Computational approaches identify a transcriptomic fingerprint of drug-induced structural cardiotoxicity.

Structural cardiotoxicity (SCT) presents a high-impact risk that is poorly tolerated in drug discovery unless significant benefit is anticipated. Therefore, we aimed to improve the mechanistic understanding of SCT. First, we combined machine learning methods with a modified calcium transient assay in human-induced pluripotent stem cell-derived cardiomyocytes to identify nine parameters that could predict SCT. Next, we applied transcriptomic profiling to human cardiac microtissues exposed to structural and non-structural cardiotoxins. Fifty-two genes expressed across the three main cell types in the heart (cardiomyocytes, endothelial cells, and fibroblasts) were prioritised in differential expression and network clustering analyses and could be linked to known mechanisms of SCT. This transcriptomic fingerprint may prove useful for generating strategies to mitigate SCT risk in early drug discovery.

High throughput screening of 0.5 million compounds against CRAF using Alpha CETSAⓇ.

The cellular thermal shift assay (CETSA®) has increasingly been used in early drug discovery to provide a measure of cellular target engagement. Traditionally, CETSA has been employed for bespoke questions with small to medium throughput and has predominantly been applied during hit validation rather than in hit identification. Using a CETSA screen versus the kinase CRAF, we assessed 3 key questions: (1) technical feasibility - could the CETSA methodology technically be applied at truly high throughput scale? (2) relevance - could hits suitable for further optimisation be identified? (3) reliability - would the approach identify known chemical equity. Here, we describe the first large scale AlphaLISA SureFire based CETSA (Alpha CETSA) approach allowing us to screen a large library of almost 0.5 million compounds. We discuss the issues overcome in automating and executing the screen and describe the resulting screen output.

Thermal unfolding methods in drug discovery.

Thermal unfolding methods, applied in both isolated protein and cell-based settings, are increasingly used to identify and characterize hits during early drug discovery. Technical developments over recent years have facilitated their application in high-throughput approaches, and they now are used more frequently for primary screening. Widespread access to instrumentation and automation, the ability to miniaturize, as well as the capability and capacity to generate the appropriate scale and quality of protein and cell reagents have all played a part in these advances. As the nature of drug targets and approaches to their modulation have evolved, these methods have broadened our ability to provide useful chemical start points. Target proteins without catalytic function, or those that may be difficult to express and purify, are amenable to these methods. Here, we provide a review of the applications of thermal unfolding methods applied in hit finding during early drug discovery.

A perspective on the discovery of enzyme activators.

Enzyme activation remains a largely under-represented and poorly exploited area of drug discovery despite some key literature examples of the successful application of enzyme activators by various mechanisms and their importance in a wide range of therapeutic interventions. Here we describe the background nomenclature, present the current position of this field of drug discovery and discuss the challenges of hit identification for enzyme activation, as well as our perspectives on the approaches needed to overcome these challenges in early drug discovery.

Acoustic Mist Ionization Mass Spectrometry for Ultrahigh-Throughput Metabolomics Screening.

Incorporating safety data early in the drug discovery pipeline is key to reducing costly lead candidate failures. For a single drug development project, we estimate that several thousand samples per day require screening (<10 s per acquisition). While chromatography-based metabolomics has proven value at predicting toxicity from metabolic biomarker profiles, it lacks sufficiently high sample throughput. Acoustic mist ionization mass spectrometry (AMI-MS) is an atmospheric pressure ionization approach that can measure metabolites directly from 384-well plates with unparalleled speed. We sought to implement a signal processing and data analysis workflow to produce high-quality AMI-MS metabolomics data and to demonstrate its application to drug safety screening. An existing direct infusion mass spectrometry workflow was adapted, extended, optimized, and tested, utilizing three AMI-MS data sets acquired from technical and biological replicates of metabolite standards and HepG2 cell lysates and a toxicity study. Driven by criteria to minimize variance and maximize feature counts, an algorithm to extract the pulsed scan data was designed; parameters for signal-to-noise-ratio, replicate filter, sample filter, missing value filter, and RSD filter were all optimized; normalization and batch correction strategies were adapted; and cell phenotype filtering was implemented to exclude high cytotoxicity samples. The workflow was demonstrated using a highly replicated HepG2 toxicity data set, comprising 2772 samples from exposures to 16 drugs across 9 concentrations and generated in under 5 h, revealing metabolic phenotypes and individual metabolite changes that characterize specific modes of action. This AMI-MS workflow opens the door to ultrahigh-throughput metabolomics screening, increasing the rate of sample analysis by approximately 2 orders of magnitude.

Information-rich high-throughput cellular assays using acoustic mist ionisation mass spectrometry.

Cellular metabolites and phospholipids contain a vast amount of information about the current state of a cell, and are a useful resource for understanding the effects of drug candidates in vitro. Typical human cell-based assays in early drug discovery rely on simple readouts such as cell viability, or focus on single end-points revealed by an antibody or other label-based technologies. We introduce a generic 384-well plate-based workflow for data-rich cellular assays using facile sample preparation and direct analysis by acoustic mist ionization mass spectrometry (AMI-MS). The assays are compatible with adherent and suspension cells, and provide simultaneous information about a number of cellular small-molecule components (e.g., amino acids, nucleotides, phospholipids), cellular processes (e.g., proliferation, glycolysis, oxidative stress), as well as compound uptake and metabolism. Thanks to the high-throughput and low cost of analysis, the workflow can be introduced very early into any drug discovery pipeline to help select optimal lead molecules.

HepG2 (C3A) spheroids show higher sensitivity compared to HepaRG spheroids for drug-induced liver injury (DILI).

High-throughput, automation-friendly and therapeutically-predictive assays are needed in early drug discovery in order to prioritise compounds and reduce the risk of new drugs causing Drug-Induced Liver Injury (DILI). We evaluated the suitability of high-throughput 3D liver spheroid models of HepG2 (C3A clone) and HepaRG cell lines to predict DILI in early drug development. Spheroids were formed in 384-well ultra-low-attachment plates and dosed via direct acoustic droplet ejection at nine half-log spaced concentrations per compound. Spheroid viability was quantified with an ATP endpoint after a 4-day incubation with 150 drugs with known DILI liability. We derived a margin of safety for each cell line defined as the ratio between the IC50 values generated for each compound to their maximum plasma concentration Cmax which resulted in optimal classification accuracy. The margin of safety can be used to estimate a maximum safe Cmax for compounds in early drug discovery for which Cmax is not yet known. Both cell lines had similar level of accuracy in predicting DILI, with HepG2 spheroids being more sensitive. HepG2 spheroids had a sensitivity of 58% and a specificity of 83%, while HepaRG spheroids had a sensitivity of 47% and specificity of 86%. Ninety-nine of the 150 compounds were used to compare the relative sensitivities of HepG2 and HepaRG spheroids. HepaRG spheroids were more sensitive to 7 compounds and HepG2 spheroids were more sensitive to 34 compounds. In conclusion, across a diverse group of drugs HepG2 spheroids were more predictive of DILI compared to HepaRG spheroids.

Synthesis and properties of a biodegradable polymer-drug conjugate: Methotrexate-poly(glycerol adipate).

Polymer-drug conjugates have been actively developed as potential anticancer drug delivery systems. In this study, we report the first polymer-anticancer drug conjugate with poly(glycerol adipate) (PGA) through the successful conjugation of methotrexate (MTX). MTX-PGA conjugates were controllably and simply fabricated by carbodiimide-mediated coupling reaction with various high molar ratios of MTX. The MTX-PGA conjugate self-assembled into nanoparticles with size dependent on the amount of conjugated MTX and the pH of medium. Change in particle size was attributed to steric hindrance and bulkiness inside the nanoparticle core and dissociation of free functional groups of the drug. The MTX-PGA nanoparticles were physically stable in media with pH range of 5-9 and ionic strength of up to 0.15 M NaCl and further chemically stable against hydrolysis in pH 7.4 medium over 30 days but enzymatically degradable to release unchanged free drug. Although 30%MTX-PGA nanoparticles exhibited only slightly less potency than free MTX in 791T cells in contrast to previously reported human serum albumin-MTX conjugates which had >300 times lower potency than free MTX. However, the MTX nanoparticles showed 7 times higher toxicity to Saos-2 cells than MTX. Together with the enzymic degradation experiments, these results suggest that with a suitable biodegradable polymer a linker moiety is not a necessary component. These easily synthesised PGA drug conjugates lacking a linker moiety could therefore be an effective new pathway for development of polymer drug conjugates.

High-Throughput Spheroid Screens Using Volume, Resazurin Reduction, and Acid Phosphatase Activity.

Mainstream adoption of physiologically relevant three-dimensional models has been slow in the last 50 years due to long, manual protocols with poor reproducibility, high price, and closed commercial platforms. This chapter describes high-throughput, low-cost, open methods for spheroid viability assessment which use readily available reagents and open-source software to analyze spheroid volume, metabolism, and enzymatic activity. We provide two ImageJ macros for automated spheroid size determination-for both single images and images in stacks. We also share an Excel template spreadsheet allowing users to rapidly process spheroid size data, analyze plate uniformity (such as edge effects and systematic seeding errors), detect outliers, and calculate dose-response. The methods would be useful to researchers in preclinical and translational research planning to move away from simplistic monolayer studies and explore 3D spheroid screens for drug safety and efficacy without substantial investment in money or time.

Spheroid arrays for high-throughput single-cell analysis of spatial patterns and biomarker expression in 3D.

We describe and share a device, methodology and image analysis algorithms, which allow up to 66 spheroids to be arranged into a gel-based array directly from a culture plate for downstream processing and analysis. Compared to processing individual samples, the technique uses 11-fold less reagents, saves time and enables automated imaging. To illustrate the power of the technology, we showcase applications of the methodology for investigating 3D spheroid morphology and marker expression and for in vitro safety and efficacy screens. First, spheroid arrays of 11 cell-lines were rapidly assessed for differences in spheroid morphology. Second, highly-positive (SOX-2), moderately-positive (Ki-67) and weakly-positive (ßIII-tubulin) protein targets were detected and quantified. Third, the arrays enabled screening of ten media compositions for inducing differentiation in human neurospheres. Last, the application of spheroid microarrays for spheroid-based drug screens was demonstrated by quantifying the dose-dependent drop in proliferation and increase in differentiation in etoposide-treated neurospheres.

Separating chemotherapy-related developmental neurotoxicity from cytotoxicity in monolayer and neurosphere cultures of human fetal brain cells.

Chemotherapy-induced neurotoxicity can reduce the quality of life of patients by affecting their intelligence, senses and mobility. Ten percent of safety-related late-stage clinical failures are due to neurological side effects. Animal models are poor in predicting human neurotoxicity due to interspecies differences and most in vitro assays cannot distinguish neurotoxicity from general cytotoxicity for chemotherapeutics. We developed in vitro assays capable of quantifying the paediatric neurotoxic potential for cytotoxic drugs. Mixed cultures of human fetal brain cells were differentiated in monolayers and as 3D-neurospheres in the presence of non-neurotoxic chemotherapeutics (etoposide, teniposide) or neurotoxicants (methylmercury). The cytotoxic potency towards dividing progenitors versus differentiated neurons and astrocytes was compared using: (1) immunohistochemistry staining and cell counts in monolayers; (2) through quantitative Western blots in neurospheres; and (3) neurosphere migration assays. Etoposide and teniposide, were 5-10 times less toxic to differentiated neurons compared to the mix of all cells in monolayer cultures. In contrast, the neurotoxicant methylmercury did not exhibit selectivity and killed all cells with the same potency. In 3D neurospheres, etoposide and teniposide were 24 to 10 times less active against neurons compared to all cells. These assays can be used prioritise drugs for local drug delivery to brain tumours.

In vitro models of medulloblastoma: Choosing the right tool for the job.

The recently-defined four molecular subgroups of medulloblastoma have required updating of our understanding of in vitro models to include molecular classification and risk stratification features from clinical practice. This review seeks to build a more comprehensive picture of the in vitro systems available for modelling medulloblastoma. The subtype classification and molecular characterisation for over 40 medulloblastoma cell-lines has been compiled, making it possible to identify the strengths and weaknesses in current model systems. Less than half (18/44) of established medulloblastoma cell-lines have been subgrouped. The majority of the subgrouped cell-lines (11/18) are Group 3 with MYC-amplification. SHH cell-lines are the next most common (4/18), half of which exhibit TP53 mutation. WNT and Group 4 subgroups, accounting for 50% of patients, remain underrepresented with 1 and 2 cell-lines respectively. In vitro modelling relies not only on incorporating appropriate tumour cells, but also on using systems with the relevant tissue architecture and phenotype as well as normal tissues. Novel ways of improving the clinical relevance of in vitro models are reviewed, focusing on 3D cell culture, extracellular matrix, co-cultures with normal cells and organotypic slices. This paper champions the establishment of a collaborative online-database and linked cell-bank to catalyse preclinical medulloblastoma research.

Highlights of Children with Cancer UK's Workshop on Drug Delivery in Paediatric Brain Tumours.

The first Workshop on Drug Delivery in Paediatric Brain Tumours was hosted in London by the charity Children with Cancer UK. The goals of the workshop were to break down the barriers to treating central nervous system (CNS) tumours in children, leading to new collaborations and further innovations in this under-represented and emotive field. These barriers include the physical delivery challenges presented by the blood-brain barrier, the underpinning reasons for the intractability of CNS cancers, and the practical difficulties of delivering cancer treatment to the brains of children. Novel techniques for overcoming these problems were discussed, new models brought forth, and experiences compared.

In vitro co-culture model of medulloblastoma and human neural stem cells for drug delivery assessment.

Physiologically relevant in vitro models can serve as biological analytical platforms for testing novel treatments and drug delivery systems. We describe the first steps in the development of a 3D human brain tumour co-culture model that includes the interplay between normal and tumour tissue along with nutrient gradients, cell-cell and cell-matrix interactions. The human medulloblastoma cell line UW228-3 and human foetal brain tissue were marked with two supravital fluorescent dyes (CDCFDASE, Celltrace Violet) and cultured together in ultra-low attachment 96-well plates to form reproducible single co-culture spheroids (d = 600 µm, CV% = 10%). Spheroids were treated with model cytotoxic drug etoposide (0.3-100 µM) and the viability of normal and tumour tissue quantified separately using flow cytometry and multiphoton microscopy. Etoposide levels of 10 µM were found to maximise toxicity to tumours (6.5% viability) while stem cells maintained a surviving fraction of 40%. The flexible cell marking procedure and high-throughput compatible protocol make this platform highly transferable to other cell types, primary tissues and personalised screening programs. The model's key anticipated use is for screening and assessment of drug delivery strategies to target brain tumours, and is ready for further developments, e.g. differentiation of stem cells to a range of cell types and more extensive biological validation.

Multiplexing spheroid volume, resazurin and acid phosphatase viability assays for high-throughput screening of tumour spheroids and stem cell neurospheres.

Three-dimensional cell culture has many advantages over monolayer cultures, and spheroids have been hailed as the best current representation of small avascular tumours in vitro. However their adoption in regular screening programs has been hindered by uneven culture growth, poor reproducibility and lack of high-throughput analysis methods for 3D. The objective of this study was to develop a method for a quick and reliable anticancer drug screen in 3D for tumour and human foetal brain tissue in order to investigate drug effectiveness and selective cytotoxic effects. Commercially available ultra-low attachment 96-well round-bottom plates were employed to culture spheroids in a rapid, reproducible manner amenable to automation. A set of three mechanistically different methods for spheroid health assessment (Spheroid volume, metabolic activity and acid phosphatase enzyme activity) were validated against cell numbers in healthy and drug-treated spheroids. An automated open-source ImageJ macro was developed to enable high-throughput volume measurements. Although spheroid volume determination was superior to the other assays, multiplexing it with resazurin reduction and phosphatase activity produced a richer picture of spheroid condition. The ability to distinguish between effects on malignant and the proliferating component of normal brain was tested using etoposide on UW228-3 medulloblastoma cell line and human neural stem cells. At levels below 10 µM etoposide exhibited higher toxicity towards proliferating stem cells, whereas at concentrations above 10 µM the tumour spheroids were affected to a greater extent. The high-throughput assay procedures use ready-made plates, open-source software and are compatible with standard plate readers, therefore offering high predictive power with substantial savings in time and money.