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.

Polymorphisms Associated With Metabolic Dysfunction-Associated Steatotic Liver Disease Influence the Progression of End-Stage Liver Disease.

BACKGROUND AND AIMS: Chronic liver injury that results in cirrhosis and end-stage liver disease (ESLD) causes more than 1 million deaths annually worldwide. Although the impact of genetic factors on the severity of metabolic dysfunction-associated steatotic liver disease (MASLD) and alcohol-related liver disease (ALD) has been previously studied, their contribution to the development of ESLD remains largely unexplored. METHODS: We genotyped 6 MASLD-associated polymorphisms in healthy (n = 123), metabolic dysfunction-associated steatohepatitis (MASH) (n = 145), MASLD-associated ESLD (n = 72), and ALD-associated ESLD (n = 57) cohorts and performed multinomial logistic regression to determine the combined contribution of genetic, demographic, and clinical factors to the progression of ESLD. RESULTS: Distinct sets of factors are associated with the progression to ESLD. The PNPLA3 rs738409:G and TM6SF2 rs58542926:T alleles, body mass index (BMI), age, and female sex were positively associated with progression from a healthy state to MASH. The PNPLA3 rs738409:G allele, age, male sex, and having type 2 diabetes mellitus were positively associated, while BMI was negatively associated with progression from MASH to MASLD-associated ESLD. The PNPLA3 rs738409:G and GCKR rs780094:T alleles, age, and male sex were positively associated, while BMI was negatively associated with progression from a healthy state to ALD-associated ESLD. The findings indicate that the PNPLA3 rs738409:G allele increases susceptibility to ESLD regardless of etiology, the TM6SF2 rs58542926:T allele increases susceptibility to MASH, and the GCKR rs780094:T allele increases susceptibility to ALD-associated ESLD. CONCLUSION: The PNPLA3, TM6SF2, and GCKR minor alleles influence the progression of MASLD-associated or ALD-associated ESLD. Genotyping for these variants in MASLD and ALD patients can enhance risk assessment, prompting early interventions to prevent ESLD.

Evaluation of Human Hepatocyte Drug Metabolism Carrying High-Risk or Protection-Associated Liver Disease Genetic Variants.

Metabolic-dysfunction-associated steatotic liver disease (MASLD), which affects 30 million people in the US and is anticipated to reach over 100 million by 2030, places a significant financial strain on the healthcare system. There is presently no FDA-approved treatment for MASLD despite its public health significance and financial burden. Understanding the connection between point mutations, liver enzymes, and MASLD is important for comprehending drug toxicity in healthy or diseased individuals. Multiple genetic variations have been linked to MASLD susceptibility through genome-wide association studies (GWAS), either increasing MASLD risk or protecting against it, such as PNPLA3 rs738409, MBOAT7 rs641738, GCKR rs780094, HSD17B13 rs72613567, and MTARC1 rs2642438. As the impact of genetic variants on the levels of drug-metabolizing cytochrome P450 (CYP) enzymes in human hepatocytes has not been thoroughly investigated, this study aims to describe the analysis of metabolic functions for selected phase I and phase II liver enzymes in human hepatocytes. For this purpose, fresh isolated primary hepatocytes were obtained from healthy liver donors (n = 126), and liquid chromatography-mass spectrometry (LC-MS) was performed. For the cohorts, participants were classified into minor homozygotes and nonminor homozygotes (major homozygotes + heterozygotes) for five gene polymorphisms. For phase I liver enzymes, we found a significant difference in the activity of CYP1A2 in human hepatocytes carrying MBOAT7 (p = 0.011) and of CYP2C8 in human hepatocytes carrying PNPLA3 (p = 0.004). It was also observed that the activity of CYP2C9 was significantly lower in human hepatocytes carrying HSD17B13 (p = 0.001) minor homozygous compared to nonminor homozygous. No significant difference in activity of CYP2E1, CYP2C8, CYP2D6, CYP2E1, CYP3A4, ECOD, FMO, MAO, AO, and CES2 and in any of the phase II liver enzymes between human hepatocytes carrying genetic variants for PNPLA3 rs738409, MBOAT7 rs641738, GCKR rs780094, HSD17B13 rs72613567, and MTARC1 rs2642438 were observed. These findings offer a preliminary assessment of the influence of genetic variations on drug-metabolizing cytochrome P450 (CYP) enzymes in healthy human hepatocytes, which may be useful for future drug discovery investigations.

Modeling mechanisms underlying differential inflammatory responses to COVID-19 in type 2 diabetes using a patient-derived microphysiological organ-on-a-chip system.

Background: COVID-19 pandemic has caused more than 6 million deaths worldwide. Co-morbid conditions such as Type 2 Diabetes (T2D) have increased mortality in COVID-19. With limited translatability of in vitro and small animal models to human disease, human organ-on-a-chip models are an attractive platform to model in vivo disease conditions and test potential therapeutics. Methods: T2D or non-diabetic patient-derived macrophages and human liver sinusoidal endothelial cells were seeded, along with normal hepatocytes and stellate cells in the liver-on-a-chip (LAMPS - liver acinus micro physiological system), perfused with media mimicking non-diabetic fasting or T2D (high levels of glucose, fatty acids, insulin, glucagon) states. The macrophages and endothelial cells were transduced to overexpress the SARS-CoV2-S (spike) protein with appropriate controls before their incorporation into LAMPS. Cytokine concentrations in the efflux served as a read-out of the effects of S-protein expression in the different experimental conditions (non-diabetic-LAMPS, T2D-LAMPS), including incubation with tocilizumab, an FDA-approved drug for severe COVID-19. Findings: S-protein expression in the non-diabetic LAMPS led to increased cytokines, but in the T2D-LAMPS, this was significantly amplified both in the number and magnitude of key pro-inflammatory cytokines (IL6, CCL3, IL1ß, IL2, TNFα, etc.) involved in cytokine storm syndrome (CSS), mimicking severe COVID-19 infection in T2D patients. Compared to vehicle control, tocilizumab (IL6-receptor antagonist) decreased the pro-inflammatory cytokine secretion in T2D-COVID-19-LAMPS but not in non-diabetic-COVID-19-LAMPS. Interpretation: macrophages and endothelial cells play a synergistic role in the pathophysiology of the hyper-inflammatory response seen with COVID-19 and T2D. The effect of Tocilizumab was consistent with large clinical trials that demonstrated Tocilizumab's efficacy only in critically ill patients with severe disease, providing confirmatory evidence that the T2D-COVID-19-LAMPS is a robust platform to model human in vivo pathophysiology of COVID-19 in T2D and for screening potential therapeutics.

The Combination of a Human Biomimetic Liver Microphysiology System with BIOLOGXsym, a Quantitative Systems Toxicology (QST) Modeling Platform for Macromolecules, Provides Mechanistic Understanding of Tocilizumab- and GGF2-Induced Liver Injury.

Biologics address a range of unmet clinical needs, but the occurrence of biologics-induced liver injury remains a major challenge. Development of cimaglermin alfa (GGF2) was terminated due to transient elevations in serum aminotransferases and total bilirubin. Tocilizumab has been reported to induce transient aminotransferase elevations, requiring frequent monitoring. To evaluate the clinical risk of biologics-induced liver injury, a novel quantitative systems toxicology modeling platform, BIOLOGXsym™, representing relevant liver biochemistry and the mechanistic effects of biologics on liver pathophysiology, was developed in conjunction with clinically relevant data from a human biomimetic liver microphysiology system. Phenotypic and mechanistic toxicity data and metabolomics analysis from the Liver Acinus Microphysiology System showed that tocilizumab and GGF2 increased high mobility group box 1, indicating hepatic injury and stress. Tocilizumab exposure was associated with increased oxidative stress and extracellular/tissue remodeling, and GGF2 decreased bile acid secretion. BIOLOGXsym simulations, leveraging the in vivo exposure predicted by physiologically-based pharmacokinetic modeling and mechanistic toxicity data from the Liver Acinus Microphysiology System, reproduced the clinically observed liver signals of tocilizumab and GGF2, demonstrating that mechanistic toxicity data from microphysiology systems can be successfully integrated into a quantitative systems toxicology model to identify liabilities of biologics-induced liver injury and provide mechanistic insights into observed liver safety signals.

Biofabrication of synthetic human liver tissue with advanced programmable functions.

Advances in cellular engineering, as well as gene, and cell therapy, may be used to produce human tissues with programmable genetically enhanced functions designed to model and/or treat specific diseases. Fabrication of synthetic human liver tissue with these programmable functions has not been described. By generating human iPSCs with target gene expression controlled by a guide RNA-directed CRISPR-Cas9 synergistic-activation-mediator, we produced synthetic human liver tissues with programmable functions. Such iPSCs were guide-RNA-treated to enhance expression of the clinically relevant CYP3A4 and UGT1A1 genes, and after hepatocyte-directed differentiation, cells demonstrated enhanced functions compared to those found in primary human hepatocytes. We then generated human liver tissue with these synthetic human iPSC-derived hepatocytes (iHeps) and other non-parenchymal cells demonstrating advanced programmable functions. Fabrication of synthetic human liver tissue with modifiable functional genetic programs may be a useful tool for drug discovery, investigating biology, and potentially creating bioengineered organs with specialized functions.

A Quantitative Systems Pharmacology Platform Reveals NAFLD Pathophysiological States and Targeting Strategies.

Non-alcoholic fatty liver disease (NAFLD) has a high global prevalence with a heterogeneous and complex pathophysiology that presents barriers to traditional targeted therapeutic approaches. We describe an integrated quantitative systems pharmacology (QSP) platform that comprehensively and unbiasedly defines disease states, in contrast to just individual genes or pathways, that promote NAFLD progression. The QSP platform can be used to predict drugs that normalize these disease states and experimentally test predictions in a human liver acinus microphysiology system (LAMPS) that recapitulates key aspects of NAFLD. Analysis of a 182 patient-derived hepatic RNA-sequencing dataset generated 12 gene signatures mirroring these states. Screening against the LINCS L1000 database led to the identification of drugs predicted to revert these signatures and corresponding disease states. A proof-of-concept study in LAMPS demonstrated mitigation of steatosis, inflammation, and fibrosis, especially with drug combinations. Mechanistically, several structurally diverse drugs were predicted to interact with a subnetwork of nuclear receptors, including pregnane X receptor (PXR; NR1I2), that has evolved to respond to both xenobiotic and endogenous ligands and is intrinsic to NAFLD-associated transcription dysregulation. In conjunction with iPSC-derived cells, this platform has the potential for developing personalized NAFLD therapeutic strategies, informing disease mechanisms, and defining optimal cohorts of patients for clinical trials.

Biomanufacturing in low Earth orbit for regenerative medicine.

Research in low Earth orbit (LEO) has become more accessible. The 2020 Biomanufacturing in Space Symposium reviewed space-based regenerative medicine research and discussed leveraging LEO to advance biomanufacturing for regenerative medicine applications. The symposium identified areas where financial investments could stimulate advancements overcoming technical barriers. Opportunities in disease modeling, stem-cell-derived products, and biofabrication were highlighted. The symposium will initiate a roadmap to a sustainable market for regenerative medicine biomanufacturing in space. This perspective summarizes the 2020 Biomanufacturing in Space Symposium, highlights key biomanufacturing opportunities in LEO, and lays the framework for a roadmap to regenerative medicine biomanufacturing in space.

In situ functional cell phenotyping reveals microdomain networks in colorectal cancer recurrence.

Tumors are dynamic ecosystems comprising localized niches (microdomains), possessing distinct compositions and spatial configurations of cancer and non-cancer cell populations. Microdomain-specific network signaling coevolves with a continuum of cell states and functional plasticity associated with disease progression and therapeutic responses. We present LEAPH, an unsupervised machine learning algorithm for identifying cell phenotypes, which applies recursive steps of probabilistic clustering and spatial regularization to derive functional phenotypes (FPs) along a continuum. Combining LEAPH with pointwise mutual information and network biology analyses enables the discovery of outcome-associated microdomains visualized as distinct spatial configurations of heterogeneous FPs. Utilization of an immunofluorescence-based (51 biomarkers) image dataset of colorectal carcinoma primary tumors (n = 213) revealed microdomain-specific network dysregulation supporting cancer stem cell maintenance and immunosuppression that associated selectively with the recurrence phenotype. LEAPH enables an explainable artificial intelligence platform providing insights into pathophysiological mechanisms and novel drug targets to inform personalized therapeutic strategies.

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.

Inhibition of RPS6K reveals context-dependent Akt activity in luminal breast cancer cells.

Aberrant signaling through insulin (Ins) and insulin-like growth factor I (IGF1) receptors contribute to the risk and advancement of many cancer types by activating cell survival cascades. Similarities between these pathways have thus far prevented the development of pharmacological interventions that specifically target either Ins or IGF1 signaling. To identify differences in early Ins and IGF1 signaling mechanisms, we developed a dual receptor (IGF1R & InsR) computational response model. The model suggested that ribosomal protein S6 kinase (RPS6K) plays a critical role in regulating MAPK and Akt activation levels in response to Ins and IGF1 stimulation. As predicted, perturbing RPS6K kinase activity led to an increased Akt activation with Ins stimulation compared to IGF1 stimulation. Being able to discern differential downstream signaling, we can explore improved anti-IGF1R cancer therapies by eliminating the emergence of compensation mechanisms without disrupting InsR signaling.

Human biomimetic liver microphysiology systems in drug development and precision medicine.

Microphysiology systems (MPS), also called organs-on-chips and tissue chips, are miniaturized functional units of organs constructed with multiple cell types under a variety of physical and biochemical environmental cues that complement animal models as part of a new paradigm of drug discovery and development. Biomimetic human liver MPS have evolved from simpler 2D cell models, spheroids and organoids to address the increasing need to understand patient-specific mechanisms of complex and rare diseases, the response to therapeutic treatments, and the absorption, distribution, metabolism, excretion and toxicity of potential therapeutics. The parallel development and application of transdisciplinary technologies, including microfluidic devices, bioprinting, engineered matrix materials, defined physiological and pathophysiological media, patient-derived primary cells, and pluripotent stem cells as well as synthetic biology to engineer cell genes and functions, have created the potential to produce patient-specific, biomimetic MPS for detailed mechanistic studies. It is projected that success in the development and maturation of patient-derived MPS with known genotypes and fully matured adult phenotypes will lead to advanced applications in precision medicine. In this Review, we examine human biomimetic liver MPS that are designed to recapitulate the liver acinus structure and functions to enhance our knowledge of the mechanisms of disease progression and of the absorption, distribution, metabolism, excretion and toxicity of therapeutic candidates and drugs as well as to evaluate their mechanisms of action and their application in precision medicine and preclinical trials.

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.

Explainable AI (xAI) for Anatomic Pathology.

Pathologists are adopting whole slide images (WSIs) for diagnosis, thanks to recent FDA approval of WSI systems as class II medical devices. In response to new market forces and recent technology advances outside of pathology, a new field of computational pathology has emerged that applies artificial intelligence (AI) and machine learning algorithms to WSIs. Computational pathology has great potential for augmenting pathologists' accuracy and efficiency, but there are important concerns regarding trust of AI due to the opaque, black-box nature of most AI algorithms. In addition, there is a lack of consensus on how pathologists should incorporate computational pathology systems into their workflow. To address these concerns, building computational pathology systems with explainable AI (xAI) mechanisms is a powerful and transparent alternative to black-box AI models. xAI can reveal underlying causes for its decisions; this is intended to promote safety and reliability of AI for critical tasks such as pathology diagnosis. This article outlines xAI enabled applications in anatomic pathology workflow that improves efficiency and accuracy of the practice. In addition, we describe HistoMapr-Breast, an initial xAI enabled software application for breast core biopsies. HistoMapr-Breast automatically previews breast core WSIs and recognizes the regions of interest to rapidly present the key diagnostic areas in an interactive and explainable manner. We anticipate xAI will ultimately serve pathologists as an interactive computational guide for computer-assisted primary diagnosis.

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.

QuartataWeb: Integrated Chemical-Protein-Pathway Mapping for Polypharmacology and Chemogenomics.

SUMMARY: QuartataWeb is a user-friendly server developed for polypharmacological and chemogenomics analyses. Users can easily obtain information on experimentally verified (known) and computationally predicted (new) interactions between 5494 drugs and 2807 human proteins in DrugBank, and between 315 514 chemicals and 9457 human proteins in the STITCH database. In addition, QuartataWeb links targets to KEGG pathways and GO annotations, completing the bridge from drugs/chemicals to function via protein targets and cellular pathways. It allows users to query a series of chemicals, drug combinations or multiple targets, to enable multi-drug, multi-target, multi-pathway analyses, toward facilitating the design of polypharmacological treatments for complex diseases. AVAILABILITY AND IMPLEMENTATION: QuartataWeb is freely accessible at http://quartata.csb.pitt.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Improving natural product research translation: From source to clinical trial.

While great interest in health effects of natural product (NP) including dietary supplements and foods persists, promising preclinical NP research is not consistently translating into actionable clinical trial (CT) outcomes. Generally considered the gold standard for assessing safety and efficacy, CTs, especially phase III CTs, are costly and require rigorous planning to optimize the value of the information obtained. More effective bridging from NP research to CT was the goal of a September, 2018 transdisciplinary workshop. Participants emphasized that replicability and likelihood of successful translation depend on rigor in experimental design, interpretation, and reporting across the continuum of NP research. Discussions spanned good practices for NP characterization and quality control; use and interpretation of models (computational through in vivo) with strong clinical predictive validity; controls for experimental artefacts, especially for in vitro interrogation of bioactivity and mechanisms of action; rigorous assessment and interpretation of prior research; transparency in all reporting; and prioritization of research questions. Natural product clinical trials prioritized based on rigorous, convergent supporting data and current public health needs are most likely to be informative and ultimately affect public health. Thoughtful, coordinated implementation of these practices should enhance the knowledge gained from future NP research.