An ensemble machine learning model generates a focused screening library for the identification of CDK8 inhibitors.

The identification of an effective inhibitor is an important starting step in drug development. Unfortunately, many issues such as the characterization of protein binding sites, the screening library, materials for assays, etc., make drug screening a difficult proposition. As the size of screening libraries increases, more resources will be inefficiently consumed. Thus, new strategies are needed to preprocess and focus a screening library towards a targeted protein. Herein, we report an ensemble machine learning (ML) model to generate a CDK8-focused screening library. The ensemble model consists of six different algorithms optimized for CDK8 inhibitor classification. The models were trained using a CDK8-specific fragment library along with molecules containing CDK8 activity. The optimized ensemble model processed a commercial library containing 1.6 million molecules. This resulted in a CDK8-focused screening library containing 1,672 molecules, a reduction of more than 99.90%. The CDK8-focused library was then subjected to molecular docking, and 25 candidate compounds were selected. Enzymatic assays confirmed six CDK8 inhibitors, with one compound producing an IC50 value of ≤100 nM. Analysis of the ensemble ML model reveals the role of the CDK8 fragment library during training. Structural analysis of molecules reveals the hit compounds to be structurally novel CDK8 inhibitors. Together, the results highlight a pipeline for curating a focused library for a specific protein target, such as CDK8.

Improving in vitro screening compounds anti-Trypanosoma cruzi by GFP-expressing parasites.

BACKGROUND: Conventional microscopic counting is a widely utilised method for evaluating the trypanocidal effects of drugs on intracellular amastigotes. This is a low-cost approach, but it is time-consuming and reliant on the expertise of the microscopist. So, there is a pressing need for developing technologies to enhance the efficiency of low-cost anti-Trypanosoma cruzi drug screening. OBJECTIVES: In our laboratory, we aimed to expedite the screening of anti-T. cruzi drugs by implementing a fluorescent method that correlates emitted fluorescence from green fluorescent protein (GFP)-expressing T. cruzi (Tc-GFP) with cellular viability. METHODS: Epimastigotes (Y strain) were transfected with the pROCKGFPNeo plasmid, resulting in robust and sustained GFP expression across epimastigotes, trypomastigotes, and intracellular amastigotes. Tc-GFP epimastigotes and intracellular amastigotes were exposed to a serial dilution of benznidazole (Bz). Cell viability was assessed through a combination of microscopic counting, MTT, and fluorimetry. FINDINGS: The fluorescence data indicated an underestimation of the activity of Bz against epimastigotes (IC50 75 µM x 14 µM). Conversely, for intracellular GFP-amastigotes, both fluorimetry and microscopy yielded identical IC50 values. Factors influencing the fluorimetry approach are discussed. MAIN CONCLUSIONS: Our proposed fluorometric assessment is effective and can serve as a viable substitute for the time-consuming microscopic counting of intracellular amastigotes.

Autocorrelation analysis of a phenotypic screen reveals hidden drug activity.

Phenotype based screening is a powerful tool to evaluate cellular drug response. Through high content fluorescence imaging of simple fluorescent labels and complex image analysis phenotypic measurements can identify subtle compound-induced cellular changes unique to compound mechanisms of action (MoA). Recently, a screen of 1008 compounds in three cell lines was reported where analysis detected changes in cellular phenotypes and accurately identified compound MoA for roughly half the compounds. However, we were surprised that DNA alkylating agents and other compounds known to induce or impact the DNA damage response produced no measured activity in cells with fluorescently labeled 53BP1-a canonical DNA damage marker. We hypothesized that phenotype analysis is not sensitive enough to detect small changes in 53BP1 distribution and analyzed the screen images with autocorrelation image analysis. We found that autocorrelation analysis, which quantifies fluorescently-labeled protein clustering, identified higher compound activity for compounds and MoAs known to impact the DNA damage response, suggesting altered 53BP1 recruitment to damaged DNA sites. We then performed experiments under more ideal imaging settings and found autocorrelation analysis to be a robust measure of changes to 53BP1 clustering in the DNA damage response. These results demonstrate the capacity of autocorrelation to detect otherwise undetectable compound activity and suggest that autocorrelation analysis of specific proteins could serve as a powerful screening tool.

Fission Yeast as a Platform for Antibacterial Drug Screens Targeting Bacterial Cytoskeleton Proteins.

Bacterial cytoskeletal proteins such as FtsZ and MreB perform essential functions such as cell division and cell shape maintenance. Further, FtsZ and MreB have emerged as important targets for novel antimicrobial discovery. Several assays have been developed to identify compounds targeting nucleotide binding and polymerization of these cytoskeletal proteins, primarily focused on FtsZ. Moreover, many of the assays are either laborious or cost-intensive, and ascertaining whether these proteins are the cellular target of the drug often requires multiple methods. Finally, the toxicity of the drugs to eukaryotic cells also poses a problem. Here, we describe a single-step cell-based assay to discover novel molecules targeting bacterial cytoskeleton and minimize hits that might be potentially toxic to eukaryotic cells. Fission yeast is amenable to high-throughput screens based on microscopy, and a visual screen can easily identify any molecule that alters the polymerization of FtsZ or MreB. Our assay utilizes the standard 96-well plate and relies on the ability of the bacterial cytoskeletal proteins to polymerize in a eukaryotic cell such as the fission yeast. While the protocols described here are for fission yeast and utilize FtsZ from Staphylococcus aureus and MreB from Escherichia coli, they are easily adaptable to other bacterial cytoskeletal proteins that readily assemble into polymers in any eukaryotic expression hosts. The method described here should help facilitate further discovery of novel antimicrobials targeting bacterial cytoskeletal proteins.

Exploiting urine-derived induced pluripotent stem cells for advancing precision medicine in cell therapy, disease modeling, and drug testing.

The field of regenerative medicine has witnessed remarkable advancements with the emergence of induced pluripotent stem cells (iPSCs) derived from a variety of sources. Among these, urine-derived induced pluripotent stem cells (u-iPSCs) have garnered substantial attention due to their non-invasive and patient-friendly acquisition method. This review manuscript delves into the potential and application of u-iPSCs in advancing precision medicine, particularly in the realms of drug testing, disease modeling, and cell therapy. U-iPSCs are generated through the reprogramming of somatic cells found in urine samples, offering a unique and renewable source of patient-specific pluripotent cells. Their utility in drug testing has revolutionized the pharmaceutical industry by providing personalized platforms for drug screening, toxicity assessment, and efficacy evaluation. The availability of u-iPSCs with diverse genetic backgrounds facilitates the development of tailored therapeutic approaches, minimizing adverse effects and optimizing treatment outcomes. Furthermore, u-iPSCs have demonstrated remarkable efficacy in disease modeling, allowing researchers to recapitulate patient-specific pathologies in vitro. This not only enhances our understanding of disease mechanisms but also serves as a valuable tool for drug discovery and development. In addition, u-iPSC-based disease models offer a platform for studying rare and genetically complex diseases, often underserved by traditional research methods. The versatility of u-iPSCs extends to cell therapy applications, where they hold immense promise for regenerative medicine. Their potential to differentiate into various cell types, including neurons, cardiomyocytes, and hepatocytes, enables the development of patient-specific cell replacement therapies. This personalized approach can revolutionize the treatment of degenerative diseases, organ failure, and tissue damage by minimizing immune rejection and optimizing therapeutic outcomes. However, several challenges and considerations, such as standardization of reprogramming protocols, genomic stability, and scalability, must be addressed to fully exploit u-iPSCs' potential in precision medicine. In conclusion, this review underscores the transformative impact of u-iPSCs on advancing precision medicine and highlights the future prospects and challenges in harnessing this innovative technology for improved healthcare outcomes.

AutoDock-SS: AutoDock for Multiconformational Ligand-Based Virtual Screening.

Ligand-based virtual screening (LBVS) can be pivotal for identifying potential drug leads, especially when the target protein's structure is unknown. However, current LBVS methods are limited in their ability to consider the ligand conformational flexibility. This study presents AutoDock-SS (Similarity Searching), which adapts protein-ligand docking for use in LBVS. AutoDock-SS integrates novel ligand-based grid maps and AutoDock-GPU into a novel three-dimensional LBVS workflow. Unlike other approaches based on pregenerated conformer libraries, AutoDock-SS's built-in conformational search optimizes conformations dynamically based on the reference ligand, thus providing a more accurate representation of relevant ligand conformations. AutoDock-SS supports two modes: single and multiple ligand queries, allowing for the seamless consideration of multiple reference ligands. When tested on the Directory of Useful Decoys─Enhanced (DUD-E) data set, AutoDock-SS surpassed alternative 3D LBVS methods, achieving a mean AUROC of 0.775 and an EF1% of 25.72 in single-reference mode. The multireference mode, evaluated on the augmented DUD-E+ data set, demonstrated superior accuracy with a mean AUROC of 0.843 and an EF1% of 34.59. This enhanced performance underscores AutoDock-SS's ability to treat compounds as conformationally flexible while considering the ligand's shape, pharmacophore, and electrostatic potential, expanding the potential of LBVS methods.

Tumor Organoids: The Era of Personalized Medicine.

The strategies of future medicine are aimed to modernize and integrate quality approaches including early molecular-genetic profiling, identification of new therapeutic targets and adapting design for clinical trials, personalized drug screening (PDS) to help predict and individualize patient treatment regimens. In the past decade, organoid models have emerged as an innovative in vitro platform with the potential to realize the concept of patient-centered medicine. Organoids are spatially restricted three-dimensional clusters of cells ex vivo that self-organize into complex functional structures through genetically programmed determination, which is crucial for reconstructing the architecture of the primary tissue and organs. Currently, there are several strategies to create three-dimensional (3D) tumor systems using (i) surgically resected patient tissue (PDTOs, patient-derived tumor organoids) or (ii) single tumor cells circulating in the patient's blood. Successful application of 3D tumor models obtained by co-culturing autologous tumor organoids (PDTOs) and peripheral blood lymphocytes have been demonstrated in a number of studies. Such models simulate a 3D tumor architecture in vivo and contain all cell types characteristic of this tissue, including immune system cells and stem cells. Components of the tumor microenvironment, such as fibroblasts and immune system cells, affect tumor growth and its drug resistance. In this review, we analyzed the evolution of tumor models from two-dimensional (2D) cell cultures and laboratory animals to 3D tissue-specific tumor organoids, their significance in identifying mechanisms of antitumor response and drug resistance, and use of these models in drug screening and development of precision methods in cancer treatment.

Inhibitors of the Thioesterase Activity of Mycobacterium tuberculosis Pks13 Discovered Using DNA-Encoded Chemical Library Screening.

DNA-encoded chemical library (DEL) technology provides a time- and cost-efficient method to simultaneously screen billions of compounds for their affinity to a protein target of interest. Here we report its use to identify a novel chemical series of inhibitors of the thioesterase activity of polyketide synthase 13 (Pks13) from Mycobacterium tuberculosis (Mtb). We present three chemically distinct series of inhibitors along with their enzymatic and Mtb whole cell potency, the measure of on-target activity in cells, and the crystal structures of inhibitor-enzyme complexes illuminating their interactions with the active site of the enzyme. One of these inhibitors showed a favorable pharmacokinetic profile and demonstrated efficacy in an acute mouse model of tuberculosis (TB) infection. These findings and assay developments will aid in the advancement of TB drug discovery.

Potential impact of underlying diseases influencing ADME in nonclinical safety assessment.

Nonclinical studies involve in vitro, in silico, and in vivo experiments to assess the toxicokinetics, toxicology, and safety pharmacology of drugs according to regulatory requirements by a national or international authority. In this review, we summarize the potential effects of various underlying diseases governing the absorption, distribution, metabolism, and excretion (ADME) of drugs to consider the use of animal models of diseases in nonclinical trials. Obesity models showed alterations in hepatic metabolizing enzymes, transporters, and renal pathophysiology, which increase the risk of drug-induced toxicity. Diabetes models displayed changes in hepatic metabolizing enzymes, transporters, and glomerular filtration rates (GFR), leading to variability in drug responses and susceptibility to toxicity. Animal models of advanced age exhibited impairment of drug metabolism and kidney function, thereby reducing the drug-metabolizing capacity and clearance. Along with changes in hepatic metabolic enzymes, animal models of metabolic syndrome-related hypertension showed renal dysfunction, resulting in a reduced GFR and urinary excretion of drugs. Taken together, underlying diseases can induce dysfunction of organs involved in the ADME of drugs, ultimately affecting toxicity. Therefore, the use of animal models of representative underlying diseases in nonclinical toxicity studies can be considered to improve the predictability of drug side effects before clinical trials.

Discovery of the small molecular inhibitors against sclerostin loop3 as potential anti-osteoporosis agents by structural based virtual screening and molecular design.

Sclerostin is a secreted glycoprotein that expresses predominantly in osteocytes and inhibits bone formation by antagonizing the Wnt/ß-catenin signaling pathway, and the loop3 region of sclerostin has recently discovered as a novel therapeutic target for bone anabolic treatment without increasing cardiovascular risk. Herein, we used a structural based virtual screening to search for small molecular inhibitors selectively targeting sclerostin loop3. A novel natural product hit ZINC4228235 (THFA) was identified as the sclerostin loop3-selective inhibitor with a Kd value of 42.43 nM against sclerostin loop3. The simplification and derivation of THFA using molecular modeling-guided modification allowed the discovery of an effective and loop3-selective small molecular inhibitor, compound (4-(3-acetamidoprop-1-yn-1-yl)benzoyl)glycine (AACA), with improved binding affinity (Kd = 15.4 nM) compared to the hit THFA. Further in-vitro experiment revealed that compound AACA could attenuate the suppressive effect of transfected sclerostin on Wnt signaling and bone formation. These results make AACA as a potential candidate for development of anti-osteoporosis agents without increasing cardiovascular risk.

Drug-Online: an online platform for drug-target interaction, affinity, and binding sites identification using deep learning.

BACKGROUND: Accurately identifying drug-target interaction (DTI), affinity (DTA), and binding sites (DTS) is crucial for drug screening, repositioning, and design, as well as for understanding the functions of target. Although there are a few online platforms based on deep learning for drug-target interaction, affinity, and binding sites identification, there is currently no integrated online platforms for all three aspects. RESULTS: Our solution, the novel integrated online platform Drug-Online, has been developed to facilitate drug screening, target identification, and understanding the functions of target in a progressive manner of "interaction-affinity-binding sites". Drug-Online platform consists of three parts: the first part uses the drug-target interaction identification method MGraphDTA, based on graph neural networks (GNN) and convolutional neural networks (CNN), to identify whether there is a drug-target interaction. If an interaction is identified, the second part employs the drug-target affinity identification method MMDTA, also based on GNN and CNN, to calculate the strength of drug-target interaction, i.e., affinity. Finally, the third part identifies drug-target binding sites, i.e., pockets. The method pt-lm-gnn used in this part is also based on GNN. CONCLUSIONS: Drug-Online is a reliable online platform that integrates drug-target interaction, affinity, and binding sites identification. It is freely available via the Internet at http://39.106.7.26:8000/Drug-Online/ .

Engineered platforms for mimicking cardiac development and drug screening.

Congenital heart defects are associated with significant health challenges, demanding a deep understanding of the underlying biological mechanisms and, thus, better devices or platforms that can recapitulate human cardiac development. The discovery of human pluripotent stem cells has substantially reduced the dependence on animal models. Recent advances in stem cell biology, genetic editing, omics, microfluidics, and sensor technologies have further enabled remarkable progress in the development of in vitro platforms with increased fidelity and efficiency. In this review, we provide an overview of advancements in in vitro cardiac development platforms, with a particular focus on technological innovation. We categorize these platforms into four areas: two-dimensional solid substrate cultures, engineered substrate architectures that enhance cellular functions, cardiac organoids, and embryos/explants-on-chip models. We conclude by addressing current limitations and presenting future perspectives.

Screening for Forensically Relevant Drugs Using Data-Independent High-Resolution Mass Spectrometry.

Forensic and clinical laboratories are expected to provide a rapid screening of samples for a wide range of analytes; however, the ever-changing landscape of illicit substances makes analysis complicated. There is a great need for untargeted methods that can aid these laboratories in broad-scope drug screening. Liquid chromatography hyphenated with high-resolution mass spectrometry (LC-HRMS) has become a popular technique for untargeted screening and presumptive identification of drugs of abuse due to its superior sensitivity and detection capabilities in complex matrices. An untargeted extraction and data acquisition method was evaluated for the broad screening of high-priority drugs of abuse in whole blood. A total of 35 forensically relevant target analytes were identified and extracted at biologically relevant low and high (10× low) concentrations from whole blood using supported liquid extraction. Data-independent acquisition was accomplished using ultraperformance liquid chromatography and a quadrupole time-of-flight mass spectrometry. Results were acceptable for screening assays, with limits of detection at or below the recommended low-concentration cutoffs for most analytes. Analyte ionization varied from 30.1 to 267.6% (average: 110.5%) at low concentrations and from 8.6 to 383.5% (average: 93.6%) at high concentrations. Extraction recovery ranged from 8.5 to 330.5% (average: 105.3%) at low concentrations and from 9.4 to 127.5% (average: 82.7%) at high concentrations. This variability was also captured as precision, ranging from 4.7 to 135.2% (average: 36.5%) at low concentrations and from 0.9 to 59.0% (average: 21.7%) at high concentrations. The method described in this work is efficient and effective for qualitative forensic toxicology screening, as demonstrated by analysis of 166 authentic suspected impaired driver and postmortem specimens. That said, it is critical that laboratories establishing untargeted LC-HRMS screening assays be aware of the strengths and limitations across diverse drug categories and chemical structures.

Fluid-Dynamic Culture of Tumour and Immune Cells for More Predictive Infiltration Studies and Immunotherapy Drug Screening.

Immunotherapies represent one of the current most promising challenges in cancer treatment. They are based on the boost of natural immune responses, aimed at cancer eradication. However, the success of immunotherapeutic approaches strictly depends on the interaction between immune cells and cancer cells. Preclinical drug tests currently available are poor in fully predicting the actual safety and efficacy of immunotherapeutic treatments under development. Indeed, conventional 2D cell culture underrepresents the complexity of the tumour microenvironment, while in vivo animal models lack in mimicking the human immune cell responses. In this context, predictability, reliability, and complete immune compatibility still represent challenges to overcome. For this aim, novel 3D, fully humanized in vitro cancer tissue models have been recently optimized by adopting emerging technologies, such as organ-on-chips (OOC) and 3D cancer cell-laden hydrogels. In particular, a novel multi-in vitro organ (MIVO) OOC platform has been recently adopted to culture 3D clinically relevant size cancer tissues under proper physiological culture conditions to investigate anti-cancer treatments and immune-tumour cell crosstalk.The proposed immune-tumour OOC-based model offers a potential tool for accurately modelling human immune-related diseases and effectively assessing immunotherapy efficacy, finally offering promising experimental approaches for personalized medicine.

Toward reproducible tumor organoid culture: focusing on primary liver cancer.

Organoids present substantial potential for pushing forward preclinical research and personalized medicine by accurately recapitulating tissue and tumor heterogeneity in vitro. However, the lack of standardized protocols for cancer organoid culture has hindered reproducibility. This paper comprehensively reviews the current challenges associated with cancer organoid culture and highlights recent multidisciplinary advancements in the field with a specific focus on standardizing liver cancer organoid culture. We discuss the non-standardized aspects, including tissue sources, processing techniques, medium formulations, and matrix materials, that contribute to technical variability. Furthermore, we emphasize the need to establish reproducible platforms that accurately preserve the genetic, proteomic, morphological, and pharmacotypic features of the parent tumor. At the end of each section, our focus shifts to organoid culture standardization in primary liver cancer. By addressing these challenges, we can enhance the reproducibility and clinical translation of cancer organoid systems, enabling their potential applications in precision medicine, drug screening, and preclinical research.

Analysis of post-market adverse events of istradefylline: a real-world study base on FAERS database.

Analyze the adverse event (AE) signals of istradefylline based on the FAERS database. By extracting large-scale data from the FAERS database, this study used various signal quantification techniques such as ROR, PRR, BCPNN, and MGPS to calculate and evaluate the ratio and association between istradefylline and specific AEs. In the FAERS database, this study extracted data from the third quarter of 2019 to the first quarter of 2023, totaling 6,749,750 AE reports. After data cleansing and drug screening, a total of 3633 AE reports related to istradefylline were included for analysis. Based on four calculation methods, this study unearthed 25 System Organ Class (SOC) AE signals and 82 potential preferred terms (PTs) related to istradefylline. The analysis revealed new AEs during istradefylline treatment, including reports of Parkinsonism hyperpyrexia syndrome (n = 3, ROR 178.70, PRR 178.63, IC 1.97, EBGM 165.63), Compulsions (n = 5, ROR 130.12, PRR 130.04, IC 2.53, EBGM 123.02), Deep brain stimulation (n = 10, ROR 114.42, PRR 114.27, IC 3.33, EBGM 108.83), and Freezing phenomenon (n = 60, ROR 97.52, PRR 96.76, IC 5.21, EBGM 92.83). This study provides new risk signals and important insights into the use of istradefylline, but further research and validation are needed, especially for those AE that may occur in actual usage scenarios but are not yet explicitly described in the instructions.

Formulation characterization of lecithin organogel as topical drug delivery system for psoriasis: In-vitro permeation and preclinical evaluation.

Psoriasis is a chronic inflammatory and proliferative skin disease that causes pathological skin changes and has a substantial impact on the quality of patient life. Apremilast was approved by the US Food and Drug Administration as an oral medication for psoriasis and is beneficial in mild to moderate conditions for chronic usage. However, 5%-7% of withdrawals were reported due to severe side effects. To address the issue, a localized drug delivery strategy via the topical route may be a viable approach. However, poor physicochemical properties make it vulnerable to passing through the skin, requiring a specialized drug delivery system to demonstrate its full potential via a topical route like lecithin organogel. The formulation was optimized by screening the suitable lecithin type and non-polar solvents based on the gel formation ability of lecithin and the solubility of apremilast in the solvent. The pseudo-ternary diagram was used to optimize the water content required to form the gel. The optimized gel was found to be shear thinning characterized for rheological parameters, in-vitro diffusion studies, and in-vitro skin distribution studies. Preclinical studies in Imiquimod-induced mice showed a better reduction in severity index, cytokine levels, and epidermal hyperplasia from the lecithin organogel group compared to the apremilast oral administration and marketed standard topical gel group. Based on these results, lecithin organogel can be considered a promising approach to deliver molecules like apremilast by topical route in psoriatic-like conditions.

Identification of a potent PCNA-p15-interaction inhibitor by autodisplay-based peptide library screening.

Proliferating cell nuclear antigen (PCNA) is an essential factor for DNA metabolism. The influence of PCNA on DNA replication and repair, combined with the high expression rate of PCNA in various tumours renders PCNA a promising target for cancer therapy. In this context, an autodisplay-based screening method was developed to identify peptidic PCNA interaction inhibitors. A 12-mer randomized peptide library consisting of 2.54 × 106 colony-forming units was constructed and displayed at the surface of Escherichia coli BL21 (DE3) cells by autodisplay. Cells exhibiting an enhanced binding to fluorescent mScarlet-I-PCNA were enriched in four sorting rounds by flow cytometry. This led to the discovery of five peptide variants with affinity to mScarlet-I-PCNA. Among these, P3 (TCPLRWITHDHP) exhibited the highest binding signal. Subsequent flow cytometric analysis revealed a dissociation constant of 0.62 µM for PCNA-P3 interaction. Furthermore, the inhibition of PCNA interactions was investigated using p15, a PIP-box containing protein involved in DNA replication and repair. P3 inhibited the PCNA-p1551-70 interaction with a half maximal inhibitory activity of 16.2 µM, characterizing P3 as a potent inhibitor of the PCNA-p15 interaction.

Cell viability and cytotoxicity assays: Biochemical elements and cellular compartments.

Cell viability and cytotoxicity assays play a crucial role in drug screening and evaluating the cytotoxic effects of various chemicals. The quantification of cell viability and proliferation serves as the cornerstone for numerous in vitro assays that assess cellular responses to external factors. In the last decade, several studies have developed guidelines for defining and interpreting cell viability and cytotoxicity based on morphological, biochemical, and functional perspectives. As this domain continues to experience ongoing growth, revealing new mechanisms orchestrating diverse cell cytotoxicity pathways, we suggest a revised classification for multiple assays employed in evaluating cell viability and cell death. This classification is rooted in the cellular compartment and/or biochemical element involved, with a specific focus on mechanistic and essential aspects of the process. The assays are founded on diverse cell functions, encompassing metabolic activity, enzyme activity, cell membrane permeability and integrity, adenosine 5'-triphosphate content, cell adherence, reduction equivalents, dye inclusion or exclusion, constitutive protease activity, colony formation, DNA fragmentation and nuclear splitting. These assays present straightforward, reliable, sensitive, reproducible, cost-effective, and high-throughput approaches for appraising the effects of newly formulated chemotherapeutic biomolecules on the cell survival during the drug development process.

Diving into drug-screening: zebrafish embryos as an in vivo platform for antimicrobial drug discovery and assessment.

The rise of multidrug-resistant bacteria underlines the need for innovative treatments, yet the introduction of new drugs has stagnated despite numerous antimicrobial discoveries. A major hurdle is a poor correlation between promising in vitro data and in vivo efficacy in animal models, which is essential for clinical development. Early in vivo testing is hindered by the expense and complexity of existing animal models. Therefore, there is a pressing need for cost-effective, rapid preclinical models with high translational value. To overcome these challenges, zebrafish embryos have emerged as an attractive model for infectious disease studies, offering advantages such as ethical alignment, rapid development, ease of maintenance, and genetic manipulability. The zebrafish embryo infection model, involving microinjection or immersion of pathogens and potential antibiotic hit compounds, provides a promising solution for early-stage drug screening. It offers a cost-effective and rapid means of assessing the efficacy, toxicity and mechanism of action of compounds in a whole-organism context. This review discusses the experimental design of this model, but also its benefits and challenges. Additionally, it highlights recently identified compounds in the zebrafish embryo infection model and discusses the relevance of the model in predicting the compound's clinical potential.