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The introduction of more relevant cell models in early preclinical drug discovery, combined with high-content imaging and automated analysis, is expected to increase the quality of compounds progressing to preclinical stages in the drug development pipeline. In this review we discuss the current switch to more relevant 3D cell culture models and associated challenges for high-throughput screening and high-content analysis. We propose that overcoming these challenges will enable front-loading the drug discovery pipeline with better biology, extracting the most from that biology, and, in general, improving translation between in vitro and in vivo models. This is expected to reduce the proportion of compounds that fail in vivo testing due to a lack of efficacy or to toxicity.

This is a report on the early years of combinatorial materials science and technology. High-throughput technologies (HTTs) are found in life- and materials-science laboratories. Although HTTs have long been the standard in life sciences in academia as well as in industry, HTTs in materials science have become the standard in industry but not in academia. In life science, successful drugs developed with HTTs have been reported, but there is no information on successful materials developed with HTTs that have made it to the market. Some initial development of HTTs in materials science is summarized, especially early applications of artificial intelligence. This outlook attempts to summarize the development of combinatorial materials sciences from the early years to today.

Objective: To establish a quantitative assay of serum Golgi protein 73 (GP73) using xMAP technology and evaluate its performance. Methods: Monoclonal antibodies against GP73 were prepared and purified, and antibody pair screening was performed by double-antibody sandwich enzyme-linked immunosorbent assay. The screened antibodies were used to construct a Luminex liquid chip detection system, and the analysis performance of the detection system was evaluated. The serum levels of GP73 were detected in 90 clinical samples from healthy controls and patients with chronic hepatitis B infection (CHB) and hepatocellular carcinoma (HCC). Results: Five anti-GP73 monoclonal antibodies were prepared and purified, and 5 antibody pairs were successfully screened. The Luminex liquid chip detection system of GP73 was successfully constructed using 8F10D1 and 10B9F11 antibody pairs. The analytical performance evaluation showed that the sensitivity of this system was 0.25 ng/ml and the dynamic range was 0.25-100 ng/ml. No cross reactivity was observed. The intra- and inter-assay variation for GP73 was <8% and <11%, respectively. The recovery was 83%-92%. The linear regression equation was y=1.141x+ 6.436 ( r (2)=0.998 4, P <0.001). The GP73 concentrations in the serum samples of healthy control, CHB group, and HCC group were 42.8 (38.68, 55.90) ng/ml, 61.49 (43.59, 81) ng/ml, and 122.78 (49.36 liter, 264.55) ng/ml, respectively. The levels of GP73 in HCC group were significantly higher than those in CHB group and healthy controls ( P <0.05). Moreover, the levels of GP73 in CHB group were significantly higher than those in healthy controls ( P <0.05). Conclusions: A liquid chip detection system of GP73 was successfully constructed. It provides a powerful tool for the clinical application of GP73 in the future.

Background: GPCRs are considered essential for various physiological processes and have been the most productive drug targets. Therefore, development of the methods of GPCR ligands screening is a high priority for pharmaceutical industries and research institutions., Methods: We developed a potential method (piggyBac-TANGO) based on the TANGO and PRESTO-TANGO assays. The system was optimized with a piggyBac transposon as a transgene vehicle, and eGFP was used as a reporter instead of luciferase. The assay was validated in the HEK 293T and U87-MG cell lines and antagonist activities of the compounds were assessed. The transgene copy number and long-term stability were evaluated by qPCR. Then, we performed a DRD2-targeted screening for natural products using the piggyBac-TANGO assay., Results: The validation assay showed that using the piggyBac transposon as a transgene vehicle produced high signal-to-background ratio and stable readout confirmed by investigation of the transgene copy number and long-term stability. Use of eGFP instead of luciferase as a reporter enabled to create a high throughput system suitable for live cells. Moreover, the piggyBac-TANGO assay permitted versatile detection of antagonist activity of compounds and was not limited to a particular cell type. With the use of the piggyBac-TANGO assay, we have successfully identified a novel agonist of DRD2., Conclusion: Thus, the results indicate that the piggyBac-TANGO method is a user-friendly, robust and imaging-based assay that provides a novel approach to high throughput GPCR-targeted ligand screening and drug development.

The Toxicology in the 21st Century (Tox21) project seeks to develop and test methods for high-throughput examination of the effect certain chemical compounds have on biological systems. Although primary and toxicity assay data were readily available for multiple reporter gene modified cell lines, extensive annotation and curation was required to improve these datasets with respect to how FAIR (Findable, Accessible, Interoperable, and Reusable) they are. In this study, we fully annotated the Tox21 published data with relevant and accepted controlled vocabularies. After removing unreliable data points, we aggregated the results and created three sets of signatures reflecting activity in the reporter gene assays, cytotoxicity, and selective reporter gene activity, respectively. We benchmarked these signatures using the chemical structures of the tested compounds and obtained generally high receiver operating characteristic (ROC) scores, suggesting good quality and utility of these signatures and the underlying data. We analyzed the results to identify promiscuous individual compounds and chemotypes for the three signature categories and interpreted the results to illustrate the utility and re-usability of the datasets. With this study, we aimed to demonstrate the importance of data standards in reporting screening results and high-quality annotations to enable re-use and interpretation of these data. To improve the data with respect to all FAIR criteria, all assay annotations, cleaned and aggregate datasets, and signatures were made available as standardized dataset packages (Aggregated Tox21 bioactivity data, 2019).

In the UK, research on hazard group 4 (HG4) pathogens requires specialised Containment Level 4 (CL4) facilities. These differ from Biosafety Level 4 (BSL4) conditions in that work is conducted in class III microbiological safety cabinets for primary containment instead of using positive pressure suits. This presents unique challenges associated with the physical restrictions of working in a limited space, and prohibits the use of many techniques and specialist equipment. In consequence, detailed studies on the biology of HG4 pathogens and in particular their immunological relationships with the host are understudied in the UK; for example, the majority of immunological assays with which the immune system is interrogated require specialist equipment that is unsuitable for CL4. Multiplexing to simultaneously measure multiple analytes is increasingly being used in immunological studies. This assay is attractive for CL4 work because it reduces the time spent in the laboratory whilst maximising the use of valuable sample volume. The Luminex microsphere approach allows for the determination of many cytokines and chemokines, however, the detection system uses fixed aligned lasers and integrated computer systems which are unsuitable for use at CL4. Therefore, we have developed an approach in which the Luminex assay is conducted within the CL4 laboratory and a formalin-fixation stage is introduced to allow for analysis to be undertaken outside of containment. Quality control preparations allow the assay characteristics to be monitored and analysis of assay performance to be evaluated. Our data demonstrate that Luminex is an applicable tool for use at CL4 and that assays can be run reliably to generate reproducible standardised data across different plates and individual experiments., (Copyright © 2019. Published by Elsevier Inc.)

Background: Frequent reversion has been commonly observed in serial QuantiFERON-TB Gold In-Tube (QFT) tests, which limited its accuracy in defining the status of Mycobacterium tuberculosis (MTB) infection. Serum cytokine profiles might provide additional information to clarify the infection status., Method: Based on a population-based cohort study aiming to track MTB infection acquisition and disease development, serum profiles of 12 cytokines were determined by bead-based multiplex assays in parallel with QFT and tuberculin skin tests (TST) to explore potential relation between serum cytokines and MTB infection status., Results: Totally, 309 subjects got QFT conversion in one year (2013-2014) and 46.92% (145/309) of them got reversion in 2015. The study subjects were classified into three groups according to their QFT and TST results in 2015 (QFT persistence positive, QFT-/TST + and QFT-/TST-). The serum levels of MCP-1 and IL-8 were significantly different among the three groups. Furthermore, level of IL-8 was dramatically lower in QFT-/TST- group as compared to the other two groups, and no significant difference was observed for QFT-/TST + group as comparing with persistent positive group., Conclusion: Our results suggested that the decreased serum level of IL-8 might be potential biomarker to identify QFT reversion caused by infection clearance., (Copyright © 2018. Published by Elsevier Ltd.)

Toxicological screening is a specific approach to analytical toxicology that uses analytical tools such as GC-MS, LC-UV (diode array) or LC-MS. Toxicological screening allows the detection and simultaneous identification of a large number of compounds. The results may be based on the use of one or more techniques. As part of the accreditation process for medical biology examinations according to standard NF EN ISO 15189, the group from SFTA and SFBC recommends an approach to accredit toxicological screening. Indeed, the complexity of the accreditation of this analysis comes in particular from the high number of compounds that can be detected. Validation parameters are discussed in the specific context of toxicological screening by considering two distinct approaches: the simple identification of compounds, or the identification and estimation of a range of concentration related to clinical outcomes.

Blockchain is a shared distributed digital ledger technology that can better facilitate data management, provenance and security, and has the potential to transform healthcare. Importantly, blockchain represents a data architecture, whose application goes far beyond Bitcoin - the cryptocurrency that relies on blockchain and has popularized the technology. In the health sector, blockchain is being aggressively explored by various stakeholders to optimize business processes, lower costs, improve patient outcomes, enhance compliance, and enable better use of healthcare-related data. However, critical in assessing whether blockchain can fulfill the hype of a technology characterized as 'revolutionary' and 'disruptive', is the need to ensure that blockchain design elements consider actual healthcare needs from the diverse perspectives of consumers, patients, providers, and regulators. In addition, answering the real needs of healthcare stakeholders, blockchain approaches must also be responsive to the unique challenges faced in healthcare compared to other sectors of the economy. In this sense, ensuring that a health blockchain is 'fit-for-purpose' is pivotal. This concept forms the basis for this article, where we share views from a multidisciplinary group of practitioners at the forefront of blockchain conceptualization, development, and deployment.

Introduction: Proton nuclear magnetic resonance spectroscopy ( 1 H-NMR)-based metabolomic profiling has a range of applications in plant sciences., Objectives: The aim of the present work is to provide advice for minimizing uncontrolled variability in plant sample preparation before and during NMR metabolomic profiling, taking into account sample composition, including its specificity in terms of pH and paramagnetic ion concentrations, and NMR spectrometer performances., Methods: An automation of spectrometer preparation routine standardization before NMR acquisition campaign was implemented and tested on three plant sample sets (extracts of durum wheat spikelet, Arabidopsis leaf and root, and flax leaf, root and stem). We performed 1 H-NMR spectroscopy in three different sites on the wheat sample set utilizing instruments from two manufacturers with different probes and magnetic field strengths. The three collections of spectra were processed separately with the NMRProcFlow web tool using intelligent bucketing, and the resulting buckets were subjected to multivariate analysis., Results: Comparability of large- (Arabidopsis) and medium-size (flax) datasets measured at 600 MHz and from the wheat sample set recorded at the three sites (400, 500 and 600 MHz) was exceptionally good in terms of spectral quality. The coefficient of variation of the full width at half maximum (FWHM) and the signal-to-noise ratio (S/N) of two selected peaks was comprised between 5 and 10% depending on the size of sample set and the spectrometer field. EDTA addition improved citrate and malate resonance patterns for wheat sample sets. A collection of 22 samples of wheat spikelet extracts was used as a proof of concept and showed that the data collected at the three sites on instruments of different field strengths and manufacturers yielded the same discrimination pattern of the biological groups., Conclusion: Standardization or automation of several steps from extract preparation to data reduction improves data quality for small to large collections of plant samples of different origins.

Advances in X-ray crystallography have streamlined the process of determining high-resolution three-dimensional macromolecular structures. However, a rate-limiting step in this process continues to be the generation of crystals that are of sufficient size and quality for subsequent diffraction experiments. Here, iterative screen optimization (ISO), a highly automated process in which the precipitant concentrations of each condition in a crystallization screen are modified based on the results of a prior crystallization experiment, is described. After designing a novel high-throughput crystallization screen to take full advantage of this method, the value of ISO is demonstrated by using it to successfully crystallize a panel of six diverse proteins. The results suggest that ISO is an effective method to obtain macromolecular crystals, particularly for proteins that crystallize under a narrow range of precipitant concentrations., (open access.)

Big Data, the production of a massive amount of heterogeneous data, is often presented as a means to ensure the economic survival and sustainability of health systems. According to this perspective, Big Data could help save the spirit of our welfare states based on the principles of risks-sharing and equal access to care for all. According to a second perspective, opposed to the first, Big Data would fuel a process of demutualization, transferring to individuals a growing share of responsibility for managing their health. This article proposes to develop a third approach: Big Data does not induce a loss of solidarity but a transformation of the European model of welfare states. These are the data that are now the objects of the pooling. Individual and collective responsibilities are thus redistributed. However, this model, as new as it is, remains liberal in its inspiration; it basically allows the continuation of political liberalism by other means., (Copyright © 2018 Elsevier Masson SAS. All rights reserved.)

Despite significant advances in the treatment of cardiovascular diseases, antiplatelet therapies are still associated with a high risk of hemorrhage. In order to develop new drugs, methods to measure platelet function must be adapted for the high-throughput screening (HTS) format. Currently, all assays capable of assessing platelet function are either expensive, complex, or not validated, which makes them unsuitable for drug discovery. Here, we propose a simple, low-cost, and high-throughput-compatible platelet function assay, validated for the 384-well plate. In the proposed assay, agonist-induced platelet activity was assessed by three different methods: (i) measurement of light absorbance, which decreases with platelet aggregation; (ii) luminescence measurement, based on ATP release from activated platelets and luciferin-luciferase reaction; and (iii) automated bright-field microscopy of the wells and further quantification of platelet image area, described here for the first time. Brightfield imaging results were validated by demonstrating the similarity of dose-response curves obtained with absorbance and luminescence measurements after stimulating platelets, pre-incubated with prostaglandin E1 or tirofiban, and demonstrating the similarity of dose-response curves obtained with agonists. Assay quality was confirmed using the Z'-factor, a statistical parameter used to validate the robustness and suitability of an HTS assay. The results showed that, under high rotations per minute (1200 RPM), an acceptable Z'-factor score is reached for absorbance measurements (Z'-factor - 0.58) and automated brightfield imaging (Z'-factor - 0.52), without the need of replicates, while triplicates must be used to achieve an acceptable Z'-factor score (0.54) for luminescence measurements. Using low platelet concentration (4 × 10 4 /μl - 10 μl), the brightfield imaging test was further validated using washed platelets. Furthermore, drug screening was performed with compounds selected by structure-based virtual screening. Taken together, this study presents an optimized and validated assay for HTS to be used as a tool for antiplatelet drug discovery.

Background: HIV-1 protease inhibitor (PI) is one of the most potent classes of drugs in combinational antiretroviral therapies (cART). When a PI is used in combination with other anti- HIV drugs, cART can often suppress HIV-1 below detection thus prolonging the patient's lives. However, the challenge often faced by patients is the emergence of HIV-1 drug resistance. Thus, PIs with high genetic-barrier to drug-resistance are needed., Objective: The objective of this study was to develop a novel and simple fission yeast (Schizosaccharomyces pombe) cell-based system that is suitable for high throughput screening (HTS) of small molecules against HIV-1 protease (PR)., Methods: A fission yeast RE294-GFP strain that stably expresses HIV-1 PR and green fluorescence protein (GFP) under the control of an inducible nmt1 promoter was used. Production of HIV-1 PR induces cellular growth arrest, which was used as the primary endpoint for the search of PIs and was quantified by an absorbance-based method. Levels of GFP production were used as a counter-screen control to eliminate potential transcriptional nmt1 inhibitors., Results: Both the absorbance-based HIV-1 PR assay and the GFP-based fluorescence assay were miniaturized and optimized for HTS. A pilot study was performed using a small drug library mixed with known PI drugs and nmt1 inhibitors. With empirically adjusted and clearly defined double-selection criteria, we were able to correctly identify the PIs and to exclude all hidden nmt1 inhibitors., Conclusion: We have successfully developed and validated a fission yeast cell-based HTS platform for the future screening and testing of HIV-1 PR inhibitors., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Vaccine immunogenicity and clinical efficacy are often assessed by the measure of serum-neutralizing antibodies. The present gold standard for detecting neutralizing antibodies against many viruses, including dengue, is the plaque/focus reduction neutralization test (P/FRNT). The FRNT is a cell-based assay that inherits high variability, resulting in poor precision and has lengthy turnaround times. The virus reduction neutralization test (VRNT) is a high-throughput alternative to the standard low-throughput and laborious FRNT. The VRNT is similar to FRNT using unaltered wild-type virus and immunostaining, yet uses imaging cytometry to count virus-infected cells 1 day post-infection, reducing assay time and increasing overall throughput 15-fold. In addition, the VRNT has lowered variability relative to FRNT, which may be explained in part by the observation that foci overlap alters foci count and titer over time, in the FRNT. The ability to count one infected cell, rather than waiting for overlapping foci to form, ensures accuracy and contributes to the precision (7-25% coefficient of variation) and sensitivity of the VRNT. Results from 81 clinical samples tested in the VRNT and FRNT show a clear positive relationship. During sample testing, a 96-well plate edge effect was noted and the elimination of this edge effect was achieved by a simple plate seeding technique. The VRNT is an improvement to the current neutralization assays for its shortened assay time, increased precision and throughput, and an alternative to the P/FRNT.

Western blotting (WB) is widely used to test antibody specificity, but the assay has low throughput and precision. Here we used preparative gel electrophoresis to develop a capture format for WB. Fractions with soluble, size-separated proteins facilitated parallel readout with antibody arrays, shotgun mass spectrometry (MS) and immunoprecipitation followed by MS (IP-MS). This pipeline provided the means for large-scale implementation of antibody validation concepts proposed by an international working group on antibody validation (IWGAV).

There is a need for standardized validation methods for antibody specificity and selectivity. Recently, five alternative validation pillars were proposed to explore the specificity of research antibodies using methods with no need for prior knowledge about the protein target. Here, we show that these principles can be used in a streamlined manner for enhanced validation of research antibodies in Western blot applications. More than 6,000 antibodies were validated with at least one of these strategies involving orthogonal methods, genetic knockdown, recombinant expression, independent antibodies, and capture mass spectrometry analysis. The results show a path forward for efforts to validate antibodies in an application-specific manner suitable for both providers and users.

Critical to maintaining quality control in high-throughput screening is the need for constant monitoring of liquid-dispensing fidelity. Traditional methods involve operator intervention with gravimetric analysis to monitor the gross accuracy of full plate dispenses, visual verification of contents, or dedicated weigh stations on screening platforms that introduce potential bottlenecks and increase the plate-processing cycle time. We present a unique solution using open-source hardware, software, and 3D printing to automate dispenser accuracy determination by providing real-time dispense weight measurements via a network-connected precision balance. This system uses an Arduino microcontroller to connect a precision balance to a local network. By integrating the precision balance as an Internet of Things (IoT) device, it gains the ability to provide real-time gravimetric summaries of dispensing, generate timely alerts when problems are detected, and capture historical dispensing data for future analysis. All collected data can then be accessed via a web interface for reviewing alerts and dispensing information in real time or remotely for timely intervention of dispense errors. The development of this system also leveraged 3D printing to rapidly prototype sensor brackets, mounting solutions, and component enclosures.

Over the past 20 years, mass spectrometry (MS) has emerged as a dynamic tool for proteomics biomarker discovery. However, published MS biomarker candidates often do not translate to the clinic, failing during attempts at independent replication. The cause can be shortcomings in study design, sample quality, assay quantitation, and/or quality/process control. To address these shortcomings, we developed an MS workflow in accordance with Tier 2 measurement requirements for targeted peptides, defined by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) "fit-for-purpose" approach, using dynamic multiple reaction monitoring (dMRM), which measures specific peptide transitions during predefined retention time (RT) windows. We describe the development of a robust multipex dMRM assay measuring 641 proteotypic peptides from 392 colorectal cancer (CRC) related proteins, and the procedures to track and handle sample processing and instrument variation over a four-month study, during which the assay measured blood samples from 1045 patients with CRC symptoms. After data collection, transitions were filtered by signal quality metrics before entering receiver operating characteristic (ROC) analysis. The results demonstrated CRC signal carried by 127 proteins in the symptomatic population. The workflow might be further developed to build Tier 1 assays for clinical tests identifying symptomatic individuals at elevated risk of CRC., Significance: We developed a dMRM MS method with the rigor of a Tier 2 assay as defined by the CPTAC 'fit for purpose approach' [1]. Using quality and process control procedures, the assay was used to quantify 641 proteotypic peptides representing 392 CRC-related proteins in plasma from 1045 CRC-symptomatic patients. To our knowledge, this is the largest MRM method applied to the largest study to date. The results showed that 127 of the proteins carried univariate CRC signal in the symptomatic population. This large number of single biomarkers bodes well for future development of multivariate classifiers to distinguish CRC in the symptomatic population., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Warfarin exerts its anticoagulation activity by blocking the vitamin K-epoxide cycle. A quantitative understanding of how warfarin and related genes interact with the vitamin K-epoxide cycle and the associated change of coagulation activity in the human body may help study the pharmacodynamics of warfarin. The plasma concentration of vitamin K 1 (VK 1 ) and vitamin K 1 2,3-epoxide (VK 1 O) could reflect the status of vitamin K-epoxide cycle. However, their determination is a challenging task due to their extremely low concentrations in human plasma and the severe interferences caused by co-extracted lipids. In this study, we developed an LC-APCI-MS/MS method for the simultaneous determination of VK 1 and VK 1 O in human plasma using stable deuterium-labeled vitamin K 1 (vitamin K 1 -d7) as the internal standard (IS). Plasma samples were prepared through protein denaturation followed by one-step liquid extraction with cyclohexane. Chromatographic separation of analytes from isobaric interferences and endogenous ion suppressor was performed on a Synergi Hydro-RP column (150 mm × 4.6 mm, 4 μm) under the reversed-phase condition with isocratic elution. The selective reaction monitoring (SRM) transitions were chosen as m/z = 451.5→187.3 for VK 1 , m/z = 467.5→161.2 for VK 1 O, and m/z = 458.6→194.3 for IS in APCI positive mode. The assay was linear in the range of 100-10,000 pg/mL for the two analytes and achieved considerable extraction recoveries (87.8-93.3%, 91.0-96.9%, and 92.0% for VK 1 , VK 1 O, and IS, respectively), negligible matrix effects (93.6-96.0%, 96.3-100.1%, and 95.5%), and high selectivity with a small sample volume requirement (0.2 mL) and short run time (15 min). The validated method was successfully applied in a clinical pharmacodynamic study of warfarin, and the clotting activity was found to be negatively correlated with the plasma concentration ratio of VK 1 O to VK 1 ., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The outcome of high-throughput biological experiments is affected by many operational factors in the experimental and data-analytical procedures. Understanding how these factors affect the reproducibility of the outcome is critical for establishing workflows that produce replicable discoveries. In this article, we propose a regression framework, based on a novel cumulative link model, to assess the covariate effects of operational factors on the reproducibility of findings from high-throughput experiments. In contrast to existing graphical approaches, our method allows one to succinctly characterize the simultaneous and independent effects of covariates on reproducibility and to compare reproducibility while controlling for potential confounding variables. We also establish a connection between our model and certain Archimedean copula models. This connection not only offers our regression framework an interpretation in copula models, but also provides guidance on choosing the functional forms of the regression. Furthermore, it also opens a new way to interpret and utilize these copulas in the context of reproducibility. Using simulations, we show that our method produces calibrated type I error and is more powerful in detecting difference in reproducibility than existing measures of agreement. We illustrate the usefulness of our method using a ChIP-seq study and a microarray study., (© 2017, The International Biometric Society.)

Skin sensitization risk assessment of botanical ingredients is necessary for consumers' protection and occupational hazard identification. There are currently very few available alternative methods that can assist in the evaluation of complex mixtures. Chemical methods can provide essential information in a timely manner and thus help to reduce the need for in vivo testing, and they can complement and facilitate targeted in vitro assays. In the present work, the applicability of the high-throughput screening with dansyl cysteamine (DCYA) method for the systematic evaluation of skin sensitization of complex botanicals was explored. Botanical ingredients of four unrelated plant species were obtained and tested with the high-throughput fluorescence method at three concentrations. To illustrate the minimal matrix effects of the tested extracts on the developed method, the least DCYA-reactive extract (Rosa canina) was spiked with known sensitizers at different concentrations. The data obtained from the four plant extracts and the spiking experiments with known sensitizers, suggest that the high-throughput screening-DCYA method can be successfully applied for estimating the skin sensitization potential of complex botanical matrices. This is the first report of an attempt to develop a versatile in chemico method for the rapid detection of reactive skin sensitizers in complex botanical extracts, which could complement the battery of existing validated, non-animal methods., (Copyright © 2018 John Wiley & Sons, Ltd.)

Recent developments in molecular biology and metabolic engineering have resulted in a large increase in the number of strains that need to be tested, positioning high-throughput screening of microorganisms as an important step in bioprocess development. Scalability is crucial for performing reliable screening of microorganisms. Most of the scalability studies from microplate screening systems to controlled stirred-tank bioreactors have been performed so far with unicellular microorganisms. We have compared cultivation of industrially relevant oleaginous filamentous fungi and microalga in a Duetz-microtiter plate system to benchtop and pre-pilot bioreactors. Maximal glucose consumption rate, biomass concentration, lipid content of the biomass, biomass, and lipid yield values showed good scalability for Mucor circinelloides (less than 20% differences) and Mortierella alpina (less than 30% differences) filamentous fungi. Maximal glucose consumption and biomass production rates were identical for Crypthecodinium cohnii in microtiter plate and benchtop bioreactor. Most likely due to shear stress sensitivity of this microalga in stirred bioreactor, biomass concentration and lipid content of biomass were significantly higher in the microtiter plate system than in the benchtop bioreactor. Still, fermentation results obtained in the Duetz-microtiter plate system for Crypthecodinium cohnii are encouraging compared to what has been reported in literature. Good reproducibility (coefficient of variation less than 15% for biomass growth, glucose consumption, lipid content, and pH) were achieved in the Duetz-microtiter plate system for Mucor circinelloides and Crypthecodinium cohnii. Mortierella alpina cultivation reproducibility might be improved with inoculation optimization. In conclusion, we have presented suitability of the Duetz-microtiter plate system for the reproducible, scalable, and cost-efficient high-throughput screening of oleaginous microorganisms.

Hepsin is a membrane-anchored serine protease whose role in hepatocyte growth factor (HGF) signaling and epithelial integrity makes it a target of therapeutic interest in carcinogenesis and metastasis. Using an integrated design, synthesis, and screening platform, we were able to rapidly develop potent and selective inhibitors of hepsin. In progressing from the initial hit 7 to compound 53, the IC 50 value against hepsin was improved from ∼1 μM to 22 nM, and the selectivity over urokinase-type plasminogen activator (uPA) was increased from 30-fold to >6000-fold. Subsequent in vitro ADMET profiling and cellular studies confirmed that the leading compounds are useful tools for interrogating the role of hepsin in breast tumorigenesis.

Summary: This R package helps to implement a robust approach to deal with mass spectrometry (MS) data. It is aimed at alleviating reproducibility issues and pernicious effects of deviating signals on both data pre-processing and downstream data analysis. Based on robust statistical methods, it facilitates the identification and filtering of low-quality mass spectra and atypical peak profiles as well as monitoring and data handling through pre-processing, which extends existing computational tools for high-throughput data., Availability and Implementation: MALDIrppa is implemented as a package for the R environment for data analysis and it is freely available to download from the CRAN repository at https://CRAN.R-project.org/package=MALDIrppa., Contact: javier.palarea@bioss.ac.uk., (© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com)

We present a standalone, scalable and high-throughput software platform for PET image reconstruction and analysis. We focus on high fidelity modelling of the acquisition processes to provide high accuracy and precision quantitative imaging, especially for large axial field of view scanners. All the core routines are implemented using parallel computing available from within the Python package NiftyPET, enabling easy access, manipulation and visualisation of data at any processing stage. The pipeline of the platform starts from MR and raw PET input data and is divided into the following processing stages: (1) list-mode data processing; (2) accurate attenuation coefficient map generation; (3) detector normalisation; (4) exact forward and back projection between sinogram and image space; (5) estimation of reduced-variance random events; (6) high accuracy fully 3D estimation of scatter events; (7) voxel-based partial volume correction; (8) region- and voxel-level image analysis. We demonstrate the advantages of this platform using an amyloid brain scan where all the processing is executed from a single and uniform computational environment in Python. The high accuracy acquisition modelling is achieved through span-1 (no axial compression) ray tracing for true, random and scatter events. Furthermore, the platform offers uncertainty estimation of any image derived statistic to facilitate robust tracking of subtle physiological changes in longitudinal studies. The platform also supports the development of new reconstruction and analysis algorithms through restricting the axial field of view to any set of rings covering a region of interest and thus performing fully 3D reconstruction and corrections using real data significantly faster. All the software is available as open source with the accompanying wiki-page and test data.

Phosphatidylethanol (PEth) is an alcohol biomarker formed in the presence of ethanol in the body. Both due to its specificity and because it has a detection window of up to several weeks after alcohol intake, its application potential is broader than for other ethanol biomarkers. The aim of this study was to develop and validate a robust method for PEth in whole blood with fast and efficient sample extraction and a short analytical runtime, suitable for high throughput routine purposes. A validated ultra-performance liquid chromatography tandem mass spectrometry (UPLC®-MSMS) method for quantification of PEth 16:0/18:1 in the range 0.05-4.00 μM (R2 ≥ 0.999) is presented. PEth 16:0/18:1 and the internal standard (IS) PEth-d5 (0.55 μM), were extracted from whole blood (150 μL) by simple protein precipitation with 2-propanol (450 μL). Chromatography was achieved using a BEH-phenyl (2.1 × 30 mm, 1.7 μm) column and a gradient elution combining ammonium formate (5 mM, pH 10.1) and acetonitrile at a flow rate of 0.5 mL/min. Runtime was 2.3 min. The mass spectrometer was monitored in negative mode with multiple reaction monitoring (MRM). The m/z 701.7 > 255.2 and 701.7 > 281.3 transitions were monitored for PEth 16:0/18:1 and the m/z 706.7 > 255.3 for PEth-d5. Limit of quantification was 0.03 μM (coefficient of variation, CV = 6.7%, accuracy = 99.3%). Within-assay and between-assay imprecision were 0.4-3.3% (CV ≤ 7.1%). Recoveries were 95-102% (CV ≤ 4.9%). Matrix effects after IS correction ranged from 107% to 112%. PEth 16:0/18:1 in patient samples were stable for several days at 30°C. Repeated freezing (-80°C) and thawing did not affect the concentration. After thawing and analysis patient samples were stable at 4-8°C for at least 4 weeks. Results from a proficiency test program, showing |Z| values ≤1.2, confirm the validity of the method. Analysis of the first 3,169 samples sent to our laboratory for routine use has demonstrated its properties as a robust method suitable for high throughput purposes.

Epigenetic alterations underlie various human disorders, including cancer, and this has resulted in the development of drugs targeting epigenetic alterations. Although DNA demethylating agents are one of the major epigenetic drugs, only two compounds-5-azacytidine (5-aza-CR, azacitidine) and 5-aza-2'-deoxycytidine (5-aza-dC, decitabine)-have obtained clinical approval. Here, we aimed to establish a detection system for DNA demethylating agents suitable for a high-throughput screening (HTS) in mammalian cells. We inserted luciferase and EGFP reporter genes under the UCHL1 promoter, which is methylation-silenced in human colon cancers and can be readily demethylated to drive strong expression. Methylated UCHL1 promoter was introduced into HCT116 colon cancer cells, and transfectants with methylated exogenous UCHL1 promoter were obtained. By screening subclones from each of the epigenetically heterogeneous transfectant clones, we finally obtained three optimal subclones that expressed luciferase and EGFP after 5-aza-dC treatment with high signal-to-noise ratios. Nucleosomes with H3K9me2 were present around the exogenous UCHL1 promoter in all three subclones. Using one of the subclones (HML58-3), HTS was conducted using 19,840 small molecules. Two hit compounds were obtained, and these turned out to be 5-aza-dC and 5-aza-CR. The assay system constructed here demonstrates a robust response to DNA demethylating agents, along with high specificity, and will be useful for screening and biological assays in epigenetics.

The new paradigm of the big data raises many expectations, particularly in the field of health. Curiously, even though medical biology laboratories generate a great amount of data, the opportunities offered by this new field are poorly documented. For better understanding the clinical context of chronical disease follow-up, for leveraging preventive and/or personalized medicine, the contribution of big data analytics seems very promising. It is within this framework that we have explored to use data of a Breton group of laboratories of medical biology to analyze the possible contributions of their exploitation in the improvement of the clinical practices and to anticipate the evolution of pathologies for the benefit of patients. We report here three practical applications derived from routine laboratory data from a period of 5 years (February 2010-August 2015): follow-up of patients treated with AVK according to the recommendations of the High authority of health (HAS), use of the new troponin markers HS and NT-proBNP in cardiology. While the risks and difficulties of using algorithms in the health domain should not be underestimated - quality, accessibility, and protection of personal data in particular - these first results show that use of tools and technologies of the big data repository could provide decisive support for the concept of "evidence based medicine".

Toxicokinetics (TK) provides critical information for integrating chemical toxicity and exposure assessments in order to determine potential chemical risk (i.e., the margin between toxic doses and plausible exposures). For thousands of chemicals that are present in our environment, in vivo TK data are lacking. The publicly available R package "httk" (version 1.8, named for "high throughput TK") draws from a database of in vitro data and physico-chemical properties in order to run physiologically-based TK (PBTK) models for 553 compounds. The PBTK model parameters include tissue:plasma partition coefficients (K p ) which the httk software predicts using the model of Schmitt (Toxicol In Vitro 22 (2):457-467, 2008). In this paper we evaluated and modified httk predictions, and quantified confidence using in vivo literature data. We used 964 rat K p measured by in vivo experiments for 143 compounds. Initially, predicted K p were significantly larger than measured K p for many lipophilic compounds (log 10 octanol:water partition coefficient > 3). Hence the approach for predicting K p was revised to account for possible deficiencies in the in vitro protein binding assay, and the method for predicting membrane affinity was revised. These changes yielded improvements ranging from a factor of 10 to nearly a factor of 10,000 for 83 K p across 23 compounds with only 3 K p worsening by more than a factor of 10. The vast majority (92%) of K p were predicted within a factor of 10 of the measured value (overall root mean squared error of 0.59 on log 10 -transformed scale). After applying the adjustments, regressions were performed to calibrate and evaluate the predictions for 12 tissues. Predictions for some tissues (e.g., spleen, bone, gut, lung) were observed to be better than predictions for other tissues (e.g., skin, brain, fat), indicating that confidence in the application of in silico tools to predict chemical partitioning varies depending upon the tissues involved. Our calibrated model was then evaluated using a second data set of human in vivo measurements of volume of distribution (V ss ) for 498 compounds reviewed by Obach et al. (Drug Metab Dispos 36(7):1385-1405, 2008). We found that calibration of the model improved performance: a regression of the measured values as a function of the predictions has a slope of 1.03, intercept of - 0.04, and R 2 of 0.43. Through careful evaluation of predictive methods for chemical partitioning into tissues, we have improved and calibrated these methods and quantified confidence for TK predictions in humans and rats.

Rationale: Using mass spectrometry, the analysis of known metabolite structures has become feasible in a systematic high-throughput fashion. Nevertheless, the identification of previously unknown structures remains challenging, partially because many unidentified variants originate from known molecules that underwent unexpected modifications. Here, we present a method for the discovery of unknown metabolite modifications and conjugate metabolite isoforms in a high-throughput fashion., Methods: The method is based on user-controlled in-source fragmentation which is used to induce loss of weakly bound modifications. This is followed by the comparison of product ions from in-source fragmentation and collision-induced dissociation (CID). Diagonal MS 2 -MS 3 matching allows the detection of unknown metabolite modifications, as well as substructure similarities. As the method relies heavily on the advantages of in-source fragmentation and its ability to 'magically' elucidate unknown modification, we have named it inSourcerer as a portmanteau of in-source and sorcerer., Results: The method was evaluated using a set of 15 different cytokinin standards. Product ions from in-source fragmentation and CID were compared. Hierarchical clustering revealed that good matches are due to the presence of common substructures. Plant leaf extract, spiked with a mix of all 15 standards, was used to demonstrate the method's ability to detect these standards in a complex mixture, as well as confidently identify compounds already present in the plant material., Conclusions: Here we present a method that incorporates a classic liquid chromatography/mass spectrometry (LC/MS) workflow with fragmentation models and computational algorithms. The assumptions upon which the concept of the method was built were shown to be valid and the method showed that in-source fragmentation can be used to pinpoint structural similarities and indicate the occurrence of a modification., (Copyright © 2017 John Wiley & Sons, Ltd.)

Access to clean, safe drinking water poses a serious challenge to regulators, and requires analytical strategies capable of rapid screening and identification of potentially hazardous chemicals, specifically in situations when threats to water quality or security require rapid investigations and potential response. This study describes a fast and efficient chemical hazard screening strategy for characterising trace levels of polar organic contaminants in water matrices, based on liquid chromatography high resolution mass spectrometry with post-acquisition 'case-control' data processing. This method allowed for a rapid response time of less than 24 h for the screening of target, suspect and non-target unknown chemicals via direct injection analysis, and a second, more sensitive analysis option requiring sample pre-concentration. The method was validated by fortifying samples with a range of pesticides, pharmaceuticals and personal care products (n = 46); with >90% of target compounds positively screened in samples at 1 ng mL -1 , and 46% at 0.1 ng mL -1 when analysed via direct injection. To simulate a contamination event samples were fortified with compounds not present in the commercial library (designated 'non-target compounds'; fipronil and fenitrothion), tentatively identified at 0.2 and 1 ng mL -1 , respectively; and a compound not included in any known commercial library or public database (designated 'unknown' compounds; 8Cl - perfluorooctanesulfonic acid), at 0.8 ng mL -1 . The method was applied to two 'real-case' scenarios: (1) the assessment of drinking water safety during a high-profile event in Brisbane, Australia; and (2) to screen treated, re-circulated drinking water and pre-treated (raw) water. The validated workflow was effective for rapid prioritisation and screening of suspect and non-target potential hazards at trace levels, and could be applied to a wide range of matrices and investigations where comparison of organic contaminants between an affected and control site and or timeframe is warranted., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Rational and high-throughput optimization of mammalian cell culture media has a great potential to modulate recombinant protein product quality. We present a process design method based on parallel design-of-experiment (DoE) of CHO fed-batch cultures in 96-deepwell plates to modulate monoclonal antibody (mAb) glycosylation using medium supplements. To reduce the risk of losing valuable information in an intricate joint screening, 17 compounds were separated into five different groups, considering their mode of biological action. The concentration ranges of the medium supplements were defined according to information encountered in the literature and in-house experience. The screening experiments produced wide glycosylation pattern ranges. Multivariate analysis including principal component analysis and decision trees was used to select the best performing glycosylation modulators. Subsequent D-optimal quadratic design with four factors (three promising compounds and temperature shift) in shake tubes confirmed the outcome of the selection process and provided a solid basis for sequential process development at a larger scale. The glycosylation profile with respect to the specifications for biosimilarity was greatly improved in shake tube experiments: 75% of the conditions were equally close or closer to the specifications for biosimilarity than the best 25% in 96-deepwell plates. Biotechnol. Bioeng. 2017;114: 1448-1458. © 2017 Wiley Periodicals, Inc., (© 2017 Wiley Periodicals, Inc.)

Synchronized brain activity in the form of alternating epochs of massive persistent network activity and periods of generalized neural silence, has been extensively studied as a fundamental form of circuit dynamics, important for many cognitive functions including short-term memory, memory consolidation, or attentional modulation. A key element in such studies is the accurate determination of the timing and duration of those network events. The local field potential (LFP) is a particularly attractive method for recording network activity, because it allows for long and stable recordings from multiple sites, allowing researchers to estimate the functional connectivity of local networks. Here, we present a computational method for the automatic detection and quantification of in-vitro LFP events, aiming to overcome the limitations of current approaches (e.g. slow analysis speed, arbitrary threshold-based detection and lack of reproducibility across and within experiments). The developed method is based on the implementation of established signal processing and machine learning approaches, is fully automated and depends solely on the data. In addition, it is fast, highly efficient and reproducible. The performance of the software is compared against semi-manual analysis and validated by verification of prior biological knowledge.

Matrix-assisted laser desorption ionization (MALDI) could be advantageous for high-throughput MS acquisition but suffers from low signal reproducibility. The purpose of this study was to establish a reliable MALDI-tandem mass spectrometry (MS/MS)-based high-throughput quantification of tryptic peptides using our newly developed scrambled internal standard (sIS) method. The standard curves obtained with sIS peptides showed good linearity over a wide concentration range (5-1000 fmol/μL) compared to that with the IS-free method, and the coefficient of variation of data points at each concentration (5-1000 fmol/μL) was significantly reduced. Furthermore, the ion suppression effect of digested serum could be normalized with the sIS peptides. Differences of quantitative values obtained by MALDI-MS/MS and liquid chromatography-MS/MS with selected reaction monitoring were within 20% in the presence of 0.1-5 μL of immunoprecipitated model plasma. Furthermore, the effect of amino acid composition on peptide sensitivity was examined, and we found that sensitivity was significantly decreased if an aromatic amino acid was replaced with a nonaromatic amino acid. Thus, high sensitivity required the use of sIS peptides containing an aromatic amino acid. Finally, the sIS method enabled high-throughput quantification of tryptic peptides with high accuracy and a wide dynamic range.

Dilutions are a common source of analytical error, both in terms of accuracy and precision, and a common source of analyst mistakes. When serial dilutions are used, errors compound, even when employing laboratory automation. Direct point dilutions instead of serial dilutions can reduce error but is often impractical as they require either large diluent volumes or very small sample volumes when performed with traditional liquid handling equipment. We evaluated preparation of dilution curves using a picoliter digital dispenser, the HP, Inc. / TECAN D300 which is capable of accurately delivering picoliter volumes directly into sample wells filled with assay diluent. Dilution linearity and variability of the direct dilutions were similar to or less than those generated with a traditional liquid handler as measured using a fluorophore assay and an ELISA used to measure vaccine potency. Minimum concentrations for detergent in the dispensed sample were identified but no correlation with detergent characteristics was observed. The tolerance to protein in the sample was evaluated as well with up to 5% BSA having no impact on dispense linearity and precision. We found the digital dispenser to reduce automation complexity while maintaining or improving assay performance in addition to facilitating complex plate lay-outs., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Characterizing the technical precision of measurements is a necessary stage in the planning of experiments and in the formal sample size calculation for optimal design. Instruments that measure multiple analytes simultaneously, such as in high-throughput assays arising in biomedical research, pose particular challenges from a statistical perspective. The current most popular method for assessing precision of high-throughput assays is by scatterplotting data from technical replicates. Here, we question the statistical rationale of this approach from both an empirical and theoretical perspective, illustrating our discussion using four example data sets from different genomic platforms. We demonstrate that such scatterplots convey little statistical information of relevance and are potentially highly misleading. We present an alternative framework for assessing the precision of high-throughput assays and planning biomedical experiments. Our methods are based on repeatability-a long-established statistical quantity also known as the intraclass correlation coefficient. We provide guidance and software for estimation and visualization of repeatability of high-throughput assays, and for its incorporation into study design. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd., (© 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.)

Background: Despite the importance of nitric oxide (NO) in vascular physiology and pathology, a high-throughput method for the quantification of its vascular generation is lacking., Objective: By using the fluorescent probe 4-amino-5-methylamino-2',7'-difluorofluorescein (DAF-FM), we have optimized a simple method for the determination of the generation of endothelial nitric oxide in a microplate format., Methods: A nitric oxide donor was used (3-morpholinosydnonimine hydrochloride, SIN-1). Different factors affecting the method were studied, such as the effects of dye concentration, different buffers, time of reaction, gain, and number of flashes., Results: Beer's law was linear over a nanomolar range (1-10 nM) of SIN-1 with wavelengths of maximum excitation and emission at 495 and 525 nm; the limit of detection reached 0.897 nM. Under the optimized conditions, the generation of rat aortic endothelial NO was measured by incubating DAF-FM with serial concentrations (10-1000 µM) of acetylcholine (ACh) for 3 min. To confirm specificity, N ω -Nitro-l-arginine methyl ester (l-NAME)-the standard inhibitor of endothelial NO synthase-was found to inhibit the ACh-stimulated generation of NO. In addition, vessels pre-exposed for 1 h to 400 µM of the endothelial damaging agent methyl glyoxal showed inhibited NO generation when compared to the control stimulated by ACh., Conclusions: The capability of the method to measure micro-volume samples makes it convenient for the simultaneous handling of a very large number of samples. Additionally, it allows samples to be run simultaneously with their replicates to ensure identical experimental conditions, thus minimizing the effect of biological variability.

Powerful machine learning tools exist to extract biological patterns for diagnosis or prediction from high-dimensional datasets. Simultaneous advances in high-throughput profiling technologies have led to a rapid acceleration of biomarker discovery investigations across all areas of medicine. However, the translation of biomarker signatures into clinically useful tools has thus far been difficult. In this chapter, several important considerations are discussed that influence such translation in the context of classifier design. These include aspects of variable selection that go beyond classification accuracy, as well as effects of variability on assay stability and sample size. The consideration of such factors may lead to an adaptation of biomarker discovery approaches, aimed at an optimal balance of performance and clinical translatability.

Neurotoxicity and developmental neurotoxicity are important issues of chemical hazard assessment. Since the interpretation of animal data and their extrapolation to man is challenging, and the amount of substances with information gaps exceeds present animal testing capacities, there is a big demand for in vitro tests to provide initial information and to prioritize for further evaluation. During the last decade, many in vitro tests emerged. These are based on animal cells, human tumour cell lines, primary cells, immortalized cell lines, embryonic stem cells, or induced pluripotent stem cells. They differ in their read-outs and range from simple viability assays to complex functional endpoints such as neural crest cell migration. Monitoring of toxicological effects on differentiation often requires multiomics approaches, while the acute disturbance of neuronal functions may be analysed by assessing electrophysiological features. Extrapolation from in vitro data to humans requires a deep understanding of the test system biology, of the endpoints used, and of the applicability domains of the tests. Moreover, it is important that these be combined in the right way to assess toxicity. Therefore, knowledge on the advantages and disadvantages of all cellular platforms, endpoints, and analytical methods is essential when establishing in vitro test systems for different aspects of neurotoxicity. The elements of a test, and their evaluation, are discussed here in the context of comprehensive prediction of potential hazardous effects of a compound. We summarize the main cellular characteristics underlying neurotoxicity, present an overview of cellular platforms and read-out combinations assessing distinct parts of acute and developmental neurotoxicology, and highlight especially the use of stem cell-based test systems to close gaps in the available battery of tests.

High-throughput screening (HTS) is an effective method for lead and probe discovery that is widely used in industry and academia to identify novel chemical matter and to initiate the drug discovery process. However, HTS can be time consuming and costly and the use of subsets as an efficient alternative to screening entire compound collections has been investigated. Subsets may be selected on the basis of chemical diversity, molecular properties, biological activity diversity or biological target focus. Previously, we described a novel form of subset screening: plate-based diversity subset (PBDS) screening, in which the screening subset is constructed by plate selection (rather than individual compound cherry-picking), using algorithms that select for compound quality and chemical diversity on a plate basis. In this paper, we describe a second-generation approach to the construction of an updated subset: PBDS2, using both plate and individual compound selection, that has an improved coverage of the chemical space of the screening file, whilst only selecting the same number of plates for screening. We describe the validation of PBDS2 and its successful use in hit and lead discovery. PBDS2 screening became the default mode of singleton (one compound per well) HTS for lead discovery in Pfizer.

Reference chemicals were selected based on thyroid bioactivity in 'Tier 1' screening assays used by the U.S. EPA's Endocrine Disruptor Screening Program. Active reference chemicals had significant effects on thyroid-responsive endpoints in the amphibian metamorphosis assay, and the male and female pubertal rat assays. In the absence of thyroid weight or histopathological effects, additional published studies providing mechanistic data on thyroid activity were required for active chemicals. Inactive reference chemicals had no significant effects on thyroid-responsive endpoints in Tier 1 assays, or in amphibian or rodent studies from several online databases. The 34 reference chemicals (29 active and five inactive) will be useful for performance-based validation of alternative, high throughput screening assays for thyroid bioactivity., (Copyright © 2016. Published by Elsevier Inc.)

High-throughput screening technologies are increasingly integrated into the formulation development process of biopharmaceuticals. The performance of liquid handling systems is dependent on the ability to deliver accurate and precise volumes of specific reagents to ensure process quality. We have developed an automated gravimetric calibration procedure to adjust the accuracy and evaluate the precision of the TECAN Freedom EVO liquid handling system. Volumes from 3 to 900 µL using calibrated syringes and fixed tips were evaluated with various solutions, including aluminum hydroxide and phosphate adjuvants, β-casein, sucrose, sodium chloride, and phosphate-buffered saline. The methodology to set up liquid class pipetting parameters for each solution was to split the process in three steps: (1) screening of predefined liquid class, including different pipetting parameters; (2) adjustment of accuracy parameters based on a calibration curve; and (3) confirmation of the adjustment. The run of appropriate pipetting scripts, data acquisition, and reports until the creation of a new liquid class in EVOware was fully automated. The calibration and confirmation of the robotic system was simple, efficient, and precise and could accelerate data acquisition for a wide range of biopharmaceutical applications., Competing Interests: The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Alhydrogel and Adjuphos are trademarks of Brenntag Nordic A/S. All authors are, or were at the time of the study, employees of the GSK group of companies. D. Lemoine owns shares in GSK., (© 2016 Society for Laboratory Automation and Screening.)

The correction or removal of signal errors in high-throughput screening (HTS) data is critical to the identification of high-quality lead candidates. Although a number of strategies have been previously developed to correct systematic errors and to remove screening artifacts, they are not universally effective and still require fair amount of human intervention. We introduce a fully automated quality control (QC) pipeline that can correct generic interplate systematic errors and remove intraplate random artifacts. The new pipeline was first applied to ~100 large-scale historical HTS assays; in silico analysis showed auto-QC led to a noticeably stronger structure-activity relationship. The method was further tested in several independent HTS runs, where QC results were sampled for experimental validation. Significantly increased hit confirmation rates were obtained after the QC steps, confirming that the proposed method was effective in enriching true-positive hits. An implementation of the algorithm is available to the screening community., (© 2016 Society for Laboratory Automation and Screening.)

In the quest for deciphering disease-associated biomarkers, high-performing tools for multiplexed protein expression profiling of crude clinical samples will be crucial. Affinity proteomics, mainly represented by antibody-based microarrays, have during recent years been established as a proteomic tool providing unique opportunities for parallelized protein expression profiling. But despite the progress, several main technical features and assay procedures remains to be (fully) resolved. Among these issues, the handling of protein microarray data, i.e. the biostatistics parts, is one of the key features to solve. In this study, we have therefore further optimized, validated, and standardized our in-house designed recombinant antibody microarray technology platform. To this end, we addressed the main remaining technical issues (e.g. antibody quality, array production, sample labelling, and selected assay conditions) and most importantly key biostatistics subjects (e.g. array data pre-processing and biomarker panel condensation). This represents one of the first antibody array studies in which these key biostatistics subjects have been studied in detail. Here, we thus present the next generation of the recombinant antibody microarray technology platform designed for clinical immunoproteomics.

Glycosyltransferase enzymes play diverse metabolic and regulatory roles by catalyzing the transfer of sugar molecules to protein, lipid, and carbohydrate acceptors, and they are increasingly of interest as therapeutic targets in a number of diseases, including metabolic disorders, cancer, and infectious diseases. The glycosyltransferases are a challenging target class from an assay development perspective because of the diversity of both donor and acceptor substrates and the lack of suitable glycan detection methods. However, many glycosyltransferases use uridine 5'-diphosphate (UDP) sugars as donor substrates, and detection of the free UDP reaction product provides a generic approach for measuring the activity of those enzymes. To exploit this approach for a broadly applicable high-throughput screening (HTS) assay for discovery of glycosyltransferase inhibitors, we developed a Transcreener(®) assay for immunodetection of UDP with a time-resolved Förster resonance energy transfer (TR-FRET) signal. We optimized the assay for detection of glycosyltransferase activity with nucleotide diphosphate (NDP) sugars at concentrations from 10 μM to 1 mM, achieving Z' values of 0.6 or higher. The assay was validated by orthogonal pooled screening with 8,000 compounds using polypeptide N-acetylgalactosaminyltransferase T3 as the target, and the hits were confirmed using an orthogonal readout. The reagents and signal were both stable for more than 8 h at room temperature, insuring robust performance in automated HTS environments. The TR-FRET-based UDP detection assay provides a broadly applicable approach for screening glycosyltransferases that use a UDP-sugar donor.

Inducing cardiomyocyte proliferation in post-mitotic adult heart tissue is attracting significant attention as a therapeutic strategy to regenerate the heart after injury. Model animal screens have identified several candidate signalling pathways, however, it remains unclear as to what extent these pathways can be exploited, either individually or in combination, in the human system. The advent of human cardiac cells from directed differentiation of human pluripotent stem cells (hPSCs) now provides the ability to interrogate human cardiac biology in vitro, but it remains difficult with existing culture formats to simply and rapidly elucidate signalling pathway penetrance and interplay. To facilitate high-throughput combinatorial screening of candidate biologicals or factors driving relevant molecular pathways, we developed a high-density microbioreactor array (HDMA)--a microfluidic cell culture array containing 8100 culture chambers. We used HDMAs to combinatorially screen Wnt, Hedgehog, IGF and FGF pathway agonists. The Wnt activator CHIR99021 was identified as the most potent molecular inducer of human cardiomyocyte proliferation, inducing cell cycle activity marked by Ki67, and an increase in cardiomyocyte numbers compared to controls. The combination of human cardiomyocytes with the HDMA provides a versatile and rapid tool for stratifying combinations of factors for heart regeneration.

The discovery of new antimalarial drugs able to target both the asexual and gametocyte stages ofPlasmodium falciparumis critical to the success of the malaria eradication campaign. We have developed and validated a robust, rapid, and cost-effective high-throughput reporter gene assay to identify compounds active against late-stage (stage IV and V) gametocytes. The assay, which is suitable for testing compound activity at incubation times up to 72 h, demonstrates excellent quality and reproducibility, with averageZ' values of 0.85 ± 0.01. We used the assay to screen more than 10,000 compounds from three chemically diverse libraries. The screening outcomes highlighted the opportunity to use collections of compounds with known activity against the asexual stages of the parasites as a starting point for gametocytocidal activity detection in order to maximize the chances of identifying gametocytocidal compounds. This assay extends the capabilities of our previously reported luciferase assay, which tested compounds against early-stage gametocytes, and opens possibilities to profile the activities of gametocytocidal compounds over the entire course of gametocytogenesis., (Copyright © 2016, American Society for Microbiology. All Rights Reserved.)