Search

Immuno-oncology (IO) is a fast-expanding field due to recent success using IO therapies in treating cancer. As IO therapies do not directly kill tumor cells but rather act upon the patients' own immune cells either systemically or in the tumor microenvironment, new and innovative approaches are required to inform IO therapy research and development. Quantitative systems pharmacology (QSP) modeling describes the biological mechanisms of disease and the mode of action of drugs with mathematical equations, which has significant potential to address the big challenges in the IO field, from identifying patient populations that respond to different therapies to guiding the selection, dosing, and scheduling of combination therapy. To assess the perspectives of the community on the impact of QSP modeling in IO drug development and to understand current applications and challenges, the IO QSP working group-under the QSP Special Interest Group (SIG) of the International Society of Pharmacometrics (ISoP)-conducted a survey among QSP modelers, non-QSP modelers, and non-modeling IO program stakeholders. The survey results are presented here with discussions on how to address some of the findings. One of the findings is the differences in perception among these groups. To help bridge this perception gap, we present several case studies demonstrating the impact of QSP modeling in IO and suggest actions that can be taken in the future to increase the real and perceived impact of QSP modeling in IO drug research and development.

Despite tremendous success of chimeric antigen receptor (CAR) T cell therapy in clinical oncology, the dose‐exposure‐response relationship of CAR‐T cells in patients is poorly understood. Moreover, the key drug‐specific and system‐specific determinants leading to favorable clinical outcomes are also unknown. Here we have developed a multiscale mechanistic pharmacokinetic (PK)‐pharmacodynamic (PD) model for anti‐B‐cell maturation antigen (BCMA) CAR‐T cell therapy (bb2121) to characterize (i) in vitro target cell killing in multiple BCMA expressing tumor cell lines at varying effector to target cell ratios, (ii) preclinical in vivo tumor growth inhibition and blood CAR‐T cell expansion in xenograft mice, and (iii) clinical PK and PD biomarkers in patients with multiple myeloma. Our translational PK‐PD relationship was able to effectively describe the commonly observed multiphasic CAR‐T cell PK profile in the clinic, consisting of the rapid distribution, expansion, contraction, and persistent phases, and accounted for the categorical individual responses in multiple myeloma to effectively calculate progression‐free survival rates. Preclinical and clinical data analysis revealed comparable parameter estimates pertaining to CAR‐T cell functionality and suggested that patient baseline tumor burden could be more sensitive than dose levels toward overall extent of exposure after CAR‐T cell infusion. Virtual patient simulations also suggested a very steep dose‐exposure‐response relationship with CAR‐T cell therapy and indicated the presence of a “threshold” dose, beyond which a flat dose‐response curve could be observed. Our simulations were concordant with multiple clinical observations discussed in this article. Moving forward, this framework could be leveraged a priori to explore multiple infusions and support the preclinical/clinical development of future CAR‐T cell therapies.

Chimeric antigen receptor (CAR) T cell therapies have revolutionized the treatment of hematologic malignancies and have potentials for solid tumor treatment. To overcome limited CAR T cell infiltration to solid tumors, local delivery of CAR T cells is a practical strategy that has shown promising therapeutic outcome and safety profile in the clinic. It is of great interest to understand the impact of dosing routes on CAR T cell distribution, subsequent proliferation and tumor killing in a quantitative manner to identify key factors that contribute to CAR T efficacy and safety. In this study, we established mouse minimal physiologically-based pharmacokinetic (mPBPK) models combined with pharmacodynamic (PD) components to delineate CAR T cell distribution, proliferation, tumor growth, and tumor cell killing in the cases of pleural and liver tumors. The pleural tumor model reasonably captured published CAR T cellular kinetic and tumor growth profiles in mice. The mPBPK-PD simulation of a liver tumor mouse model showed a substantial increase in initial tumor infiltration and earlier CAR T cell proliferation with local hepatic artery delivery compared to portal vein and intravenous (i.v.) injections whereas portal vein injection showed little difference from i.v. administration, suggesting the importance of having the injection site close to tumor for maximal effect of non-systemic administration. Blood flow rate in the liver tumor was found to be a sensitive parameter for cellular kinetics and efficacy, indicating a potential role of tumor vascularization in the efficacy of CAR T cell therapies.

The objective of this work was to develop a systems pharmacokinetics-pharmacodynamics (PK-PD) model that can characterize in vivo bystander effect of antibody-drug conjugate (ADC) in a heterogeneous tumor. To accomplish this goal, a coculture xenograft tumor with 50% GFP-MCF7 (HER2-low) and 50% N87 (HER2-high) cells was developed. The relative composition of a heterogeneous tumor for each cell type was experimentally determined by immunohistochemistry analysis. Trastuzumab-vc-MMAE (T-vc-MMAE) was used as a tool ADC. Plasma and tumor PK of T-vc-MMAE was analyzed in N87, GFP-MCF7, and coculture tumor-bearing mice. In addition, tumor growth inhibition (TGI) studies were conducted in all three xenografts at different T-vc-MMAE dose levels. To characterize the PK of ADC in coculture tumors, our previously published tumor distribution model was evolved to account for different cell populations. The evolved tumor PK model was able to a priori predict the PK of all ADC analytes in the coculture tumors reasonably well. The tumor PK model was subsequently integrated with a PD model that used intracellular tubulin occupancy to drive ADC efficacy in each cell type. The final systems PK-PD model was able to simultaneously characterize all the TGI data reasonably well, with a common set of parameters for MMAE-induced cytotoxicity. The model was later used to simulate the effect of different dosing regimens and tumor compositions on the bystander effect of ADC. The model simulations suggested that dose-fractionation regimen may further improve overall efficacy and bystander effect of ADCs by prolonging the tubulin occupancy in each cell type. SIGNIFICANCE STATEMENT: A PK-PD analysis is presented to understand bystander effect of Trastuzumab-vc-MMAE ADC in antigen (Ag)-low, Ag-high, and coculture (i.e., Ag-high + Ag-low) xenograft mice. This study also describes a novel single cell-level systems PK-PD model to characterize in vivo bystander effect of ADCs. The proposed model can serve as a platform to mathematically characterize multiple cell populations and their interactions in tumor tissues. Our analysis also suggests that fractionated dosing regimen may help improve the bystander effect of ADCs.

Cellular protein homeostasis is achieved by a delicate network of molecular chaperones and various proteolytic processes such as ubiquitin–proteasome system (UPS) to avoid a build-up of misfolded protein aggregates. The latter is a common denominator of neurodegeneration. Neurons are found to be particularly vulnerable to toxic stress from aggregation-prone proteins such as α-synuclein. Induction of heat-shock proteins (HSPs), such as through activated heat shock transcription factor 1 (HSF1) via Hsp90 inhibition, is being investigated as a therapeutic option for proteinopathic diseases. HSF1 is a master stress-protective transcription factor which activates genes encoding protein chaperones (e.g. iHsp70) and anti-apoptotic proteins. However, whether and how HSF1 is dysregulated during neurodegeneration has not been studied. Here, we discover aberrant HSF1 degradation by aggregated α-synuclein (or α-synuclein-induced proteotoxic stress) in transfected neuroblastoma cells. HSF1 dysregulation via α-synuclein was confirmed by in vivo assessment of mouse and in situ studies of human specimens with α-synucleinopathy. We demonstrate that elevated NEDD4 is implicated as the responsible ubiquitin E3 ligase for HSF1 degradation through UPS. Furthermore, pharmacologically induced SIRT1-mediated deacetylation can attenuate aberrant NEDD4-mediated HSF1 degradation. Indeed, we define the acetylation status of the Lys 80 residue located in the DNA-binding domain of HSF1 as a critical factor in modulating HSF1 protein stability in addition to its previously identified role in the transcriptional activity. Together with the finding that preserving HSF1 can alleviate α-synuclein toxicity, the first part of the study strongly suggests that aberrant HSF1 degradation is a key neurodegenerative mechanism underlying α-synucleinopathy. Chronic activation of another cellular stress response, unfolded protein response in ER, has been implicated in tauopathy including Alzheimer’s disease (AD). The unfolded protein response (UPR) in the endoplasmic reticulum (ER) and the cytoplasmic heat stress response are two major stress response systems necessary for maintaining proteostasis for cellular health. Failure of either of these systems, such as in sustained UPR activation or in insufficient heat shock response activation, can lead to the development of neurodegeneration. Alleviation of ER stress and enhancement of heat shock response through heat shock factor 1 (HSF1) activation have previously been considered as attractive potential therapeutic targets for AD—a prevalent and devastating tauopathy. The second part of the study concentrates on our attempts to understand the interplay of the two aforementioned systems and their cooperative role in AD. We provide compelling in vitro and in vivo evidence that strongly suggests an auto-propagating interplay of UPR activation and HSF1 degradation being a common pathogenic feature in both human AD and tau transgenic mouse AD models. We identify aging-associated AD-like neuropathological changes in the hippocampus of HSF1 heterozygous knock-out mice. We speculate that HSF1 loss as an early (earliest) event which constitutes a mechanistic connection between ER stress and tau hyperphosphorylation in tau pathology. Finally, we demonstrate that aged mice lacking HSF1 gene exhibited deficits in hippocampal-dependent functions including short-term working memory, spatial learning and long-term memory. All together, our work supports a previously underappreciated importance of this master stress regulator HSF1 in neuronal functions and in maintaining brain homeostasis.

Acyldepsipeptides are a unique class of antibiotics that act via allosterically dysregulated activation of the bacterial caseinolytic protease (ClpP). The ability of ClpP activators to kill nongrowing bacteria represents a new opportunity to combat deep-seated biofilm infections. However, the acyldepsipeptide scaffold is subject to rapid metabolism. Herein, we explore alteration of the potentially metabolically reactive α,β unsaturated acyl chain. Through targeted synthesis, a new class of phenyl urea substituted depsipeptide ClpP activators with improved metabolic stability is described. The ureadepsipeptides are potent activators of Staphylococcus aureus ClpP and show activity against Gram-positive bacteria, including S. aureus biofilms. These studies demonstrate that a phenyl urea motif can successfully mimic the double bond, maintaining potency equivalent to acyldepsipeptides but with decreased metabolic liability. Although removal of the double bond from acyldepsipeptides generally has a significant negative impact on potency, structural studies revealed that the phenyl ureadepsipeptides can retain potency through the formation of a third hydrogen bond between the urea and the key Tyr63 residue in the ClpP activation domain. Ureadepsipeptides represent a new class of ClpP activators with improved drug-like properties, potent antibacterial activity, and the tractability to be further optimized.

A series of novel chalcone and thiol-Michael addition analogues was synthesized and tested against Mycobacterium tuberculosis and other clinically significant bacterial pathogens. Previously reported chalcone-like antibacterials (1a–c and 2) were used as a training set to generate a pharmacophore model. The chalcone derivative hit compound 3 was subsequently identified through a pharmacophore-based virtual screen of the Specs library of >200 000 compounds. Among the newly synthesized chalcones and thiol-Michael addition analogues, chalcones 6r and 6s were active (minimum inhibitory concentrations (MICs) = 1.56–6.25 μg/mL) against Gram-positive pathogens Bacillus anthracis and Staphylococcus aureus [methicillin-susceptible S. aureus (MSSA) and methicillin-resistant S. aureus (MRSA)]. The chalcone thiol-Michael addition derivatives 7j–m showed good to excellent antibacterial activities (MICs = 0.78–6.25 μg/mL) against Enterococcus faecalis, B. anthracis, and S. aureus. Interestingly, the amine-Michael addition analogue 12a showed promising anti-MRSA activity (MIC = 1.56 μg/mL) with a selectivity index of 14 toward mammalian Vero cells. In addition, evaluation of selected compounds against biofilm and planktonic S. aureus (MSSA and MRSA) revealed that 12a exhibited bactericidal activities in these assays, which was overall superior to vancomycin. These properties may result from the compounds dissipating the proton motive force of bacterial membranes.

Chimeric antigen receptor (CAR)-T cell therapy has achieved considerable success in treating B-cell hematologic malignancies. However, the challenges of extending CAR-T therapy to other tumor types, particularly solid tumors, remain appreciable. There are substantial variabilities in CAR-T cellular kinetics across CAR-designs, CAR-T products, dosing regimens, patient responses, disease types, tumor burdens, and lymphodepletion conditions. As a “living drug”, CAR-T cellular kinetics typically exhibit four distinct phases: distribution, expansion, contraction, and persistence. The cellular kinetics of CAR-T may correlate with patient responses, but which factors determine CAR-T cellular kinetics remain poorly defined. Herein, we developed a cellular kinetic model to retrospectively characterize CAR-T kinetics in 217 patients from 7 trials and compared CAR-T kinetics across response status, patient populations, and tumor types. Based on our analysis results, CAR-T cells exhibited a significantly higher cell proliferation rate and capacity but a lower contraction rate in patients who responded to treatment. CAR-T cells proliferate to a higher degree in hematologic malignancies than in solid tumors. Within the assessed dose ranges (107–109 cells), CAR-T doses were weakly correlated with CAR-T cellular kinetics and patient response status. In conclusion, the developed CAR-T cellular kinetic model adequately characterized the multiphasic CAR-T cellular kinetics and supported systematic evaluations of the potential influencing factors, which can have significant implications for the development of more effective CAR-T therapies.

The development of mechanism-based, multiscale pharmacokinetic–pharmacodynamic (PK-PD) models for chimeric antigen receptor (CAR)-T cells is needed to enable investigation of in vitro and in vivo correlation of CAR-T cell responses and to facilitate preclinical-to-clinical translation. Toward this goal, we first developed a cell-level in vitro PD model that quantitatively characterized CAR-T cell-induced target cell depletion, CAR-T cell expansion and cytokine release. The model accounted for key drug-specific (CAR-affinity, CAR-densities) and system-specific (antigen densities, E:T ratios) variables and was able to characterize comprehensive in vitro datasets from multiple affinity variants of anti-EGFR and anti-HER2 CAR-T cells. Next, a physiologically based PK (PBPK) model was developed to simultaneously characterize the biodistribution of untransduced T-cells, anti-EGFR CAR-T and anti-CD19 CAR-T cells in xenograft -mouse models. The proposed model accounted for the engagement of CAR-T cells with tumor cells at the site of action. Finally, an integrated PBPK-PD relationship was established to simultaneously characterize expansion of CAR-T cells and tumor growth inhibition (TGI) in xenograft mouse model, using datasets from anti-BCMA, anti-HER2, anti-CD19 and anti-EGFR CAR-T cells. Model simulations provided potential mechanistic insights toward the commonly observed multiphasic PK profile (i.e., rapid distribution, expansion, contraction and persistence) of CAR-T cells in the clinic. Model simulations suggested that CAR-T cells may have a steep dose-exposure relationship, and the apparent Cmax upon CAR-T cell expansion in blood may be more sensitive to patient tumor-burden than CAR-T dose levels. Global sensitivity analysis described the effect of other drug-specific parameters toward CAR-T cell expansion and TGI. The proposed modeling framework will be further examined with the clinical PK and PD data, and the learnings can be used to inform design and development of future CAR-T therapies.

The constitutive androstane receptor (CAR) and pregnane X receptor (PXR) are xenobiotic sensors that regulate the expression of drug-metabolizing enzymes and efflux transporters. CAR activation promotes drug elimination, thereby reducing therapeutic effectiveness, or causes adverse drug effects via toxic metabolites. CAR inhibitors could be used to attenuate these adverse drug effects. CAR and PXR share ligands and target genes, confounding the understanding of the regulation of receptor-specific activity. We previously identified a small-molecule inhibitor, CINPA1, that inhibits CAR (without activating PXR at lower concentrations) by altering CAR-coregulator interactions and reducing CAR recruitment to DNA response elements of regulated genes. However, solid evidence was not presented for the direct binding of CINPA1 to CAR. In this study, we demonstrate direct interaction of CINPA1 with the CAR ligand-binding domain (CAR-LBD) and identify key residues involved in such interactions through a combination of biophysical and computational methods. We found that CINPA1 resides in the ligand-binding pocket to stabilize the CAR-LBD in a more rigid, less fluid state. Molecular dynamics simulations, together with our previously reported docking model, enabled us to predict which CAR residues were critical for interactions with CINPA1. The importance of these residues for CINPA1 binding were then validated by directed mutations and testing the mutant CAR proteins in transcription reporter and coregulatory interaction assays. We demonstrated strong hydrogen bonding of CINPA1 with N165 and H203 and identified other residues involved in hydrophobic contacts with CINPA1. Overall, our data confirm that CINPA1 directly binds to CAR.

Successful clinical translation of antibody-drug conjugates (ADCs) can be challenging due to complex pharmacokinetics and differences between preclinical and clinical tumors. To facilitate this translation, we have developed a general pharmacokinetic-pharmacodynamic (PK-PD) modeling and simulation (M&S)-based strategy for ADCs. Here we present the validation of this strategy using T-DM1 as a case study. A previously developed preclinical tumor disposition model for T-DM1 (Singh and Shah, AAPSJ. 2015; 18(4):861–875) was used to develop a PK-PD model that can characterize in vivo efficacy of T-DM1 in preclinical tumor models. The preclinical data was used to estimate the efficacy parameters for T-DM1. Human PK of T-DM1 was a priori predicted using allometric scaling of monkey PK parameters. The predicted human PK, preclinically estimated efficacy parameters, and clinically observed volume and growth parameters for breast cancer were combined to develop a translated clinical PK-PD model for T-DM1. Clinical trial simulations were performed using the translated PK-PD model to predict progression-free survival (PFS) and objective response rates (ORRs) for T-DM1. The model simulated PFS rates for HER2 1+ and 3+ populations were comparable to the rates observed in three different clinical trials. The model predicted only a modest improvement in ORR with an increase in clinically approved dose of T-DM1. However, the model suggested that a fractionated dosing regimen (e.g., front loading) may provide an improvement in the efficacy. In general, the PK-PD M&S-based strategy presented here is capable of a priori predicting the clinical efficacy of ADCs, and this strategy has been now retrospectively validated for all clinically approved ADCs.

The objective of this work was to develop a systems pharmacokinetics-pharmacodynamics (PK-PD) model that can characterize in vivo bystander effect of antibody-drug conjugate (ADC) in a heterogeneous tumor. To accomplish this goal, a coculture xenograft tumor with 50% GFP-MCF7 (HER2-low) and 50% N87 (HER2-high) cells was developed. The relative composition of a heterogeneous tumor for each cell type was experimentally determined by immunohistochemistry analysis. Trastuzumab-vc-MMAE (T-vc-MMAE) was used as a tool ADC. Plasma and tumor PK of T-vc-MMAE was analyzed in N87, GFP-MCF7, and coculture tumor–bearing mice. In addition, tumor growth inhibition (TGI) studies were conducted in all three xenografts at different T-vc-MMAE dose levels. To characterize the PK of ADC in coculture tumors, our previously published tumor distribution model was evolved to account for different cell populations. The evolved tumor PK model was able to a priori predict the PK of all ADC analytes in the coculture tumors reasonably well. The tumor PK model was subsequently integrated with a PD model that used intracellular tubulin occupancy to drive ADC efficacy in each cell type. The final systems PK-PD model was able to simultaneously characterize all the TGI data reasonably well, with a common set of parameters for MMAE-induced cytotoxicity. The model was later used to simulate the effect of different dosing regimens and tumor compositions on the bystander effect of ADC. The model simulations suggested that dose-fractionation regimen may further improve overall efficacy and bystander effect of ADCs by prolonging the tubulin occupancy in each cell type. SIGNIFICANCE STATEMENT: A PK-PD analysis is presented to understand bystander effect of Trastuzumab-vc-MMAE ADC in antigen (Ag)-low, Ag-high, and coculture (i.e., Ag-high + Ag-low) xenograft mice. This study also describes a novel single cell–level systems PK-PD model to characterize in vivo bystander effect of ADCs. The proposed model can serve as a platform to mathematically characterize multiple cell populations and their interactions in tumor tissues. Our analysis also suggests that fractionated dosing regimen may help improve the bystander effect of ADCs.

It has been proposed that the binding-site barrier (BSB) for antibody-drug conjugates (ADCs) can be overcome with the help of antibody coadministration. However, broad utility of this strategy remains in question. Consequently, here, we have conducted in vivo experiments and pharmacokinetics-pharmacodynamics (PK-PD) modeling and simulation (M&S) to further evaluate the antibody coadministration hypothesis in a quantitative manner. Two different Trastuzumab-based ADCs, T-DM1 (no bystander effect) and T-vc-MMAE (with a bystander effect), were evaluated in high-HER2 (N87) and low-HER2 (MDA-MB-453) expressing tumors, with or without the coadministration of 1, 3, or 8-fold higher Trastuzumab. The tumor growth inhibition (TGI) data was quantitatively characterized using a semi-mechanistic PK-PD model to determine the nature of drug interaction for each coadministration regimen, by estimating the interaction parameter ψ. It was found that the coadministration strategy improved ADC efficacy under certain conditions and had no impact on ADC efficacy in others. The benefit was more pronounced for N87 tumors with very high antigen expression levels where the effect on treatment was synergistic (a synergistic drug interaction, ψ = 2.86 [2.6–3.12]). The benefit was diminished in tumor with lower antigen expression (MDA-MB-453) and payload with bystander effect. Under these conditions, the coadministration regimens resulted in an additive or even less than additive benefit (ψ ≤ 1). As such, our results suggest that while antibody coadministration may be helpful for ADCs in certain circumstances, one should not broadly apply this strategy to all the scenarios without first identifying the costs and benefits of this approach.

Here, we have developed a cell-level systems PK-PD model to characterize the bystander effect of antibody-drug conjugates (ADCs). Cytotoxicity data generated following incubation of Trastuzumab-vc-MMAE in cocultures of high HER2-expressing N87 and low HER2-expressing GFP-MCF7 cells were used to build the model. Single-cell PK model for ADC was used to characterize the PK of trastuzumab-vc-MMAE and released MMAE in N87 and GFP-MCF7 cells. The 2 cell-level PK models were mechanistically integrated to mimic the coculture condition. MMAE-induced intracellular occupancy of tubulin was used to drive the efficacy of ADC, and improvement in the tubulin occupancy of GFP-MCF7 cells in the presence of N87 cells was used to drive the bystander effect of trastuzumab-vc-MMAE. The “dual” cell-level PK-PD model was able to capture the observed data reasonably well. It was found that similar and high occupancy of tubulin by MMAE was required to achieve the cytotoxic effect in each cell line. In addition, estimated model parameters suggested that ∼60% improvement in the tubulin occupancy was required to attain half of the maximum bystander killing effect by the ADC. The presented model provides foundation for in vivo systems PK-PD model to characterize and predict the bystander effect of ADCs.

Antibody-drug conjugates (ADCs) are designed to target antigen expressing (Ag+) cells in a tumor. Once processed by the Ag+ cells, ADCs can release cytotoxic drug molecules that can diffuse out of Ag+ cells into the neighboring antigen-negative (Ag-) cells to induce their cytotoxicity. This additional efficacy of ADCs on Ag- cells in the presence of Ag+ cells is known as the 'bystander effect'. Although the importance of this phenomena is widely acknowledged for effective killing of a heterogeneous tumor, the rate and extent of the bystander killing in a heterogeneous system is not quantitatively understood yet. Thus, the objectives of this manuscript were to: (1) synthesize and characterize a tool ADC Trastuzumab-vc-MMAE that is capable of exhibiting bystander effect, (2) quantify the time course of the bystander effect for the tool ADC using in vitro co-culture systems created using mixture of various HER2-expressing cell lines, and (3) develop a pharmacodynamic (PD) model that is capable of characterizing the bystander effect of ADCs. Co-culture studies conducted using GFP labelled MCF7 cells as Ag- cells and N87, BT474, and SKBR3 as Ag+ cells revealed that the bystander effect of ADC increases with increasing fraction of Ag+ cells in a co-culture system, and with increased expression level of target on Ag+ cells. A notable lag time after ADC incubation was also observed prior to significant bystander killing of Ag- cells. Based on our results we hypothesize that there may be other determinants apart from the antigen expression level that can also influence the ability of Ag+ cells to demonstrate the bystander effect in a co-culture system. The co-culture analysis also suggested that the bystander effect of the ADC can dissipate over the period of time as the population of Ag+ cells declines. A novel PD model was developed to mathematically characterize the bystander effect of ADCs by combining two different cell distribution models to represent the population of Ag+ and Ag- cells in a co-culture system. This PD model can be integrated with the systems PK model for ADCs in the future to generate a quantitative framework that is capable of supporting the discovery and development of novel ADCs with optimal bystander killing capabilities.

Bacterial infections, caused by Mycobacterium tuberculosis and other problematic bacterial pathogens, continue to pose a significant threat to global public health. As such, new chemotype antibacterial agents are desperately needed to fuel and strengthen the antibacterial drug discovery and development pipeline. As part of our antibacterial research program to develop natural product-inspired new antibacterial agents, here we report synthesis, antibacterial evaluation, and structure-activity relationship studies of an extended chemical library of macrocyclic diarylheptanoids with diverse amine, amide, urea, and sulfonamide functionalities. Results of this study have produced macrocyclic geranylamine and 4-fluorophenethylamine substituted derivatives, exhibiting moderate to good activity against M. tuberculosis and selected Gram-positive bacterial pathogens.

Antibiotics with novel bactericidal mechanisms of action are urgently needed. The antibiotic acyldepsipeptide 4 (ADEP4) activates the ClpP protease and causes cells to self-digest. The effects of ADEP4 and ClpP activation have not been characterized sufficiently for the enterococci, which are important pathogens known for high levels of acquired and intrinsic antibiotic resistance. In the present study, ADEP4 was found to be potently active against both Enterococcus faecalis and Enterococcus faecium, with MIC90s of 0.016 μg/ml and 0.031 μg/ml, respectively. ClpP purified from E. faecium was found to bind ADEP4 in a surface plasmon resonance analysis, and ClpP activation by ADEP4 was demonstrated biochemically with a β-casein digestion assay. In addition, E. faecium ClpP was crystallized in the presence of ADEP4, revealing ADEP4 binding to ClpP in the activated state. These results confirm that the anti-enterococcal activity of ADEP4 occurs through ClpP activation. In killing curve assays, ADEP4 was found to be bactericidal against stationary-phase vancomycin-resistant E. faecalis (VRE) strain V583, and resistance development was prevented when ADEP4 was combined with multiple classes of approved antibiotics. ADEP4 in combination with partnering antibiotics also eradicated mature VRE biofilms within 72 h of treatment. Biofilm killing with ADEP4 antibiotic combinations was superior to that with the clinically used combinations ampicillin-gentamicin and ampicillin-daptomycin. In a murine peritoneal septicemia model, ADEP4 alone was as effective as ampicillin. ADEP4 coadministered with ampicillin was significantly more effective than either drug alone. These data suggest that ClpP-activating antibiotics may be useful for treating enterococcal infections.

Recombinant human erythropoietin (rHuEPO) is used effectively in the treatment of various anemic disorders. Belgrade rat is a useful animal model of anemia caused by defect in iron utilization. The objective of the present study was to investigate the dynamics of erythropoietic biomarkers in Belgrade rats receiving rHuEPO. Pharmacokinetics of rHuEPO was evaluated in Belgrade rats and normal rats after intravenous administration of single doses of the drug (100 and 1350 IU/kg). Pharmacodynamic biomarkers included levels of red blood cells, hemoglobin, and reticulocytes following administration of a single intravenous dose of rHuEPO (100 IU/kg). Red blood cell survival was assessed after treatment with rHuEPO (450 IU/kg), three times a week for 2 weeks. It was found that rHuEPO exhibited non-linear pharmacokinetics in both Belgrade and control rats. At the low dose, plasma concentrations and AUC (area under the curve) were significantly lower while clearance and volume of distribution were higher in Belgrade rats (p < 0.05). At the higher dose, there was no difference in pharmacokinetics between the two groups. Erythropoietic effect of rHuEPO was negligible in Belgrade rats at the dose of 100 IU/kg whereas all studied erythropoietic biomarkers were increased in normal rats. The levels of red blood cells, hemoglobin were significantly lower whereas the percentage of reticulocytes was higher in Belgrade rats compared to that in normal rats (p < 0.05). RHuEPO increased red blood cell survival in both animal groups. In conclusion, rHuEPO effect on erythropoietic biomarkers was stronger in normal rats than Belgrade rats at the studied doses. The findings from this study may provide further insights into understanding of anemic disorders resulting from mutations in the divalent metal transporter.

Comprehension of the pharmacokinetics (PK) and pharmacodynamics (PD) of Antibody-drug Conjugates (ADCs) can be challenging as it requires integration of the information stemming from various moieties (i.e. the antibody, the drug, and the conjugate). Computational modeling provides an excellent tool to overcome these challenges by providing an opportunity to integrate all the available information within a mathematical framework. With an ever-increasing pipeline of more than 60 ADC molecules currently in the clinic, plenty of resources and time are invested towards discerning some key questions associated with PK, efficacy, and toxicity of the most promising candidates. In order to streamline the process of finding the answers to these questions and to expedite the development of ADCs, mathematical modeling and simulation (M&S) can be employed at different stages of ADC development. Successful application of this tool can not only enhance the scientific understanding of the processes underlying PK-PD of ADCs but can also provide comprehensive model-derived outcomes that can help accelerate the decision-making process. Within this book chapter, we have discussed an array of different PK-PD models and modeling strategies that could be employed at discovery, preclinical, or clinical stages, to make rational decisions for the development of ADCs. In addition, suitable examples from the literature are discussed where M&S has been utilized to make key go/no-go decisions.

OBJECTIVES Metronidazole, a mainstay treatment for Clostridium difficile infection (CDI), is often ineffective for severe CDI. Whilst this is thought to arise from suboptimal levels of metronidazole in the colon due to rapid absorption, empirical validation is lacking. In contrast, reutericyclin, an antibacterial tetramic acid from Lactobacillus reuteri, concentrates in the gastrointestinal tract. In this study, we modified metronidazole with reutericyclin's tetramic acid motif to obtain non-absorbed compounds, enabling assessment of the impact of pharmacokinetics on treatment outcomes. METHODS A series of metronidazole-bearing tetramic acid substituents were synthesized and evaluated in terms of anti-C. difficile activities, gastric permeability, in vivo pharmacokinetics, efficacy in the hamster model of CDI and mode of action. RESULTS Most compounds were absorbed less than metronidazole in cell-based Caco-2 permeability assays. In hamsters, lead compounds compartmentalized in the colon rather than the bloodstream with negligible levels detected in the blood, in direct contrast with metronidazole, which was rapidly absorbed into the blood and was undetectable in caecum. Accordingly, four leads were more efficacious (P

Prediction of human pharmacokinetics (PK) can be challenging for monoclonal antibodies (mAbs) exhibiting target-mediated drug disposition (TMDD). In this study, we performed a quantitative analysis of a diverse set of six mAbs exhibiting TMDD to explore translational rules that can be utilized to predict human PK. A TMDD model with rapid-binding approximation was utilized to fit PK and PD (i.e., free and/or total target levels) data, and average absolute fold error (AAFE) was calculated for each model parameter. Based on the comparative analysis, translational rules were developed and applied to a test antibody not included in the original analysis. AAFE of less than two-fold was observed between monkey and human for baseline target levels (R 0), body-weight (BW) normalized central elimination rate (K el/BW(-0.25)) and central volume (V c/BW(1.0)). AAFE of less than three-fold was estimated for the binding affinity constant (K D). The other four parameters, i.e., complex turnover rate (K int), target turnover rate (K deg), central to peripheral distribution rate constant (K pt) and peripheral to central rate constant (K tp) were poorly correlated between monkey and human. The projected human PK of test antibody based on the translation rules was in good agreement with the observed nonlinear PK. In conclusion, we recommend a TMDD model-based prediction approach that integrates in vitro human biomeasures and in vivo preclinical data using translation rules developed in this study.

The main objective of this work was to understand and mathematically characterize the cellular disposition of a tool antibody-drug conjugate (ADC), trastuzumab-valine-citrulline-monomethyl auristatin E (T-vc-MMAE). Toward this goal, three different analytical methods were developed to measure the concentrations of different ADC-related analytes in the media and cell lysate. A liquid chromatography-tandem mass spectrometry method was developed to quantify unconjugated drug (i.e., MMAE) concentrations, a forced deconjugation method was developed to quantify total drug concentrations, and an enzyme-linked immunosorbent assay method was developed to quantify total antibody (i.e., trastuzumab) concentrations. Cellular disposition studies were conducted in low-HER2-(GFP-MCF7) and high-HER2-expressing (N87) cell lines, following continuous or 2-hour exposure to MMAE and T-vc-MMAE. Similar intracellular accumulation of MMAE was observed between two cell lines following incubation with plain MMAE. However, when incubated with T-vc-MMAE, much higher intracellular exposures of unconjugated drug, total drug, and total antibody were observed in N87 cells compared with GFP-MCF7 cells. A novel single-cell disposition model was developed to simultaneously characterize in vitro pharmacokinetics of all three analytes of the ADC in the media and cellular space. The model was able to characterize all the data well and provided robust estimates of MMAE influx rate, MMAE efflux rate, and intracellular degradation rate for T-vc-MMAE. ADC internalization and degradation rates, HER2 expression, and MMAE efflux rate were found to be the key parameters responsible for intracellular exposure to MMAE, on the basis of a global sensitivity analysis. The single-cell pharmacokinetics model for ADCs presented here is expected to provide a better framework for characterizing bystander effect of ADCs.

Here, we have presented the development of a systems pharmacokinetics-pharmacodynamics (PK-PD) model for antibody-drug conjugates (ADCs), which uses intracellular target occupancy to drive in-vivo efficacy. The model is built based on PK and efficacy data generated using Trastuzumab-Valine-Citrulline-Monomethyl Auristatin E (T-vc-MMAE) ADC in N87 (high-HER2) and GFP-MCF7 (low-HER2) tumor bearing mice. It was observed that plasma PK of all ADC analytes was similar between the two tumor models, however, total trastuzumab, unconjugated MMAE, and total MMAE exposures were &gt, 10-fold, ~1.6-fold, and ~1.8-fold higher in N87 tumors. In addition, a prolonged retention of MMAE was observed within the tumors of both the mouse models, suggesting intracellular binding of MMAE to tubulin. A systems PK model, developed by integrating single-cell PK model with tumor distribution model, was able to capture all in vivo PK data reasonably well. Intracellular occupancy of tubulin predicted by the PK model was used to drive the efficacy of ADC using a novel PK-PD model. It was found that the same set of PD parameters was able to capture MMAE induced killing of GFP-MCF7 and N87 cells in vivo. These observations highlight the benefit of adopting a systems approach for ADC and provide a robust and predictive framework for successful clinical translation of ADCs.

A mathematical model capable of accurately characterizing intracellular disposition of ADCs is essential for a priori predicting unconjugated drug concentrations inside the tumor. Towards this goal, the objectives of this manuscript were to: (1) evolve previously published cellular disposition model of ADC with more intracellular details to characterize the disposition of T-DM1 in different HER2 expressing cell lines, (2) integrate the improved cellular model with the ADC tumor disposition model to a priori predict DM1 concentrations in a preclinical tumor model, and (3) identify prominent pathways and sensitive parameters associated with intracellular activation of ADCs. The cellular disposition model was augmented by incorporating intracellular ADC degradation and passive diffusion of unconjugated drug across tumor cells. Different biomeasures and chemomeasures for T-DM1, quantified in the companion manuscript, were incorporated into the modified model of ADC to characterize in vitro pharmacokinetics of T-DM1 in three HER2+ cell lines. When the cellular model was integrated with the tumor disposition model, the model was able to a priori predict tumor DM1 concentrations in xenograft mice. Pathway analysis suggested different contribution of antigen-mediated and passive diffusion pathways for intracellular unconjugated drug exposure between in vitro and in vivo systems. Global and local sensitivity analyses revealed that non-specific deconjugation and passive diffusion of the drug across tumor cell membrane are key parameters for drug exposure inside a cell. Finally, a systems pharmacokinetic model for intracellular processing of ADCs has been proposed to highlight our current understanding about the determinants of ADC activation inside a cell.

Pretomanid (PA-824) is an important nitroimidazole antitubercular agent in late stage clinical trials. However, pretomanid is limited by poor solubility and high protein binding, which presents opportunities for improvement in its physiochemical properties. Conversely, the oxazolidinone linezolid has excellent physicochemical properties and has recently shown impressive activity for the treatment of drug resistant tuberculosis. In this study we explore if incorporation of the outer ring elements found in first and second generation oxazolidinones into the nitroimidazole core of pretomanid can be used to improve its physicochemical and antitubercular properties. The synthesis of pretomanid outer oxazolidinone ring hybrids was successfully performed producing hybrids that maintained antitubercular activity and had improved in vitro physicochemical properties. Three lead compounds were identified and evaluated in a chronic model of tuberculosis infection in mice. However, the compounds lacked efficacy suggesting that portions of PA-824 tail not found in the hybrid molecules are required for in vivo efficacy.

The antibiotic spectinomycin is a potent inhibitor of bacterial protein synthesis with a unique mechanism of action and an excellent safety index, but it lacks antibacterial activity against most clinically important pathogens. A novel series of N-benzyl substituted 3'-(R)- 3'-aminomethyl-3'-hydroxy spectinomycins was developed based on a computational analysis of the aminomethyl spectinomycin binding site and structure guided synthesis. These compounds had ribosomal inhibition values comparable to spectinomycin but showed increased potency against common respiratory tract pathogens Streptococcus pneumoniae, Haemophilus influenzae, Legionella pneumophila, and Moraxella catarrhalis as well as the sexually transmitted bacteria Neisseria gonorrhoeae and Chlamydia trachomatis. Non-ribosome binding 3'-(S) isomers of the leads demonstrated weak inhibitory activity in in vitro protein translation assays and poor antibacterial activity, indicating that the antibacterial activity of the series remains on target. In addition to improved antibacterial potency, compounds also demonstrated no mammalian cytotoxicity, improved microsomal stability, and favorable pharmacokinetic properties in rats. The lead compound from the series, compound 1, exhibited excellent chemical stability, which was superior to spectinomycin and had no significant interaction with a panel of human receptors and drug metabolism enzymes suggesting low potential for adverse reactions or drug-drug interactions in vivo. Compound 1 was active in vitro against a panel of penicillin, macrolide, and cephalosporin resistant S. pneumoniae clinical isolates and cured mice of fatal pneumococcal pneumonia and sepsis at a dose of 5 mg/kg. Together, these studies indicate N-benzyl aminomethyl spectinomycins possess suitable properties for further development as novel antibacterial agents to treat drug resistant respiratory tract and sexually transmitted bacterial infections.

In an effort to develop new fluoroquinolones, we synthesized eight compounds and tested them against a panel of bacteria. The design of these compounds was guided by the introduction of the isothiazoloquinolone motif. The three most active compounds in this series, 8-10, demonstrated good antibacterial activity against methicillin-sensitive Staphylococcus aureus and healthcare-acquired methicillin-resistant Staphylococcus aureus (MIC 0.62-6.3 µg/mL). Further, when these three active compounds were tested for their inhibitory effects on bacterial enzymes, compound 9 was the most effective agent exhibiting IC50 values of 33.9 and 116.5 μM in the S. aureus deoxyribonucleic acid (DNA) gyrase supercoiling and topoisomerase IV decatenation assays, respectively.

Characterization and prediction of the pharmacokinetics (PK) and pharmacodynamics (PD) of Antibody-Drug Conjugates (ADCs) is challenging, since it requires simultaneous quantitative understanding about the PK-PD properties of three different molecular species i.e., the monoclonal antibody, the drug, and the conjugate. Mathematical modeling and simulation provides an excellent tool to overcome these challenges, as it can simultaneously integrate the PK-PD of ADCs and their components in a quantitative manner. Additionally, the computational PK-PD models can also serve as a cornerstone for the model-based drug development and preclinical-to-clinical translation of ADCs. To provide an overview of this subject matter, this manuscript reviews the PK-PD models applicable to ADCs. Additionally, the usage of these models during different drug development stages (i.e., discovery, preclinical development, and clinical development) is also emphasized. The importance of PK-PD modeling and simulation in making rationale go/no-go decisions throughout the drug development process is also highlighted. There is an array of PK-PD models available, ranging from the systems models specifically developed for ADCs to the empirical models applicable to all chemotherapeutic agents, which one can employ for ADCs. The decision about which model to choose depends on the questions to be answered, time at hand, and resources available.

Whilst the development of membrane-active antibiotics is now an attractive therapeutic concept, progress in this area is disadvantaged by poor knowledge of the structure-activity relationship (SAR) required for optimizing molecules to selectively target bacteria. This prompted us to explore the SAR of the Lactobacillus reuteri membrane-active antibiotic reutericyclin, modifying three key positions about its tetramic acid core. The SAR revealed that lipophilic analogs were generally more active against Gram-positive pathogens, but introduction of polar and charged substituents diminished their activity. This was confirmed by cytometric assays showing that inactive compounds failed to dissipate the membrane potential. Radiolabeled substrate assays indicated that dissipation of the membrane potential by active reutericyclins correlated with inhibition of macromolecular synthesis in cells. However, compounds with good antibacterial activities also showed cytotoxicity against Vero cells and hemolytic activity. Although this study highlights the challenge of optimizing membrane-active antibiotics, it shows that by increasing antibacterial potency the selectivity index could be widened, allowing use of lower non-cytotoxic doses.

The reductively activated nitroaromatic class of antimicrobials, which include nitroimidazole and the more metabolically labile nitrofuran antitubercular agents, have demonstrated some potential for development as therapeutics against dormant TB bacilli. In previous studies, the pharmacokinetic properties of nitrofuranyl isoxazolines were improved by incorporation of the outer ring elements of the antitubercular nitroimidazole OPC-67683. This successfully increased stability of the resulting pentacyclic nitrofuran lead compound Lee1106 (referred to herein as 9a). In the current study, we report the synthesis and antimicrobial properties of 9a and panel of 9a analogs, which were developed to increase oral bioavailability. These hybrid nitrofurans remained potent inhibitors of Mycobacterium tuberculosis with favorable selectivity indices (>150) and a narrow spectrum of activity. In vivo, the pentacyclic nitrofuran compounds showed long half-lives and high volumes of distribution. Based on pharmacokinetic testing and lack of toxicity in vivo, 9a remained the series lead. 9a exerted a lengthy post antibiotic effect and was highly active against nonreplicating M. tuberculosis grown under hypoxia. 9a showed a low potential for cross resistance to current antitubercular agents, and a mechanism of activation distinct from pre-clinical tuberculosis candidates PA-824 and OPC-67683. Together these studies show that 9a is a nanomolar inhibitor of actively growing as well as nonreplicating M. tuberculosis.

DYRK-family kinases employ an intramolecular mechanism to autophosphorylate a critical tyrosine residue in the activation loop. Once phosphorylated, DYRKs lose tyrosine kinase activity and function as serine/threonine kinases. DYRKs have been characterized in organisms from yeast to human; however, all entities belong to the Unikont supergroup, only one of five eukaryotic supergroups. To assess the evolutionary age and conservation of the DYRK intramolecular kinase-activation mechanism, we surveyed 21 genomes representing four of the five eukaryotic supergroups for the presence of DYRKs. We also analyzed the activation mechanism of the sole DYRK (class 2 DYRK) present in Trypanosoma brucei (TbDYRK2), a member of the excavate supergroup and separated from Drosophila by ∼850 million years. Bioinformatics showed the DYRKs clustering into five known subfamilies, class 1, class 2, Yaks, HIPKs and Prp4s. Only class 2 DYRKs were present in all four supergroups. These diverse class 2 DYRKs also exhibited conservation of N-terminal NAPA regions located outside of the kinase domain, and were shown to have an essential role in activation loop autophosphorylation of Drosophila DmDYRK2. Class 2 TbDYRK2 required the activation loop tyrosine conserved in other DYRKs, the NAPA regions were critical for this autophosphorylation event, and the NAPA-regions of Trypanosoma and human DYRK2 complemented autophosphorylation by the kinase domain of DmDYRK2 in trans. Finally, sequential deletion analysis was used to further define the minimal region required for trans-complementation. Our analysis provides strong evidence that class 2 DYRKs were present in the primordial or root eukaryote, and suggest this subgroup may be the oldest, founding member of the DYRK family. The conservation of activation loop autophosphorylation demonstrates that kinase self-activation mechanisms are also primitive.