal dosing schedules for preclinical studies using CP-105696.

Purpose: The translation of nonclinical oncology studies is a subject of continuous debate. We propose that translational oncology studies need to optimize both pharmacokinetic (drug exposure) and pharmacodynamic (xenograft model) aspects. While improvements in pharmacodynamic translatability can be obtained by choosing cell lines or patient-derived xenograft models closer to the clinical indication, significant ambiguity and variability exists when optimizing the pharmacokinetic translation of small molecule and biotherapeutic agents. Experimental Design and Results: In this work, we propose a pharmacokinetic-based strategy to select nonclinical doses for approved drug molecules. We define a clinically relevant dose (CRD) as the dosing regimen in mice that most closely approximates the relevant pharmacokinetic metric in humans. Such metrics include area under the time–concentration curve and maximal or minimal concentrations within the dosing interval. The methodology is applied to six drugs, including targeted agents and chemotherapeutics, small and large molecules (erlotinib, dasatinib, vismodegib, trastuzumab, irinotecan, and capecitabine). The resulting efficacy response at the CRD is compared with clinical responses. Conclusions: We conclude that nonclinical studies designed with the appropriate CRDs of approved drug molecules will maximize the translatability of efficacy results, which is critical when testing approved and investigational agents in combination. Clin Cancer Res; 23(4); 1080–90. ©2016 AACR.

The role of the host microbiome has come to the forefront as a potential modulator of cancer metabolism and could be a future target for precision medicine. A recent study revealed that in colon cancer, bacteria form polysaccharide matrices called biofilms at a high frequency in the proximal colon. Comprehensive untargeted and stable isotope–assisted metabolomic analysis revealed that the bacteria utilize polyamine metabolites produced from colon adenomas/carcinomas to build these protective biofilms and may contribute to inflammation and proliferation observed in colon cancer. This study highlighted the importance of finding the biological origin of a metabolite and assessing its metabolism and mechanism of action. This led to a better understanding of host and microbial interactions, thereby aiding therapeutic design for cancer. In this review, we will discuss methodologies for identifying the biological origin and roles of metabolites in cancer progression and discuss the interactions of the microbiome and metabolites in immunity and cancer treatment, focusing on the flourishing field of cancer immunotherapy. Cancer Res; 76(21); 6146–52. ©2016 AACR.

Purpose: [18F]FLT (3′-Fluoro-3′ deoxythymidine)–PET imaging was proposed as a tool for measuring in vivo tumor cell proliferation. The aim of this article was to validate the use of [18F]FLT–PET imaging for measuring xenograft proliferation and subsequent monitoring of targeted therapy. Experimental Design: In exponentially growing xenografts, factors that could impact the outcome of [18F]FLT–PET imaging, such as nucleoside transporters, thymidine kinase 1, the relative contribution of DNA salvage pathway, and the ratio of FLT to thymidine, were evaluated. The [18F]FLT tracer avidity was compared with other proliferation markers. Results: In a panel of proliferating xenografts, [18F]FLT or [3H]thymidine tracer avidity failed to reflect the tumor growth rate across different tumor types, despite the high expressions of Ki67 and TK1. When FLT was injected at the same dose level as used in the preclinical [18F]FLT–PET imaging, the plasma exposure ratio of FLT to thymidine was approximately 1:200. Thymidine levels in different tumor types seemed to be variable and exhibited an inverse relationship with the FLT tracer avidity. In contrast, high-dose administration of bromdeoxyuridine (BrdUrd; 50 mg/kg) yielded a plasma exposure of more than 4-fold higher than thymidine and leads to a strong correlation between the BrdUrd uptake and the tumor proliferation rate. In FLT tracer-avid models, [18F]FLT–PET imaging as a surrogate biomarker predicted the therapeutic response of CDK4/6 inhibitor PD-0332991. Conclusions: Tumor thymidine level is one of the factors that impact the correlation between [18F]FLT uptake and tumor cell proliferation. With careful validation, [18F]FLT–PET imaging can be used to monitor antiproliferative therapies in tracer-avid malignancies. Clin Cancer Res; 18(5); 1303–12. ©2011 AACR.

Inhibition of the Smoothened (Smo) represents a promising therapeutic strategy for treating malignant tumors that are dependent on the Hedgehog (Hh) signaling pathway. PF-5274857 is a novel Smo antagonist that specifically binds to Smo with a Ki of 4.6 ± 1.1 nmol/L and completely blocks the transcriptional activity of the downstream gene Gli1 with an IC50 of 2.7 ± 1.4 nmol/L in cells. This Smo antagonist showed robust antitumor activity in a mouse model of medulloblastoma with an in vivo IC50 of 8.9 ± 2.6 nmol/L. The downregulation of Gli1 is closely linked to the tumor growth inhibition in patched+/− medulloblastoma mice. Mathematical analysis of the relationship between the drug's pharmacokinetics and Gli1 pharmacodynamics in patched+/− medulloblastoma tumor models yielded similar tumor and skin Gli1 IC50 values, suggesting that skin can be used as a surrogate tissue for the measurement of tumor Gli1 levels. In addition, PF-5274857 was found to effectively penetrate the blood–brain barrier and inhibit Smo activity in the brain of primary medulloblastoma mice, resulting in improved animal survival rates. The brain permeability of PF-5274857 was also confirmed and quantified in nontumor-bearing preclinical species with an intact blood–brain barrier. PF-5274857 was orally available and metabolically stable in vivo. These findings suggest that PF-5274857 is a potentially attractive clinical candidate for the treatment of tumor types including brain tumors and brain metastasis driven by an activated Hh pathway. Mol Cancer Ther; 11(1); 57–65. ©2011 AACR.

[(11)C]Flumazenil (FMZ) is a benzodiazepine receptor antagonist that binds reversibly to central-type gamma-aminobutyric acid (GABA-A) sites. A validated approach for analysis of [(11)C]FMZ is the invasive one-tissue (1T) compartmental model. However, it would be advantageous to analyse FMZ binding with whole-brain pixel-based methods that do not require a-priori hypotheses regarding preselected regions. Therefore, in this study we compared invasive and noninvasive data-driven methods (Logan graphical analysis, LGA; multilinear reference tissue model, MRTM2; spectral analysis, SA; basis pursuit denoising, BPD) with the 1T model.We focused on two aspects: (1) replacing the arterial input function analyses with a reference tissue method using the pons as the reference tissue, and (2) shortening the scan protocol from 90 min to 60 min. Dynamic PET scans were conducted in seven healthy volunteers with arterial blood sampling. Distribution volume ratios (DVRs) were selected as the common outcome measure.The SA, LGA with and without arterial input, and MRTM2 agreed best with the 1T model DVR values. The invasive and noninvasive BPD were slightly less well correlated. The full protocol of a 90-min emission data performed better than the 60-min protocol, but the 60-min protocol still delivered useful data, as assessed by the coefficient of variation, and the correlation and bias analyses.This study showed that the SA, LGA and MRTM2 are valid methods for the quantification of benzodiazepine receptor binding with [(11)C]FMZ using an invasive or noninvasive protocol, and therefore have the potential to reduce the invasiveness of the procedure.

The runner's high describes a euphoric state resulting from long-distance running. The cerebral neurochemical correlates of exercise-induced mood changes have been barely investigated so far. We aimed to unravel the opioidergic mechanisms of the runner's high in the human brain and to identify the relationship to perceived euphoria. We performed a positron emission tomography "ligand activation" study with the nonselective opioidergic ligand 6-O-(2-[(18)F]fluoroethyl)-6-O-desmethyldiprenorphine ([(18)F]FDPN). Ten athletes were scanned at 2 separate occasions in random order, at rest and after 2 h of endurance running (21.5 +/- 4.7 km). Binding kinetics of [(18)F]FDPN were quantified by basis pursuit denoising (DEPICT software). Statistical parametric mapping (SPM2) was used for voxelwise analyses to determine relative changes in ligand binding after running and correlations of opioid binding with euphoria ratings. Reductions in opioid receptor availability were identified preferentially in prefrontal and limbic/paralimbic brain structures. The level of euphoria was significantly increased after running and was inversely correlated with opioid binding in prefrontal/orbitofrontal cortices, the anterior cingulate cortex, bilateral insula, parainsular cortex, and temporoparietal regions. These findings support the "opioid theory" of the runner's high and suggest region-specific effects in frontolimbic brain areas that are involved in the processing of affective states and mood.

In recent years, development of rheumatoid arthritis (RA) drug therapy has been more directly targeted to counteract specific mechanisms of inflammation, and it is now believed that early aggressive treatment with disease modifying drugs is important to inhibit future structural joint damage. The development of these new treatments has increased the need for methodologies to assess disease activity in RA and monitor the effectiveness of drug therapy. Unlike X-ray, which shows only structural bone damage, magnetic resonance imaging (MRI) can depict soft tissue damage and synovitis, the primary pathology of RA. Recent studies have also indicated that MRI is sensitive to pathophysiologic changes that may predate radiographic erosions and may predict future joint damage. In this study, we have developed a computer automated analysis technique for MR wrist images that provides an objective measure of RA synovitis. This method applies a two-compartment pharmacokinetic model to every voxel of a dynamic contrast-enhanced MRI (DCE-MRI) dataset and outputs resulting parametric images. The aim of this technique is to not only objectively quantify the severity of rheumatoid synovitis, but to also locally determine where areas of serious disease activity are situated through kinetic modeling of blood-tissue exchange. Preliminary results show good correlation to early enhancement rate, which has previously been shown to be a useful clinical marker of RA activity. However, the use of tracer kinetic modeling methods potentially provides more specific information regarding underlying RA physiology. This approach could provide a useful new tool in RA patient management and could substantially improve RA therapeutic studies by calculating objective biomarkers of the disease state.

Understanding a drug's whole-body biodistribution and tumor targeting can provide important information regarding efficacy, safety, and dosing parameters. Current methods to evaluate biodistribution include in vivo imaging technologies like positron electron tomography and single-photon emission computed tomography or ex vivo quantitation of drug concentrations in tissues using autoradiography and standard biochemical assays. These methods use radioactive compounds or are cumbersome and do not give whole-body information. Here, for the first time, we show the utility of fluorescence molecular tomography (FMT) imaging to determine the biodistribution and targeting of an antibody–drug conjugate (ADC). An anti–5T4-antibody (5T4-Ab) and 5T4-ADC were conjugated with a near-infrared (NIR) fluorophore VivoTag 680XL (VT680). Both conjugated compounds were stable as determined by SEC-HPLC and plasma stability studies. Flow cytometry and fluorescence microscopy studies showed that VT680-conjugated 5T4-ADC specifically bound 5T4-expressing cells in vitro and also exhibited a similar cytotoxicity profile as the unconjugated 5T4-ADC. In vivo biodistribution and tumor targeting in an H1975 subcutaneous xenograft model demonstrated no significant differences between accumulation of VT680-conjugated 5T4-Ab or 5T4-ADC in either normal tissues or tumor. In addition, quantitation of heart signal from FMT imaging showed good correlation with the plasma pharmacokinetic profile suggesting that it (heart FMT imaging) may be a surrogate for plasma drug clearance. These results demonstrate that conjugation of VT680 to 5T4-Ab or 5T4-ADC does not change the behavior of native biologic, and FMT imaging can be a useful tool to understand biodistribution and tumor-targeting kinetics of antibodies, ADCs, and other biologics. Mol Cancer Ther; 15(10); 2530–40. ©2016 AACR.

BACKGROUND: Human in vivo data on dietary determinants of alpha-linolenic acid (ALA; 18:3n-3) metabolism are scarce. OBJECTIVE: We examined whether intakes of ALA or linoleic acid (LA; 18:2n-6) or their ratio influences ALA metabolism. DESIGN: During 4 wk, 29 subjects received a control diet (7% of energy from LA, 0.4% of energy from ALA, ALA-to-LA ratio = 1:19). For the next 6 wk, a control diet, a low-LA diet (3% of energy from LA, 0.4% of energy from ALA, ratio = 1:7), or a high-ALA diet (7% of energy from LA, 1.1% of energy from ALA, ratio = 1:7) was consumed. Ten days before the end of each dietary period, [U-13C]ALA was administered orally for 9 d. ALA oxidation was determined from breath. Conversion was estimated by using compartmental modeling of [13C]- and [12C]n-3 fatty acid concentrations in fasting plasma phospholipids. RESULTS: Compared with the control group, ALA incorporation into phospholipids increased by 3.6% in the low-LA group (P = 0.012) and decreased by 8.0% in the high-ALA group (P < 0.001). In absolute amounts, it increased by 34.3 mg (P = 0.020) in the low-LA group but hardly changed in the high-ALA group. Nearly all ALA from the plasma phospholipid pool was converted into eicosapentaenoic acid. Conversion of eicosapentaenoic acid into docosapentaenoic acid and docosahexaenoic acid hardly changed in the 3 groups and was

Background— Neovasculature within atherosclerotic plaques is believed to be associated with infiltration of inflammatory cells and plaque destabilization. The aim of the present investigation was to determine whether the amount of neovasculature present in advanced carotid plaques can be noninvasively measured by dynamic, contrast-enhanced MRI. Methods and Results— A total of 20 consecutive patients scheduled for carotid endarterectomy were recruited to participate in an MRI study. Images were obtained at 15-second intervals, and a gadolinium contrast agent was injected coincident with the second of 10 images in the sequence. The resulting image intensity within the plaque was tracked over time, and a kinetic model was used to estimate the fractional blood volume. For validation, matched sections from subsequent endarterectomy were stained with ULEX and CD-31 antibody to highlight microvessels. Finally, all microvessels within the matched sections were identified, and their total area was computed as a fraction of the plaque area. Results were obtained from 16 participants, which showed fractional blood volumes ranging from 2% to 41%. These levels were significantly higher than the histological measurements of fractional vascular area. Nevertheless, the 2 measurements were highly correlated, with a correlation coefficient of 0.80 ( P Conclusions— Dynamic contrast-enhanced MRI provides an indication of the extent of neovasculature within carotid atherosclerotic plaque. MRI therefore provides a means for prospectively studying the link between neovasculature and plaque vulnerability.

In drug development, in vivo assessment of target engagement provides confidence when testing the drug's mechanism of action and improves the likelihood of clinical success. For biologics, receptor occupancy (RO) determined from circulating cells can provide evidence of target engagement. Integrating this information with mathematical modeling can further enhance the understanding of drug-target interactions and the biological factors that are critical to the successful modulation of the target and ultimately the disease state.This mini-review presents two specific types of mathematical models used to describe antibody-receptor systems and highlights how experimental data can inform the model parameters. Simulations are used to illustrate how various mechanisms influence RO, PK and total cellular receptor profiles.The simulations demonstrate the effect antibody-receptor internalization, affinity and receptor turnover have on commonly acquired data in drug development.Integrating RO data with mathematical models such as the two presented here (target-mediated drug disposition and site-of-action models) can provide a more comprehensive view of the biological system, which can be used to test hypotheses, extrapolate preclinical findings to humans and impact clinical study designs and risk assessments for the successful development of biotherapeutics.

Fluorocarbons are lipophobic and non-polar molecules that exhibit remarkable bio-compatibility, with applications in liquid ventilation and synthetic blood. The unique properties of these compounds have also enabled mass spectrometry imaging of tissues where the fluorocarbons act as a Teflon-like coating for nanostructured surfaces to assist in desorption/ionization. Here we report fluorinated gold nanoparticles (f-AuNPs) designed to facilitate nanostructure imaging mass spectrometry. Irradiation of f-AuNPs results in the release of the fluorocarbon ligands providing a driving force for analyte desorption. The f-AuNPs allow for the mass spectrometry analysis of both lipophilic and polar (central carbon) metabolites. An important property of AuNPs is that they also act as contrast agents for X-ray microtomography and electron microscopy, a feature we have exploited by infusing f-AuNPs into tissue via fluorocarbon liquids to facilitate multi-modal (molecular and anatomical) imaging.

The chemokine receptor CXCR4 triggers signaling pathways that control cell migration to tissues where its ligand, CXCL12, is highly expressed, including the bone marrow (BM). In hematologic cancers, CXCR4 expression is associated with poor prognosis. CXCR4-driven homing of malignant cells to the BM protective niche is a key mechanism of chemotherapy resistance. PF-06747143 is a novel humanized IgG1 therapeutic antibody that binds to CXCR4 and inhibits CXCL12-driven pathways. Human IgG1 antibodies can induce strong cytotoxicity mediated by the antibody Fc-region, including antibody-dependent cell-mediated cytotoxicity (ADCC) and complement-driven cytotoxicity, while human IgG4 antibodies show minimal or no Fc-driven cytotoxicity. Here we generated an IgG4 version of PF-06747143 (m15-IgG4), which has similar binding to CXCR4 as the IgG1 antibody. We then characterized the role of Fc-driven cytotoxic function, comparing both antibodies in efficacy and safety studies. In an ADCC assay, PF-06747143 showed strong cytotoxicity of non-Hodgkin’s lymphoma (NHL) and acute myeloid leukemia (AML), while m15-IgG4 had no significant cytotoxicity. In a NHL mouse tumor model, the IgG1 CXCR4 antibody resulted in superior tumor growth inhibition, with 50% of mice exhibiting complete tumor regressions, compared to the m15-IgG4 antibody, which had limited activity, with no tumor regressions (p 4 days. Since both antibodies had comparable exposures, the different mobilization duration is likely due to the ability of the IgG1 CXCR4 antibody to reduce the number of mobilized cells via Fc-driven cytotoxic function. Finally, CXCR4 has been shown to play a key role in chemotherapy resistance. In a chemo-resistant PDX AML mouse model, in which the standard of care agents daunorubicin and cytarabine had limited activity, resulting in 30% of tumor cells remaining in the BM post-treatment, we show that combination of PF-06747143 with these chemo agents led to synergistic activity, with tumor burden reduced to 0.3% tumor cells in the BM. In conclusion, PF-06747143 attributes offer potential efficacy- and safety-related advantages over other CXCR4 antagonists currently in development, which do not have Fc-driven cytotoxic activity. PF-06747143 is now being evaluated in a Phase 1 clinical trial in relapsed and refractory AML (NCTID 02954653). Citation Format: Flavia Pernasetti, Shu-Hui Liu, Gu Yin, Bernadette Pascual, Zhengming Yan, Max Hallin, Rolla Yafawi, Cathy Zhang, Connie Fang, Wenlian Wang, Justine Lam, Mary E. Spilker, Eileen Blasi, Brett Simmons, Nanni Huser, Wei-Hsien Ho, Kevin Lindquist, Thomas-Toan Tran, Jyothirmayee Kudaravalli, Jing-Tyan Ma, Gretchen Jimenez, Ishita Barman, Colleen Brown, Sherman-Michael Chin, Maria Costa, David Shelton, Tod Smeal, Valeria R. Fantin. Fc-effector function activity of the CXCR4 IgG1 antibody PF-06747143: a novel clinical candidate for the treatment of hematologic malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2649. doi:10.1158/1538-7445.AM2017-2649

Background The complexity and multiscale nature of the mammalian immune response provides an excellent test bed for the potential of mathematical modeling and simulation to facilitate mechanistic understanding. Historically, mathematical models of the immune response focused on subsets of the immune system and/or specific aspects of the response. Mathematical models have been developed for the humoral side of the immune response, or for the cellular side, or for cytokine kinetics, but rarely have they been proposed to encompass the overall system complexity. We propose here a framework for integration of subset models, based on a system biology approach. Results A dynamic simulator, the Fully-integrated Immune Response Model (FIRM), was built in a stepwise fashion by integrating published subset models and adding novel features. The approach used to build the model includes the formulation of the network of interacting species and the subsequent introduction of rate laws to describe each biological process. The resulting model represents a multi-organ structure, comprised of the target organ where the immune response takes place, circulating blood, lymphoid T, and lymphoid B tissue. The cell types accounted for include macrophages, a few T-cell lineages (cytotoxic, regulatory, helper 1, and helper 2), and B-cell activation to plasma cells. Four different cytokines were accounted for: IFN-γ, IL-4, IL-10 and IL-12. In addition, generic inflammatory signals are used to represent the kinetics of IL-1, IL-2, and TGF-β. Cell recruitment, differentiation, replication, apoptosis and migration are described as appropriate for the different cell types. The model is a hybrid structure containing information from several mammalian species. The structure of the network was built to be physiologically and biochemically consistent. Rate laws for all the cellular fate processes, growth factor production rates and half-lives, together with antibody production rates and half-lives, are provided. The results demonstrate how this framework can be used to integrate mathematical models of the immune response from several published sources and describe qualitative predictions of global immune system response arising from the integrated, hybrid model. In addition, we show how the model can be expanded to include novel biological findings. Case studies were carried out to simulate TB infection, tumor rejection, response to a blood borne pathogen and the consequences of accounting for regulatory T-cells. Conclusions The final result of this work is a postulated and increasingly comprehensive representation of the mammalian immune system, based on physiological knowledge and susceptible to further experimental testing and validation. We believe that the integrated nature of FIRM has the potential to simulate a range of responses under a variety of conditions, from modeling of immune responses after tuberculosis (TB) infection to tumor formation in tissues. FIRM also has the flexibility to be expanded to include both complex and novel immunological response features as our knowledge of the immune system advances.