scholarly journals An In Vivo Platform for Rapid High-Throughput Antitubercular Drug Discovery

Cell Reports ◽  
2012 ◽  
Vol 2 (1) ◽  
pp. 175-184 ◽  
Author(s):  
Kevin Takaki ◽  
Christine L. Cosma ◽  
Mark A. Troll ◽  
Lalita Ramakrishnan
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
Antitubercular Drug

FRET-Based Probe for High-Throughput DNA Intercalator Drug Discovery and In Vivo Imaging

ACS Sensors ◽  
2021 ◽  
Author(s):  
Chandrashekhar U. Murade ◽  
Samata Chaudhuri ◽  
Ibtissem Nabti ◽  
Hala Fahs ◽  
Fatima S. M. Refai ◽  
...  
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
In Vivo Imaging ◽  
Dna Intercalator

scholarly journals Recent Advances in In-Vitro Assays for Type 2 Diabetes Mellitus: An Overview

2020 ◽  
Vol 16 (1) ◽  
pp. 13-23
Author(s):  
Nazmina Vhora ◽  
Ujjal Naskar ◽  
Aishwarya Hiray ◽  
Abhijeet S. Kate ◽  
Alok Jain
Keyword(s):  
Type 2 Diabetes ◽  
Drug Discovery ◽  
High Throughput ◽  
High Throughput Screening ◽  
Antidiabetic Activity ◽  
Screening Methods ◽  
Selection Of

BACKGROUND: A higher rate of attenuation of molecules in drug discovery has enabled pharmaceutical companies to enhance the efficiency of their hit identification and lead optimization. Selection and development of appropriate in-vitro and in-vivo strategies may improve this process as primary and secondary screening utilize both strategies. In-vivo approaches are too relentless and expensive for assessing hits. Therefore, it has become indispensable to develop and implement suitable in-vitro screening methods to execute the required activities and meet the respective targets. However, the selection of an appropriate in-vitro assay for specific evaluation of cellular activity is no trivial task. It requires thorough investigation of the various parameters involved. AIM: In this review, we aim to discuss in-vitro assays for type 2 diabetes (T2D), which have been utilized extensively by researchers over the last five years, including target-based, non-target based, low-throughput, and high-throughput screening assays. METHODS: The literature search was conducted using databases including Scifinder, PubMed, ScienceDirect, and Google Scholar to find the significant published articles. DISCUSSION and CONCLUSION: The accuracy and relevance of in-vitro assays have a significant impact on the drug discovery process for T2D, especially in assessing the antidiabetic activity of compounds and identifying the site of effect in high-throughput screening. The report reviews the advantages, limitations, quality parameters, and applications of the probed invitro assays, and compares them with one another to enable the selection of the optimal method for any purpose. The information on these assays will accelerate numerous procedures in the drug development process with consistent quality and accuracy.

scholarly journals High Throughput Screening of Pharmacokinetics and Metabolism in Drug Discovery (II) —Investigation on In vitro and In vivo Correlation in Drug Metabolism Screening—

2005 ◽  
Vol 125 (1) ◽  
pp. 131-139 ◽  
Author(s):  
Hiroshi KOMURA ◽  
Kenichi MATSUDA ◽  
Yukie SHIGEMOTO ◽  
Iichiro KAWAHARA ◽  
Rieko ANO ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Drug Metabolism ◽  
High Throughput ◽  
High Throughput Screening

scholarly journals A FRET-based Probe for High Throughput DNA Intercalator Drug Discovery and In Vivo Imaging

2020 ◽  
Vol 118 (3) ◽  
pp. 315a
Author(s):  
Chandrashekhar U. Murade ◽  
Samata Chadhuri ◽  
Ibtissem Nabita ◽  
Hala Fahs ◽  
Fathima Refai ◽  
...  
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
In Vivo Imaging ◽  
Dna Intercalator

scholarly journals A cross-species drug discovery pipeline to identify and validate new treatments for osteosarcoma

2020 ◽  
Author(s):  
Jason A. Somarelli ◽  
Gabrielle Rupprecht ◽  
Erdem Altunel ◽  
Etienne M. Flamant ◽  
Sneha Rao ◽  
...  
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
Nuclear Export ◽  
Complex Disease ◽  
Rare Cancers ◽  
Synergistic Cytotoxicity ◽  
New Treatments ◽  
Discovery Pipeline

AbstractPurposeOsteosarcoma is a rare but aggressive bone cancer that occurs primarily in children. Like other rare cancers, treatment advances for osteosarcoma have stagnated, with little improvement in survival for the past several decades. Developing new treatments has been hampered by extensive genomic heterogeneity and limited access to patient samples to study the biology of this complex disease.Experimental designTo overcome these barriers, we combined the power of comparative oncology with patient-derived models of cancer and high-throughput chemical screens in a cross-species drug discovery pipeline.ResultsCoupling in vitro high-throughput drug screens on low-passage and established cell lines with in vivo validation in patient-derived xenografts we identify the proteasome and CRM1 nuclear export pathways as therapeutic sensitivities in osteosarcoma, with dual inhibition of these pathways inducing synergistic cytotoxicity.ConclusionsThese collective efforts provide an experimental framework and set of new tools for osteosarcoma and other rare cancers to identify and study new therapeutic vulnerabilities.

scholarly journals An orthotopic glioblastoma animal model suitable for high-throughput screenings

2018 ◽  
Vol 20 (11) ◽  
pp. 1475-1484 ◽  
Author(s):  
Linda Pudelko ◽  
Steven Edwards ◽  
Mirela Balan ◽  
Daniel Nyqvist ◽  
Jonathan Al-Saadi ◽  
...  
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
Large Scale ◽  
Light Sheet ◽  
Time Lapse ◽  
Zebrafish Model ◽  
Light Sheet Microscopy ◽  
Disease Biology ◽  
Vertebrate Model

Abstract Background Glioblastoma (GBM) is an aggressive form of brain cancer with poor prognosis. Although murine animal models have given valuable insights into the GBM disease biology, they cannot be used in high-throughput screens to identify and profile novel therapies. The only vertebrate model suitable for large-scale screens, the zebrafish, has proven to faithfully recapitulate biology and pathology of human malignancies, and clinically relevant orthotopic zebrafish models have been developed. However, currently available GBM orthotopic zebrafish models do not support high-throughput drug discovery screens. Methods We transplanted both GBM cell lines as well as patient-derived material into zebrafish blastulas. We followed the behavior of the transplants with time-lapse microscopy and real-time in vivo light-sheet microscopy. Results We found that GBM material transplanted into zebrafish blastomeres robustly migrated into the developing nervous system, establishing an orthotopic intracranial tumor already 24 hours after transplantation. Detailed analysis revealed that our model faithfully recapitulates the human disease. Conclusion We have developed a robust, fast, and automatable transplantation assay to establish orthotopic GBM tumors in zebrafish. In contrast to currently available orthotopic zebrafish models, our approach does not require technically challenging intracranial transplantation of single embryos. Our improved zebrafish model enables transplantation of thousands of embryos per hour, thus providing an orthotopic vertebrate GBM model for direct application in drug discovery screens.

scholarly journals 1341. Development of a Series of High-Throughput Screens to Identify Leads for Nontuberculous Mycobacteria Drug Design

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S485-S485
Author(s):  
Sarah McGuffin ◽  
Steven Mullen ◽  
Julie Early ◽  
Tanya Parish
Keyword(s):  
Drug Discovery ◽  
Drug Development ◽  
High Throughput ◽  
Nontuberculous Mycobacteria ◽  
Human Infection ◽  
Attrition Rate ◽  
In Vitro Assays ◽  
Vitro Assay

Abstract Background Nontuberculous mycobacteria (NTM), particularly Mycobacterium avium complex and Mycobacterium abscessus complex, cause significant morbidity and mortality in patients with impaired host immunity or pre-existing structural lung conditions. NTM infections are increasing at an alarming rate worldwide and there is a dearth of progress in regard to the development of efficacious and tolerable drugs to treat such infections. Traditional drug discovery screens do not account for the diverse physiological conditions, microenvironments, and compartments that the bacilli encounter during human infection. In order to help populate the NTM drug pipeline, and explore the disconnect between in vitro activity, in vivo activity, and clinical outcomes, we are developing a high throughput in vitro assay platform that will more closely model the unique infection-relevant conditions encountered by NTM. Methods We are developing and validating a suite of in vitro assays that screen compounds for activity against extracellular planktonic bacteria, extracellular bacteria within biofilms, intracellular bacteria, and nutrient-starved non-replicating bacteria. Results We are using both the smooth and rough morphotypes of M. abscessus and M. avium. We have validated high throughput assays to pharmaceutical standards for replicating and non-replicating M. abscessus. We have also tested a panel of 18 known anti-mycobacterial compounds. Assay development is currently underway to test compounds for activity against NTM in biofilm and inside macrophages as well. Conclusion To enhance hit identification for scaffolds to use as starting points for NTM drug development, focused libraries of compounds that have undergone significant preclinical profiling and/or compounds with known activity against M. tuberculosis (TB) will be screened. Such a “piggyback” approach usurps advances made in TB drug development and leverages them for NTM drug discovery. This will help expedite novel drug development, reduce attrition rate, and offer a shorter route to clinical use as it exploits the prior investment in medicinal chemistry, pharmacology, and toxicology. Disclosures All authors: No reported disclosures.

scholarly journals RNAi High-Throughput Screening of Single- and Multi-Cell-Type Tumor Spheroids: A Comprehensive Analysis in Two and Three Dimensions

2017 ◽  
Vol 22 (5) ◽  
pp. 525-536 ◽  
Author(s):  
Jiaqi Fu ◽  
Daniel Fernandez ◽  
Marc Ferrer ◽  
Steven A. Titus ◽  
Eugen Buehler ◽  
...  
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
High Throughput Screening ◽  
Attrition Rate ◽  
Three Dimensions ◽  
Cell Type ◽  
Tumor Spheroids ◽  
Flat Bottom ◽  
Cancer Subtypes

The widespread use of two-dimensional (2D) monolayer cultures for high-throughput screening (HTS) to identify targets in drug discovery has led to attrition in the number of drug targets being validated. Solid tumors are complex, aberrantly growing microenvironments that harness structural components from stroma, nutrients fed through vasculature, and immunosuppressive factors. Increasing evidence of stromally-derived signaling broadens the complexity of our understanding of the tumor microenvironment while stressing the importance of developing better models that reflect these interactions. Three-dimensional (3D) models may be more sensitive to certain gene-silencing events than 2D models because of their components of hypoxia, nutrient gradients, and increased dependence on cell-cell interactions and therefore are more representative of in vivo interactions. Colorectal cancer (CRC) and breast cancer (BC) models composed of epithelial cells only, deemed single-cell-type tumor spheroids (SCTS) and multi-cell-type tumor spheroids (MCTS), containing fibroblasts were developed for RNAi HTS in 384-well microplates with flat-bottom wells for 2D screening and round-bottom, ultra-low-attachment wells for 3D screening. We describe the development of a high-throughput assay platform that can assess physiologically relevant phenotypic differences between screening 2D versus 3D SCTS, 3D SCTS, and MCTS in the context of different cancer subtypes. This assay platform represents a paradigm shift in how we approach drug discovery that can reduce the attrition rate of drugs that enter the clinic.

scholarly journals Dr. Sim: Similarity Learning for Transcriptional Phenotypic Drug discovery

2021 ◽  
Author(s):  
Zhiting Wei ◽  
Sheng Zhu ◽  
Xiaohan Chen ◽  
Chenyu Zhu ◽  
Bin Duan ◽  
...  
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
Great Success ◽  
Similarity Learning ◽  
Integrated Network ◽  
High Throughput Data ◽  
Drug Mechanism ◽  
Perturbation Data

Transcriptional phenotypic drug discovery has achieved great success, and various compound perturbation-based data resources, such as Connectivity Map (CMap) and Library of Integrated Network-Based Cellular Signatures (LINCS), have been presented. Computational strategies fully mining these resources for phenotypic drug discovery have been proposed, and among them, a fundamental issue is to define the proper similarity between the transcriptional profiles to elucidate the drug mechanism of actions and identify new drug indications. Traditionally, this similarity has been defined in an unsupervised way, and due to the high dimensionality and the existence of high noise in those high-throughput data, it lacks robustness with limited performance. In our study, we present Dr. Sim, which is a general learning-based framework that automatically infers similarity measurement rather than being manually designed and can be used to characterize transcriptional phenotypic profiles for drug discovery with generalized good performance. We evaluated Dr. Sim on comprehensively publicly available in vitro and in vivo datasets in drug annotation and repositioning using high-throughput transcriptional perturbation data and indicated that Dr. Sim significantly outperforms the existing methods and is proved to be a conceptual improvement by learning transcriptional similarity to facilitate the broad utility of high-throughput transcriptional perturbation data for phenotypic drug discovery. The source code and usage of Dr. Sim is available at https://github.com/bm2-lab/DrSim/.

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