A metabolic-dysfunction associated steatotic liver acinus biomimetic induces pancreatic islet dysfunction in a coupled microphysiology system.

Preclinical and clinical studies suggest that lipid-induced hepatic insulin resistance is a primary defect that predisposes to dysfunction in pancreatic islets, implicating a perturbed liver-pancreas axis underlying the comorbidity of T2DM and MASLD. To investigate this hypothesis, we developed a human biomimetic microphysiological system (MPS) coupling our vascularized liver acinus MPS (vLAMPS) with primary islets on a chip (PANIS) enabling MASLD progression and islet dysfunction to be quantitatively assessed. The modular design of this system (vLAMPS-PANIS) allows intra-organ and inter-organ dysregulation to be deconvoluted. When compared to normal fasting (NF) conditions, under early metabolic syndrome (EMS) conditions, the standalone vLAMPS exhibited characteristics of early stage MASLD, while no significant differences were observed in the standalone PANIS. In contrast, with EMS, the coupled vLAMPS-PANIS exhibited a perturbed islet-specific secretome and a significantly dysregulated glucose stimulated insulin secretion (GSIS) response implicating direct signaling from the dysregulated liver acinus to the islets. Correlations between several pairs of a vLAMPS-derived and a PANIS-derived secreted factors were significantly altered under EMS, as compared to NF conditions, mechanistically connecting MASLD and T2DM associated hepatic factors with islet-derived GLP-1 synthesis and regulation. Since vLAMPS-PANIS is compatible with patient-specific iPSCs, this platform represents an important step towards addressing patient heterogeneity, identifying complex disease mechanisms, and advancing precision medicine.

Comparison of Wild-Type and High-risk PNPLA3 variants in a Human Biomimetic Liver Microphysiology System for Metabolic Dysfunction-associated Steatotic Liver Disease Precision Therapy.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a worldwide health epidemic with a global occurrence of approximately 30%. The pathogenesis of MASLD is a complex, multisystem disorder driven by multiple factors including genetics, lifestyle, and the environment. Patient heterogeneity presents challenges for developing MASLD therapeutics, creation of patient cohorts for clinical trials and optimization of therapeutic strategies for specific patient cohorts. Implementing pre-clinical experimental models for drug development creates a significant challenge as simple in vitro systems and animal models do not fully recapitulate critical steps in the pathogenesis and the complexity of MASLD progression. To address this, we implemented a precision medicine strategy that couples the use of our liver acinus microphysiology system (LAMPS) constructed with patient-derived primary cells. We investigated the MASLD-associated genetic variant PNPLA3 rs738409 (I148M variant) in primary hepatocytes, as it is associated with MASLD progression. We constructed LAMPS with genotyped wild type and variant PNPLA3 hepatocytes together with key non-parenchymal cells and quantified the reproducibility of the model. We altered media components to mimic blood chemistries, including insulin, glucose, free fatty acids, and immune activating molecules to reflect normal fasting (NF), early metabolic syndrome (EMS) and late metabolic syndrome (LMS) conditions. Finally, we investigated the response to treatment with resmetirom, an approved drug for metabolic syndrome-associated steatohepatitis (MASH), the progressive form of MASLD. This study using primary cells serves as a benchmark for studies using patient biomimetic twins constructed with patient iPSC-derived liver cells using a panel of reproducible metrics. We observed increased steatosis, immune activation, stellate cell activation and secretion of pro-fibrotic markers in the PNPLA3 GG variant compared to wild type CC LAMPS, consistent with the clinical characterization of this variant. We also observed greater resmetirom efficacy in PNPLA3 wild type CC LAMPS compared to the GG variant in multiple MASLD metrics including steatosis, stellate cell activation and the secretion of pro-fibrotic markers. In conclusion, our study demonstrates the capability of the LAMPS platform for the development of MASLD precision therapeutics, enrichment of patient cohorts for clinical trials, and optimization of therapeutic strategies for patient subgroups with different clinical traits and disease stages.

Validation of a high throughput screening assay to identify small molecules that target the eukaryotic replicative helicase.

Mcm2-7 is the catalytic core of the eukaryotic replicative helicase, which together with CDC45 and the GINS complex unwind parental DNA to generate templates for DNA polymerase. Being a highly regulated and complex enzyme that operates via an incompletely understood multi-step mechanism, molecular probes of Mcm2-7 that interrogate specific mechanistic steps would be useful tools for research and potential future chemotherapy. Based upon a synthetic lethal approach, we previously developed a budding yeast multivariate cell-based high throughput screening (HTS) assay to identify putative Mcm inhibitors by their ability to specifically cause a growth defect in an mcm mutant relative to a wild-type strain[1]. Here, as proof of concept, we used this assay to screen a 1280-member compound library (LOPAC) for potential Mcm2-7 inhibitors. Primary screening and dose-dependent retesting identified twelve compounds from this library that specifically inhibited the growth of the Mcm mutant relative to the corresponding wild-type strain (0.9 % hit rate). Secondary assays were employed to rule out non-specific DNA damaging agents, establish direct protein-ligand interaction via biophysical methods, and verify in vivo DNA replication inhibition via fluorescence activated cell sorter analysis (FACS). We identified one agent (ß-carboline-3-carboxylic acid N-methylamide, CMA) that physically bound to the purified Mcm2-7 complex (Kdapp119 µM), and at slightly higher concentrations specifically blocked S-phase cell cycle progression of the wild-type strain. In total, identification of Mcm2-7 as a CMA target validates our synthetic lethal HTS assay paradigm as a tool to identify chemical probes for the Mcm2-7 replicative helicase.

A systems-level study reveals host-targeted repurposable drugs against SARS-CoV-2 infection.

Understanding the mechanism of SARS-CoV-2 infection and identifying potential therapeutics are global imperatives. Using a quantitative systems pharmacology approach, we identified a set of repurposable and investigational drugs as potential therapeutics against COVID-19. These were deduced from the gene expression signature of SARS-CoV-2-infected A549 cells screened against Connectivity Map and prioritized by network proximity analysis with respect to disease modules in the viral-host interactome. We also identified immuno-modulating compounds aiming at suppressing hyperinflammatory responses in severe COVID-19 patients, based on the transcriptome of ACE2-overexpressing A549 cells. Experiments with Vero-E6 cells infected by SARS-CoV-2, as well as independent syncytia formation assays for probing ACE2/SARS-CoV-2 spike protein-mediated cell fusion using HEK293T and Calu-3 cells, showed that several predicted compounds had inhibitory activities. Among them, salmeterol, rottlerin, and mTOR inhibitors exhibited antiviral activities in Vero-E6 cells; imipramine, linsitinib, hexylresorcinol, ezetimibe, and brompheniramine impaired viral entry. These novel findings provide new paths for broadening the repertoire of compounds pursued as therapeutics against COVID-19.

Unique integrated stress response sensors regulate cancer cell susceptibility when Hsp70 activity is compromised.

Molecular chaperones, such as Hsp70, prevent proteotoxicity and maintain homeostasis. This is perhaps most evident in cancer cells, which overexpress Hsp70 and thrive even when harboring high levels of misfolded proteins. To define the response to proteotoxic challenges, we examined adaptive responses in breast cancer cells in the presence of an Hsp70 inhibitor. We discovered that the cells bin into distinct classes based on inhibitor sensitivity. Strikingly, the most resistant cells have higher autophagy levels, and autophagy was maximally activated only in resistant cells upon Hsp70 inhibition. In turn, resistance to compromised Hsp70 function required the integrated stress response transducer, GCN2, which is commonly associated with amino acid starvation. In contrast, sensitive cells succumbed to Hsp70 inhibition by activating PERK. These data reveal an unexpected route through which breast cancer cells adapt to proteotoxic insults and position GCN2 and autophagy as complementary mechanisms to ensure survival when proteostasis is compromised.

Analysis of reproducibility and robustness of a human microfluidic four-cell liver acinus microphysiology system (LAMPS).

A human microfluidic four-cell liver acinus microphysiology system (LAMPS), was evaluated for reproducibility and robustness as a model for drug pharmacokinetics and toxicology. The model was constructed using primary human hepatocytes or human induced pluripotent stem cell (iPSC)-derived hepatocytes and 3 human cell lines for the endothelial, Kupffer and stellate cells. The model was tested in two laboratories and demonstrated to be reproducible in terms of basal function of hepatocytes, Terfenadine metabolism, and effects of Tolcapone (88 µM), Troglitazone (150 µM), and caffeine (600 µM) over 9 days in culture. Additional experiments compared basal outputs of albumin, urea, lactate dehydrogenase (LDH) and tumor necrosis factor (TNF)α, as well as drug metabolism and toxicity in the LAMPS model, and in 2D cultures seeded with either primary hepatocytes or iPSC-hepatocytes. Further experiments to study the effects of Terfenadine (10 µM), Tolcapone (88 µM), Trovafloxacin (150 µM with or without 1 µg/mL lipopolysaccharide), Troglitazone (28 µM), Rosiglitazone (0.8 µM), Pioglitazone (3 µM), and caffeine (600 µM) were carried out over 10 days. We found that both primary human hepatocytes and iPSC-derived hepatocytes in 3D culture maintained excellent basal liver function and Terfenadine metabolism over 10 days compared the same cells in 2D cultures. In 2D, non-overlay monolayer cultures, both cell types lost hepatocyte phenotypes after 48 h. With respect to drug effects, both cell types demonstrated comparable and more human-relevant effects in LAMPS, as compared to 2D cultures. Overall, these studies show that LAMPS is a robust and reproducible in vitro liver model, comparable in performance when seeded with either primary human hepatocytes or iPSC-derived hepatocytes, and more physiologically and clinically relevant than 2D monolayer cultures.

Pharmacological clearance of misfolded rhodopsin for the treatment of RHO-associated retinitis pigmentosa.

Rhodopsin mutation and misfolding is a common cause of autosomal dominant retinitis pigmentosa (RP). Using a luciferase reporter assay, we undertook a small-molecule high-throughput screening (HTS) of 68, 979 compounds and identified nine compounds that selectively reduced the misfolded P23H rhodopsin without an effect on the wild type (WT) rhodopsin protein. Further, we found five of these compounds, including methotrexate (MTX), promoted P23H rhodopsin degradation that also cleared out other misfolded rhodopsin mutant proteins. We showed MTX increased P23H rhodopsin degradation via the lysosomal but not the proteasomal pathway. Importantly, one intravitreal injection (IVI) of 25 pmol MTX increased electroretinogram (ERG) response and rhodopsin level in the retinae of RhoP23H/+ knock-in mice at 1 month of age. Additionally, four weekly IVIs increased the photoreceptor cell number in the retinae of RhoP23H/+ mice compared to vehicle control. Our study indicates a therapeutic potential of repurposing MTX for the treatment of rhodopsin-associated RP.

Targeting NAD+ Biosynthesis Overcomes Panobinostat and Bortezomib-Induced Malignant Glioma Resistance.

To improve therapeutic responses in patients with glioma, new combination therapies that exploit a mechanistic understanding of the inevitable emergence of drug resistance are needed. Intratumoral heterogeneity enables a low barrier to resistance in individual patients with glioma. We reasoned that targeting two or more fundamental processes that gliomas are particularly dependent upon could result in pleiotropic effects that would reduce the diversity of resistant subpopulations allowing convergence to a more robust therapeutic strategy. In contrast to the cytostatic responses observed with each drug alone, the combination of the histone deacetylase inhibitor panobinostat and the proteasome inhibitor bortezomib synergistically induced apoptosis of adult and pediatric glioma cell lines at clinically achievable doses. Resistance that developed was examined using RNA-sequencing and pharmacologic screening of resistant versus drug-naïve cells. Quinolinic acid phosphoribosyltransferase (QPRT), the rate-determining enzyme for de novo synthesis of NAD+ from tryptophan, exhibited particularly high differential gene expression in resistant U87 cells and protein expression in all resistant lines tested. Reducing QPRT expression reversed resistance, suggesting that QPRT is a selective and targetable dependency for the panobinostat-bortezomib resistance phenotype. Pharmacologic inhibition of either NAD+ biosynthesis or processes such as DNA repair that consume NAD+ or their simultaneous inhibition with drug combinations, specifically enhanced apoptosis in treatment-resistant cells. Concomitantly, de novo vulnerabilities to known drugs were observed. IMPLICATIONS: These data provide new insights into mechanisms of treatment resistance in gliomas, hold promise for targeting recurrent disease, and provide a potential strategy for further exploration of next-generation inhibitors.

Applications of the microphysiology systems database for experimental ADME-Tox and disease models.

To accelerate the development and application of Microphysiological Systems (MPS) in biomedical research and drug discovery/development, a centralized resource is required to provide the detailed design, application, and performance data that enables industry and research scientists to select, optimize, and/or develop new MPS solutions, as well as to harness data from MPS models. We have previously implemented an open source Microphysiology Systems Database (MPS-Db), with a simple icon driven interface, as a resource for MPS researchers and drug discovery/development scientists (https://mps.csb.pitt.edu). The MPS-Db captures and aggregates data from MPS, ranging from static microplate models to integrated, multi-organ microfluidic models, and associates those data with reference data from chemical, biochemical, pre-clinical, clinical and post-marketing sources to support the design, development, validation, application and interpretation of the models. The MPS-Db enables users to manage their multifactor, multichip studies, then upload, analyze, review, computationally model and share data. Here we discuss how the sharing of MPS study data in the MS-Db is under user control and can be kept private to the individual user, shared with a select group of collaborators, or be made accessible to the general scientific community. We also present a test case using our liver acinus MPS model (LAMPS) as an example and discuss the use of the MPS-Db in managing, designing, and analyzing MPS study data, assessing the reproducibility of MPS models, and evaluating the concordance of MPS model results with clinical findings. We introduce the Disease Portal module with links to resources for the design of MPS disease models and studies and discuss the integration of computational models for the prediction of PK/PD and disease pathways using data generated from MPS models.

Mutant huntingtin disrupts mitochondrial proteostasis by interacting with TIM23.

Mutant huntingtin (mHTT), the causative protein in Huntington's disease (HD), associates with the translocase of mitochondrial inner membrane 23 (TIM23) complex, resulting in inhibition of synaptic mitochondrial protein import first detected in presymptomatic HD mice. The early timing of this event suggests that it is a relevant and direct pathophysiologic consequence of mHTT expression. We show that, of the 4 TIM23 complex proteins, mHTT specifically binds to the TIM23 subunit and that full-length wild-type huntingtin (wtHTT) and mHTT reside in the mitochondrial intermembrane space. We investigated differences in mitochondrial proteome between wtHTT and mHTT cells and found numerous proteomic disparities between mHTT and wtHTT mitochondria. We validated these data by quantitative immunoblotting in striatal cell lines and human HD brain tissue. The level of soluble matrix mitochondrial proteins imported through the TIM23 complex is lower in mHTT-expressing cell lines and brain tissues of HD patients compared with controls. In mHTT-expressing cell lines, membrane-bound TIM23-imported proteins have lower intramitochondrial levels, whereas inner membrane multispan proteins that are imported via the TIM22 pathway and proteins integrated into the outer membrane generally remain unchanged. In summary, we show that, in mitochondria, huntingtin is located in the intermembrane space, that mHTT binds with high-affinity to TIM23, and that mitochondria from mHTT-expressing cells and brain tissues of HD patients have reduced levels of nuclearly encoded proteins imported through TIM23. These data demonstrate the mechanism and biological significance of mHTT-mediated inhibition of mitochondrial protein import, a mechanism likely broadly relevant to other neurodegenerative diseases.

Harnessing Human Microphysiology Systems as Key Experimental Models for Quantitative Systems Pharmacology.

Two technologies that have emerged in the last decade offer a new paradigm for modern pharmacology, as well as drug discovery and development. Quantitative systems pharmacology (QSP) is a complementary approach to traditional, target-centric pharmacology and drug discovery and is based on an iterative application of computational and systems biology methods with multiscale experimental methods, both of which include models of ADME-Tox and disease. QSP has emerged as a new approach due to the low efficiency of success in developing therapeutics based on the existing target-centric paradigm. Likewise, human microphysiology systems (MPS) are experimental models complementary to existing animal models and are based on the use of human primary cells, adult stem cells, and/or induced pluripotent stem cells (iPSCs) to mimic human tissues and organ functions/structures involved in disease and ADME-Tox. Human MPS experimental models have been developed to address the relatively low concordance of human disease and ADME-Tox with engineered, experimental animal models of disease. The integration of the QSP paradigm with the use of human MPS has the potential to enhance the process of drug discovery and development.

A High-Throughput Assay for DNA Replication Inhibitors Based upon Multivariate Analysis of Yeast Growth Kinetics.

Mcm2-7 is the molecular motor of eukaryotic replicative helicase, and the regulation of this complex is a major focus of cellular S-phase regulation. Despite its cellular importance, few small-molecule inhibitors of this complex are known. Based upon our genetic analysis of synthetic growth defects between mcm alleles and a range of other alleles, we have developed a high-throughput screening (HTS) assay using a well-characterized mcm mutant (containing the mcm2DENQ allele) to identify small molecules that replicate such synthetic growth defects. During assay development, we found that aphidicolin (inhibitor of DNA polymerase alpha) and XL413 (inhibitor of the DNA replication-dependent kinase CDC7) preferentially inhibited growth of the mcm2DENQ strain relative to the wild-type parental strain. However, as both strains demonstrated some degree of growth inhibition with these compounds, small and variable assay windows can result. To increase assay sensitivity and reproducibility, we developed a strategy combining the analysis of cell growth kinetics with linear discriminant analysis (LDA). We found that LDA greatly improved assay performance and captured a greater range of synthetic growth inhibition phenotypes, yielding a versatile analysis platform conforming to HTS requirements.

A Quantitative Systems Pharmacology Approach to Infer Pathways Involved in Complex Disease Phenotypes.

Designing effective therapeutic strategies for complex diseases such as cancer and neurodegeneration that involve tissue context-specific interactions among multiple gene products presents a major challenge for precision medicine. Safe and selective pharmacological modulation of individual molecular entities associated with a disease often fails to provide efficacy in the clinic. Thus, development of optimized therapeutic strategies for individual patients with complex diseases requires a more comprehensive, systems-level understanding of disease progression. Quantitative systems pharmacology (QSP) is an approach to drug discovery that integrates computational and experimental methods to understand the molecular pathogenesis of a disease at the systems level more completely. Described here is the chemogenomic component of QSP for the inference of biological pathways involved in the modulation of the disease phenotype. The approach involves testing sets of compounds of diverse mechanisms of action in a disease-relevant phenotypic assay, and using the mechanistic information known for the active compounds, to infer pathways and networks associated with the phenotype. The example used here is for monogenic Huntington's disease (HD), which due to the pleiotropic nature of the mutant phenotype has a complex pathogenesis. The overall approach, however, is applicable to any complex disease.

Integrating Analysis of Cellular Heterogeneity in High-Content Dose-Response Studies.

Heterogeneity is a complex property of cellular systems and therefore presents challenges to the reliable identification and characterization. Large-scale biology projects may span many months, requiring a systematic approach to quality control to track reproducibility and correct for instrumental variation and assay drift that could mask biological heterogeneity and preclude comparisons of heterogeneity between runs or even between plates. However, presently there is no standard approach to the tracking and analysis of heterogeneity. Previously, we demonstrated the use of the Kolmogorov-Smirnov statistic as a metric for monitoring the reproducibility of heterogeneity in a screen and described the use of three heterogeneity indices as a means to characterize, filter, and browse cellular heterogeneity in big data sets (Gough et al., Methods 96:12-26, 2016). In this chapter, we present a detailed method for integrating the analysis of cellular heterogeneity in assay development, validation, screening, and post screen. Importantly, we provide a detailed method for quality control, to normalize cellular data, track heterogeneity over time, and analyze heterogeneity in big data sets, along with software tools to assist in that process. The example screen for this method is from an HCS project, but the approach applies equally to other experimental methods that measure populations of cells.

Connecting Neuronal Cell Protective Pathways and Drug Combinations in a Huntington's Disease Model through the Application of Quantitative Systems Pharmacology.

Quantitative Systems Pharmacology (QSP) is a drug discovery approach that integrates computational and experimental methods in an iterative way to gain a comprehensive, unbiased understanding of disease processes to inform effective therapeutic strategies. We report the implementation of QSP to Huntington's Disease, with the application of a chemogenomics platform to identify strategies to protect neuronal cells from mutant huntingtin induced death. Using the STHdh Q111 cell model, we investigated the protective effects of small molecule probes having diverse canonical modes-of-action to infer pathways of neuronal cell protection connected to drug mechanism. Several mechanistically diverse protective probes were identified, most of which showed less than 50% efficacy. Specific combinations of these probes were synergistic in enhancing efficacy. Computational analysis of these probes revealed a convergence of pathways indicating activation of PKA. Analysis of phospho-PKA levels showed lower cytoplasmic levels in STHdh Q111 cells compared to wild type STHdh Q7 cells, and these levels were increased by several of the protective compounds. Pharmacological inhibition of PKA activity reduced protection supporting the hypothesis that protection may be working, in part, through activation of the PKA network. The systems-level studies described here can be broadly applied to any discovery strategy involving small molecule modulation of disease phenotype.

Comparison of three cell-based drug screening platforms for HSV-1 infection.

Acyclovir (ACV) and its derivatives have been highly effective for treating recurrent, lytic infections with Herpes Simplex Virus, type 1 (HSV-1), but searches for additional antiviral drugs are motivated by recent reports of resistance to ACV, particularly among immunocompromised patients. In addition, the relative neurotoxicity of ACV and its inability to prevent neurological sequelae among HSV-1 encephalitis survivors compel searches for new drugs to treat HSV-1 infections of the central nervous system (CNS). Primary drug screens for neurotropic viruses like HSV-1 typically utilize non-neuronal cell lines, but they may miss drugs that have neuron specific antiviral effects. Therefore, we compared the effects of a panel of conventional and novel anti-herpetic compounds in monkey epithelial (Vero) cells, human induced pluripotent stem cells (hiPSCs)-derived neural progenitor cells (NPCs) and hiPSC-derived neurons (N = 73 drugs). While the profiles of activity for the majority of the drugs were similar in all three tissues, Vero cells were less likely than NPCs to identify drugs with substantial inhibitory activity in hiPSC-derived neurons. We discuss the relative merits of each cell type for antiviral drug screens against neuronal infections with HSV-1.

Biologically Relevant Heterogeneity: Metrics and Practical Insights.

Heterogeneity is a fundamental property of biological systems at all scales that must be addressed in a wide range of biomedical applications, including basic biomedical research, drug discovery, diagnostics, and the implementation of precision medicine. There are a number of published approaches to characterizing heterogeneity in cells in vitro and in tissue sections. However, there are no generally accepted approaches for the detection and quantitation of heterogeneity that can be applied in a relatively high-throughput workflow. This review and perspective emphasizes the experimental methods that capture multiplexed cell-level data, as well as the need for standard metrics of the spatial, temporal, and population components of heterogeneity. A recommendation is made for the adoption of a set of three heterogeneity indices that can be implemented in any high-throughput workflow to optimize the decision-making process. In addition, a pairwise mutual information method is suggested as an approach to characterizing the spatial features of heterogeneity, especially in tissue-based imaging. Furthermore, metrics for temporal heterogeneity are in the early stages of development. Example studies indicate that the analysis of functional phenotypic heterogeneity can be exploited to guide decisions in the interpretation of biomedical experiments, drug discovery, diagnostics, and the design of optimal therapeutic strategies for individual patients.

Optimization of pyrazole-containing 1,2,4-triazolo-[3,4-b]thiadiazines, a new class of STAT3 pathway inhibitors.

Structure-activity relationship studies of a 1,2,4-triazolo-[3,4-b]thiadiazine scaffold, identified in an HTS campaign for selective STAT3 pathway inhibitors, determined that a pyrazole group and specific aryl substitution on the thiadiazine were necessary for activity. Improvements in potency and metabolic stability were accomplished by the introduction of an α-methyl group on the thiadiazine. Optimized compounds exhibited anti-proliferative activity, reduction of phosphorylated STAT3 levels and effects on STAT3 target genes. These compounds represent a starting point for further drug discovery efforts targeting the STAT3 pathway.

Selection of a potential diagnostic biomarker for HIV infection from a random library of non-biological synthetic peptoid oligomers.

Non-biological synthetic oligomers can serve as ligands for antibodies. We hypothesized that a random combinatorial library of synthetic poly-N-substituted glycine oligomers, or peptoids, could represent a random "shape library" in antigen space, and that some of these peptoids would be recognized by the antigen-binding pocket of disease-specific antibodies. We synthesized and screened a one bead one compound combinatorial library of peptoids, in which each bead displayed an 8-mer peptoid with ten possible different amines at each position (10(8) theoretical variants). By screening one million peptoid/beads we found 112 (approximately 1 in 10,000) that preferentially bound immunoglobulins from human sera known to be positive for anti-HIV antibodies. Reactive peptoids were then re-synthesized and rigorously evaluated in plate-based ELISAs. Four peptoids showed very good, and one showed excellent, properties for establishing a sero-diagnosis of HIV. These results demonstrate the feasibility of constructing sero-diagnostic assays for infectious diseases from libraries of random molecular shapes. In this study we sought a proof-of-principle that we could identify a potential diagnostic antibody ligand biomarker for an infectious disease in a random combinatorial library of 100 million peptoids. We believe that this is the first evidence that it is possible to develop sero-diagnostic assays - for any infectious disease - based on screening random libraries of non-biological molecular shapes.

A Perspective on Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery and the Advancement of Personalized Medicine.

Drug candidates exhibiting well-defined pharmacokinetic and pharmacodynamic profiles that are otherwise safe often fail to demonstrate proof-of-concept in phase II and III trials. Innovation in drug discovery and development has been identified as a critical need for improving the efficiency of drug discovery, especially through collaborations between academia, government agencies, and industry. To address the innovation challenge, we describe a comprehensive, unbiased, integrated, and iterative quantitative systems pharmacology (QSP)-driven drug discovery and development strategy and platform that we have implemented at the University of Pittsburgh Drug Discovery Institute. Intrinsic to QSP is its integrated use of multiscale experimental and computational methods to identify mechanisms of disease progression and to test predicted therapeutic strategies likely to achieve clinical validation for appropriate subpopulations of patients. The QSP platform can address biological heterogeneity and anticipate the evolution of resistance mechanisms, which are major challenges for drug development. The implementation of this platform is dedicated to gaining an understanding of mechanism(s) of disease progression to enable the identification of novel therapeutic strategies as well as repurposing drugs. The QSP platform will help promote the paradigm shift from reactive population-based medicine to proactive personalized medicine by focusing on the patient as the starting and the end point.