ACFIS 2.0: an improved web-server for fragment-based drug discovery via a dynamic screening strategy.

Drug discovery, which plays a vital role in maintaining human health, is a persistent challenge. Fragment-based drug discovery (FBDD) is one of the strategies for the discovery of novel candidate compounds. Computational tools in FBDD could help to identify potential drug leads in a cost-efficient and time-saving manner. The Auto Core Fragment in silico Screening (ACFIS) server is a well-established and effective online tool for FBDD. However, the accurate prediction of protein-fragment binding mode and affinity is still a major challenge for FBDD due to weak binding affinity. Here, we present an updated version (ACFIS 2.0), that incorporates a dynamic fragment growing strategy to consider protein flexibility. The major improvements of ACFIS 2.0 include (i) increased accuracy of hit compound identification (from 75.4% to 88.5% using the same test set), (ii) improved rationality of the protein-fragment binding mode, (iii) increased structural diversity due to expanded fragment libraries and (iv) inclusion of more comprehensive functionality for predicting molecular properties. Three successful cases of drug lead discovery using ACFIS 2.0 are described, including drugs leads to treat Parkinson's disease, cancer, and major depressive disorder. These cases demonstrate the utility of this web-based server. ACFIS 2.0 is freely available at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS2/.

Computational approaches streamlining drug discovery.

Computer-aided drug discovery has been around for decades, although the past few years have seen a tectonic shift towards embracing computational technologies in both academia and pharma. This shift is largely defined by the flood of data on ligand properties and binding to therapeutic targets and their 3D structures, abundant computing capacities and the advent of on-demand virtual libraries of drug-like small molecules in their billions. Taking full advantage of these resources requires fast computational methods for effective ligand screening. This includes structure-based virtual screening of gigascale chemical spaces, further facilitated by fast iterative screening approaches. Highly synergistic are developments in deep learning predictions of ligand properties and target activities in lieu of receptor structure. Here we review recent advances in ligand discovery technologies, their potential for reshaping the whole process of drug discovery and development, as well as the challenges they encounter. We also discuss how the rapid identification of highly diverse, potent, target-selective and drug-like ligands to protein targets can democratize the drug discovery process, presenting new opportunities for the cost-effective development of safer and more effective small-molecule treatments.

Human iPSC-Based Modeling of Central Nerve System Disorders for Drug Discovery.

A high-throughput drug screen identifies potentially promising therapeutics for clinical trials. However, limitations that persist in current disease modeling with limited physiological relevancy of human patients skew drug responses, hamper translation of clinical efficacy, and contribute to high clinical attritions. The emergence of induced pluripotent stem cell (iPSC) technology revolutionizes the paradigm of drug discovery. In particular, iPSC-based three-dimensional (3D) tissue engineering that appears as a promising vehicle of in vitro disease modeling provides more sophisticated tissue architectures and micro-environmental cues than a traditional two-dimensional (2D) culture. Here we discuss 3D based organoids/spheroids that construct the advanced modeling with evolved structural complexity, which propels drug discovery by exhibiting more human specific and diverse pathologies that are not perceived in 2D or animal models. We will then focus on various central nerve system (CNS) disease modeling using human iPSCs, leading to uncovering disease pathogenesis that guides the development of therapeutic strategies. Finally, we will address new opportunities of iPSC-assisted drug discovery with multi-disciplinary approaches from bioengineering to Omics technology. Despite technological challenges, iPSC-derived cytoarchitectures through interactions of diverse cell types mimic patients' CNS and serve as a platform for therapeutic development and personalized precision medicine.

Future perspective: high-throughput construction of new ultrasensitive cytokine and virion liquid chips for high-throughput screening (HTS) of anti-inflammatory drugs or clinical diagnosis and treatment of inflammatory diseases.

Pathogen-host cell interactions play an important role in many human infectious and inflammatory diseases. Several pathogens, including Escherichia coli (E. coli), Mycobacterium tuberculosis (M. tb), and even the recent 2019 novel coronavirus (2019-nCoV), can cause serious breathing and brain disorders, tissue injury and inflammation, leading to high rates of mortality and resulting in great loss to human physical and mental health as well as the global economy. These infectious diseases exploit the microbial and host factors to induce serious inflammatory and immunological symptoms. Thus the development of anti-inflammatory drugs targeting bacterial/viral infection is an urgent need. In previous studies, YojI-IFNAR2, YojI-IL10RA, YojI-NRP1,YojI-SIGLEC7, and YojI-MC4R membrane-protein interactions were found to mediate E. coli invasion of the blood-brain barrier (BBB), which activated the downstream anti-inflammatory proteins NACHT, LRR and PYD domains-containing protein 2(NLRP2), using a proteomic chip conjugated with cell immunofluorescence labeling. However, the studies of pathogen (bacteria/virus)-host cell interactions mediated by membrane protein interactions did not extend their principles to broad biomedical applications such as 2019-nCoV infectious disease therapy. The first part of this feature article presents in-depth analysis of the cross-talk of cellular anti-inflammatory transduction signaling among interferon membrane protein receptor II (IFNAR2), interleukin-10 receptor subunit alpha (IL-10RA), NLRP2 and [Ca2+]-dependent phospholipase A2 (PLA2G5), based on experimental results and important published studies, which lays a theoretical foundation for the high-throughput construction of the cytokine and virion solution chip. The paper then moves on to the construction of the novel GPCR recombinant herpes virion chip and virion nano-oscillators for profiling membrane protein functions, which drove the idea of constructing the new recombinant virion and cytokine liquid chips for HTS of leading drugs. Due to the different structural properties of GPCR, IFNAR2, ACE2 and Spike of 2019-nCoV, their ligands will either bind the extracellular domain of IFNAR2/ACE2/Spike or the specific loops of the GPCR on the envelope of the recombinant herpes virions to induce dynamic charge distribution changes that lead to the variable electron transition for detection. Taken together, the combined overview of two of the most innovative and exciting developments in the immunoinflammatory field provides new insight into high-throughput construction of ultrasensitive cytokine and virion liquid chips for HTS of anti-inflammatory drugs or clinical diagnosis and treatment of inflammatory diseases including infectious diseases, acute or chronic inflammation (acute gouty arthritis or rheumatoid arthritis), cardiovascular disease, atheromatosis, diabetes, obesity, tissue injury and tumors. It has significant value in the prevention and treatment of these serious and painful diseases. Graphical abstract.

Comprehensive online multicolumn two-dimensional liquid chromatography-diode array detection-mass spectrometry workflow as a framework for chromatographic screening and analysis of new drug substances.

The analysis of complex mixtures of closely related species is quickly becoming a bottleneck in the development of new drug substances, reflecting the ever-increasing complexity of both fundamental biology and the therapeutics used to treat disease. Two-dimensional liquid chromatography (2D-LC) is emerging as a powerful tool to achieve substantial improvements in peak capacity and selectivity. However, 2D-LC suffers from several limitations, including the lack of automated multicolumn setups capable of combining multiple columns in both dimensions. Herein, we report an investigation into the development and implementation of a customized online comprehensive multicolumn 2D-LC-DAD-MS setup for screening and method development purposes, as well as analysis of multicomponent biopharmaceutical mixtures. In this study, excellent chromatographic performance in terms of selectivity, peak shape, and reproducibility were achieved by combining reversed-phase (RP), strong cation exchange (SCX), strong anion exchange (SAX), and size exclusion chromatography (SEC) using sub-2-µm columns in the first dimension in conjunction with several 3.0 mm × 50 mm RP columns packed with sub-3-µm fully porous particles in the second dimension. Multiple combinations of separation modes coupled to UV and MS detection are applied to the LC × LC analysis of a protein standard mixture, intended to be representative of protein drug substances. The results reported in this study demonstrate that our automated online multicolumn 2D-LC-DAD-MS workflow can be a powerful tool for comprehensive chromatographic column screening that enables the semi-automated development of 2D-LC methods, offering the ability to streamline full visualization of sample composition for an unknown complex mixture while maximizing chromatographic orthogonality. Graphical Abstract.

Integration of micro-fractionation, high-performance liquid chromatography-ultraviolet detector-charged aerosol detector-mass spectrometry analysis and cellular dynamic mass redistribution assay to accelerate alkaloid drug discovery.

Natural products, including alkaloids, are important resources for new drugs. However, in today's high throughput screening (HTS) environment, natural product drug discovery programs are challenged for their low efficiency. In order to adapt to current HTS models, we here developed a rapid, sample-saving and miniaturized paradigm that seamlessly integrated alkaloid micro-fractionation, quantitative analysis, qualitative analysis and phenotypic screening. In the work, alkaloid samples were analyzed and fractionated on an analytical charged C18 column (150 × 4.6 mm, i.d.), and fraction qualities were determined by a charged aerosol detector (CAD). Fraction activities on dopamine D2 receptor were screened by cellular dynamic mass redistribution (DMR) assay and active fractions were further characterized by high-resolution mass spectrometry (MS). The whole workflow was first validated by mixed standard for accuracy, and then by 300 µg of Corydalis yanhusuo extract for its feasibility in complex samples. Finally, the method was applied for sample prioritization in four papaveraceae family plants and 21 compounds were predicted to be active, and Corydalis yanhusuo and Corydalis decumbens were determined as promising species for activity tracking. Overall, these results highlighted the feasibility of this miniatured and integrated model in rapid alkaloid screening. Advantages of this workflow were: first, the highly efficient separation method accelerated alkaloid fractionation; second, the analytical and biological test were conducted on the same scale; third, the quantification method ensured accurate screening on microscale; last, the combination of MS analysis and data mining strategy accelerated the decision-making process in the primary screening.

Do We have a Satisfactory Cell Viability Assay? Review of the Currently Commercially-Available Assays.

Cell-based assays are an important part of the drug discovery process and clinical research. One of the main hurdles is to design sufficiently robust assays with adequate signal to noise parameters while maintaining the inherent physiology of the cells and not interfering with the pharmacology of target being investigated. A plethora of assays that assess cell viability (or cell heath in general) are commercially available and can be classified under different categories according to their concepts and principle of reactions. The assays are valuable tools, however, suffer from a large number of limitations. Some of these limitations can be procedural or operational, but others can be critical as those related to a poor concept or the lack of proof of concept of an assay, e.g. those relying on differential permeability of dyes in-and-out of viable versus compromised cell membranes. While the assays can differentiate between dead and live cells, most, if not all, of them can just assess the relative performance of cells rather than providing a clear distinction between healthy and dying cells. The possible impact of relatively high molecular weight dyes, used in most of the assay, on cell viability has not been addressed. More innovative assays are needed, and until better alternatives are developed, setup of current cell-based studies and data interpretation should be made with the limitations in mind. Negative and positive control should be considered whenever feasible. Also, researchers should use more than one orthogonal method for better assessment of cell health.

Protocol development for discovery of angiogenesis inhibitors via automated methods using zebrafish.

Their optical clarity as larvae and embryos, small size, and high fecundity make zebrafish ideal for whole animal high throughput screening. A high-throughput drug discovery platform (HTP) has been built to perform fully automated screens of compound libraries with zebrafish embryos. A Tg(kdrl:EGFP) line, marking endothelial cell cytoplasm, was used in this work to help develop protocols and functional algorithms for the system, with the intent of screening for angiogenesis inhibitors. Indirubin 3' Monoxime (I3M), a known angiogenesis inhibitor, was used at various concentrations to validate the protocols. Consistent with previous studies, a dose dependant inhibitory effect of I3M on angiogenesis was confirmed. The methods and protocols developed here could significantly increase the throughput of drug screens, while limiting human errors. These methods are expected to facilitate the discovery of novel anti-angiogenesis compounds and can be adapted for many other applications in which samples have a good fluorescent signal.

Novel chemical starting points for drug discovery in leishmaniasis and Chagas disease.

Visceral leishmaniasis (VL) and Chagas disease (CD) are caused by kinetoplastid parasites that affect millions of people worldwide and impart a heavy burden against human health. Due to the partial efficacy and toxicity-related limitations of the existing treatments, there is an urgent need to develop novel therapies with superior efficacy and safety profiles to successfully treat these diseases. Herein we report the application of whole-cell phenotypic assays to screen a set of 150,000 compounds against Leishmania donovani, a causative agent of VL, and Trypanosoma cruzi, the causative agent of CD, with the objective of finding new starting points to develop novel drugs to effectively treat and control these diseases. The screening campaign, conducted with the purpose of global open access, identified twelve novel chemotypes with low to sub-micromolar activity against T. cruzi and/or L. donovani. We disclose these hit structures and associated activity with the goal to contribute to the drug discovery community by providing unique chemical tools to probe kinetoplastid biology and as hit-to-lead candidates for drug discovery.

HPLC-based activity profiling for pharmacologically and toxicologically relevant natural products - principles and recent examples.

CONTEXT: Discovery of pharmacologically active natural products as starting points for drug development remains important and, for reasons of consumer safety, the identification of toxicologically relevant compounds in herbal drugs. OBJECTIVE: To explain, with the aid of relevant examples from our own research, how these goals can be achieved. METHODS: An in-house technology platform comprising pre-formatted extract libraries in 96-well format, miniaturized tracking of activity in extracts via HPLC-activity profiling, structure elucidation with microprobe NMR, and in vitro and in vivo pharmacological methods were used. RESULTS: Piperine was identified as a new scaffold for allosteric GABAA receptor modulators with in vivo activity that interacts at a benzodiazepine-independent binding site. Selectivity and potency were improved by iterative optimization towards synthetic piperine analogues. Dehydroevodiamine and hortiamine from the traditional Chinese herbal drug Evodiae fructus were identified as potent hERG channel blockers in vitro. The compounds induced torsades de pointes arrhythmia in animal models. CONCLUSIONS: The allosteric binding site for piperine analogues remains to be characterized and cardiac risks of herbal drugs need to be further evaluated to ensure consumer safety.

A novel method using nuclear magnetic resonance for plasma protein binding assessment in drug discovery programs.

A new methodology based on Nuclear Magnetic Resonance (NMR) was developed to determine plasma protein binding (PPB) of drug candidates in drug discovery programs. A strong correlation was found between the attenuation of NMR signals of diverse drugs in the presence of different plasma concentrations and their fraction bound (fb) reported in the literature. Based on these results, a protocol for a rapid calculation of fb of small molecules was established. The advantage of using plasma instead of purified recombinant proteins and the possibility of pool analysis to increase throughput were also evaluated. This novel methodology proved to be very versatile, cost-effective, fast and suitable for automation. As a plus, it contemporarily provides a quality check and solubility of the compound.

Ligand fishing with cellular membrane-coated cellulose filter paper: a new method for screening of potential active compounds from natural products.

Ligand fishing is a widely used approach for screening active compounds from natural products. Recently, cell membrane (CM) as affinity ligand has been applied in ligand fishing, including cell membrane chromatography (CMC) and CM-coated magnetic bead. However, these methods possess many weaknesses, including complicated preparation processes and time-consuming operation. In this study, cheap and easily available cellulose filter paper (CFP) was selected as carrier of CM and used to fabricate a novel CM-coated CFP (CMCFP) for the first time. The type of CFP was optimized according to the amount of immobilized protein, and the immobilization of CM onto CFP by the insertion and self-fusion process was verified by confocal imaging. The CMCFP exhibited good selectivity and stability and was used for fishing potentially active compounds from extracts of Angelica dahurica. Three potentially active compounds, including bergapten, pabulenol, and imperatorin, were fished out and identified. The traditional Chinese medicine systems pharmacology database and analysis platform was used to build an active compound-target protein network, and accordingly, the gamma-aminobutyric acid receptor subunit alpha-1 (GABRA1) was deduced as potential target of CM for the active compounds of Angelica dahurica. Molecular docking was performed to evaluate the interaction between active compounds and GABRA1, and bergapten was speculated as a new potentially active compound. Compared with other methods, the fishing assay based on CMCFP was more effective, simpler, and cheaper.

A novel strategy to screen inhibitors of multiple aminoglycoside-modifying enzymes with ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry.

Resistance to aminoglycoside antibiotics occurs primarily as a result of aminoglycoside-modification enzymes (AMEs) that modify the antibiotics. In this work, a novel strategy to combat the effects of antibiotic resistance was developed by screening multiple AMEs inhibitors with ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UHPLC-QTOF MS). The method screened inhibitors of three AMEs (AAC(6')-APH(2"), AAC(6') and APH(2")) simultaneously through measuring the acetyltransferase activity and phosphotransferase activity of AAC(6')-APH(2") enzyme in a single assay. Screening inhibitors of multiple targets could greatly improve the screening efficiency at early-stages of drug discovery. In this study, enzyme reaction conditions including cosubstrate, enzyme concentration and cosubstrate concentration were optimized. The inhibition constants (Ki) for two known inhibitors, paromomycin and quercetin, were determined to be 1.23 and 20.27 µM, respectively. The assay was further validated through the determination of a high Z' factor value of 0.73. The developed assay was applied to screen a chemical library against bifunctional AAC(6')-APH(2'') enzyme. Using this assay, two pyrimidinyl indole derivatives were found to be potent, and effective AAC(6')-APH(2'') inhibitors. The assay of exploring the selective inhibitory effect on two AAC(6')-APH(2'') active sites was further performed. Two pyrimidinyl indole derivatives were found to exhibit striking inhibitory activities on AAC(6').

Rapid identification of urokinase plasminogen activator inhibitors from Traditional Chinese Medicines based on ultrafiltration, LC-MS and in silico docking.

The urokinase plasminogen activator (uPA) is regarded as the crucial trigger for plasmin generation, which is involved in several diseases especially for neoplasm metastasis. In this study, an efficient approach integrating ultrafiltration, LC/MS, bioassay and in silico docking, was proposed for rapidly detecting uPA ligands from Traditional Chinese Medicines (TCMs). Forty-two TCMs were initially assessed, and as illustrative case studies, Galla Chinensis and Sanguisorbae Radix, which appeared significant inhibitory activities on uPA, were chosen to develpe and verify the strategy. A total of seven uPA ligands were successfully detected and identified. Two of them, pentagalloylglucose and 28-O-ß-d-glucopyranosyl pomolic acid, were demonstrated to be potential inhibitors, with IC50 at 1.639 µM and 37.82 µM repectively. Furthermore, a combinatorial compound library screening combined with in silico docking assay, was revealed that ursolic acid (IC50 = 2.623 µM) was also speculated to be a potent parent structure for inhibition of uPA. This approach offers a multidimensional perspective to discover uPA-binding leading compounds from TCMs or other complex mixtures, which would provide an efficient route for drug discovery.

Cardiovascular disease models: A game changing paradigm in drug discovery and screening.

Cardiovascular disease is the leading cause of death worldwide. Although investment in drug discovery and development has been sky-rocketing, the number of approved drugs has been declining. Cardiovascular toxicity due to therapeutic drug use claims the highest incidence and severity of adverse drug reactions in late-stage clinical development. Therefore, to address this issue, new, additional, replacement and combinatorial approaches are needed to fill the gap in effective drug discovery and screening. The motivation for developing accurate, predictive models is twofold: first, to study and discover new treatments for cardiac pathologies which are leading in worldwide morbidity and mortality rates; and second, to screen for adverse drug reactions on the heart, a primary risk in drug development. In addition to in vivo animal models, in vitro and in silico models have been recently proposed to mimic the physiological conditions of heart and vasculature. Here, we describe current in vitro, in vivo, and in silico platforms for modelling healthy and pathological cardiac tissues and their advantages and disadvantages for drug screening and discovery applications. We review the pathophysiology and the underlying pathways of different cardiac diseases, as well as the new tools being developed to facilitate their study. We finally suggest a roadmap for employing these non-animal platforms in assessing drug cardiotoxicity and safety.

Automated MALDI Target Preparation Concept: Providing Ultra-High-Throughput Mass Spectrometry-Based Screening for Drug Discovery.

Label-free, mass spectrometric (MS) deciphering of enzymatic reactions by direct analysis of substrate-to-product conversion provides the next step toward more physiological relevant assays within drug discovery campaigns. Reduced risk of suffering from compound interference combined with diminished necessity for tailored signal mediators emphasizes the valuable role of label-free readouts. However, MS-based detection has not hitherto met high-throughput screening (HTS) requirements because of the lack of HTS-compatible sample introduction. In the present study, we report on a fully automated liquid-handling concept built in-house to concatenate biochemical assays with matrix-assisted laser desorption/ionization time-of-flight closing this technological gap. The integrated reformatting from 384- to 1536-well format enables cycle times of 0.6 s/sample for automated spotting and 0.4 s/sample for MS analysis, matching the requirements of HTS compatibility. In-depth examination of spotting quality, quantification accuracy, and instrument robustness together with the implementation of a protein tyrosine phosphatase 1B (PTP1B) inhibitor screening (4896 compounds) demonstrate the potential of the heavily inquired HTS integration of the label-free MS readout. Overall, the presented data demonstrate that the introduced automation concept makes label-free MS-based readouts accessible for HTS within drug discovery campaigns but also in other research areas requiring ultrafast MS-based detection.

Biomimetic cardiovascular platforms for in vitro disease modeling and therapeutic validation.

Bioengineered tissues have become increasingly more sophisticated owing to recent advancements in the fields of biomaterials, microfabrication, microfluidics, genetic engineering, and stem cell and developmental biology. In the coming years, the ability to engineer artificial constructs that accurately mimic the compositional, architectural, and functional properties of human tissues, will profoundly impact the therapeutic and diagnostic aspects of the healthcare industry. In this regard, bioengineered cardiac tissues are of particular importance due to the extremely limited ability of the myocardium to self-regenerate, as well as the remarkably high mortality associated with cardiovascular diseases worldwide. As novel microphysiological systems make the transition from bench to bedside, their implementation in high throughput drug screening, personalized diagnostics, disease modeling, and targeted therapy validation will bring forth a paradigm shift in the clinical management of cardiovascular diseases. Here, we will review the current state of the art in experimental in vitro platforms for next generation diagnostics and therapy validation. We will describe recent advancements in the development of smart biomaterials, biofabrication techniques, and stem cell engineering, aimed at recapitulating cardiovascular function at the tissue- and organ levels. In addition, integrative and multidisciplinary approaches to engineer biomimetic cardiovascular constructs with unprecedented human and clinical relevance will be discussed. We will comment on the implementation of these platforms in high throughput drug screening, in vitro disease modeling and therapy validation. Lastly, future perspectives will be provided on how these biomimetic platforms will aid in the transition towards patient centered diagnostics, and the development of personalized targeted therapeutics.

High Content, Phenotypic Assays and Screens for Compounds Modulating Cellular Processes in Primary Neurons.

High content, phenotypic screens offer a powerful approach to systems biology at the cellular level. The approach employs cells carrying fluorescently labeled molecules or organelles in 384- or 1536-well microplates, and an automated confocal screening microscope for capturing images from each well. Although some specifics vary according to the assay type, each will apply some degree of image processing and feature extraction followed by a data analysis pipeline to identify the perturbations (small molecules, etc.) of interest. We describe and discuss the advantages and limitations of high content assays and screens using the specific example of assaying mitochondrial dynamics in primary neurons. We provide a detailed description of our culturing methods, imaging and data analysis techniques and provide an open source, ready to use CellProfiler pipeline for high-throughput image segmentation and quantification tool for mitochondrial parameters.

A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery.

The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

Advanced Microengineered Lung Models for Translational Drug Discovery.

Lung diseases impose a significant socioeconomic burden and are a leading cause of morbidity and mortality worldwide. Moreover, respiratory medicine, unlike several other therapeutic areas, faces a disappointingly low number of new approved therapies. This is partly due to lack of reliable in vitro or in vivo models that can reproduce organ-level complexity and pathophysiological responses of human lung. Here, we examine new opportunities in application of recently emerged organ-on-chip technology to model human lung alveolus and small airway in preclinical drug development and biomarker discovery. We also discuss challenges that need to be addressed in coming years to further enhance the physiological and clinical relevance of these microsystems, enable their increased accessibility, and support their leap into personalized medicine.