SLAS Discovery highlights innovative screening platforms and AI-driven analytics for treating oncology, infectious disease, and immunology research. The journal focuses on drug discovery sciences with a strong record of scientific rigor and impact, reporting on research that advances life sciences discovery and technology.
Research in SLAS Technology Vol. 40 explores smartphone glucose sensing and RNA-based therapeutics in Crohn's disease. The publication showcases innovative technologies and scientific advancements in life sciences discovery and development.
The webinar aims to connect Asian researchers with SLAS journals, publishing opportunities, and collaboration. SLAS Discovery and SLAS Technology journals are two peer-reviewed, open-access journals publishing innovative research and technologies.
A new high-throughput tool developed by Stanford University scientists can detect small changes in protein levels within cells, enabling faster and more efficient drug discovery. By amplifying these changes, researchers can identify potential therapeutic targets for diseases like cancer, potentially leading to breakthroughs in treatment.
Researchers have identified a widespread source of error in a popular genome study method and created a machine-learning tool to correct it. PATTY uses machine learning to reduce artifacts while preserving real signals in noisy data, giving researchers a clearer view of gene activity control.
SLAS Discovery highlights innovative screening platforms accelerating therapeutic discovery for neurodegenerative diseases, including a newly identified link to Alzheimer's progression. The journal showcases novel technologies and approaches to understand and treat human disease, advancing life sciences discovery and technology.
This volume of SLAS Technology highlights novel laboratory technologies, open-source software, and disease-specific tools for advancing life sciences research and development. The journal emphasizes the importance of education, knowledge exchange, and global community building to drive innovation in biomedical research.
A novel AI model called BINND has been developed to predict which DNA molecules bind to each other. The model achieved an accuracy of 83.5% in predicting DNA pairs that would bind, surpassing the state-of-the-art model by at least 10%. This improvement has significant utility for biomedical diagnostic tools and DNA computing applications.
A team of researchers has developed a new method for finding effective tuberculosis drugs by leveraging the PAC-MAN technique and artificial intelligence. The approach uses machine learning models to predict which chemical compounds can penetrate the outer membrane of the bacteria, paving the way for more efficient drug discovery.
A team from the University of Osaka has created a high-throughput platform to engineer versatile biosensors that can track lipid molecules in living cells. This method, called Cell surface Liposome Binding (CLiB) assay, uses yeast cells and fluorescence readouts to test protein variants' binding to lipids.
Researchers at Texas A&M University develop a laser technique called TRIP to directly measure quantum forces shaping proteins, enabling accurate prediction of how pharmaceutical drugs interact with them. This breakthrough could lead to the design of medicines tailored to specific diseases, revolutionizing precision medicine.
Researchers develop cellular model to reproduce NF1-associated tumour progression, identifying new therapeutic opportunities. The combination of olaparib and selumetinib shows promise in reducing tumour growth.
Researchers at Purdue University have developed a next-generation technology platform designed to dramatically accelerate one of the slowest stages of cancer drug discovery. The platform combines chemical synthesis, biological testing, and mass spectrometry into a single integrated workflow, allowing researchers to generate, evaluate, ...
The University of Virginia has joined SPARK GLOBAL to leverage resources and expertise in accelerating the development of new medicines. This collaboration aims to reduce time from lab discoveries to clinic trials, delivering tangible healthcare solutions to patients.
The study uses DNA barcodes to track and compare dozens of gold nanoparticle designs in living tumour models, identifying those effective at reaching mitochondria. Two formulations emerged as standout performers, achieving high tumour regression when combined with RNA therapy and photothermal treatment.
Volume 39 of SLAS Discovery highlights novel assays and AI-assisted workflows to accelerate personalized cancer immunotherapy. The journal aims to advance life sciences discovery through education, knowledge exchange, and global community building.
Advances in high-throughput proteomics and artificial intelligence are transforming biomarker discovery, disease prediction, and drug development. Proteomic technologies enable comprehensive snapshots of physiological and pathological states, driving breakthroughs in early diagnosis and personalized treatments.
Scientists at the University of Virginia Health System have developed a suite of AI-powered tools, called YuelDesign, YuelPocket and YuelBond, to transform how new drugs are created. These tools can design drug molecules tailored to fit their protein targets exactly, even accounting for protein flexibility.
The latest volume of SLAS Discovery highlights advances in 3D cell culture and novel technologies for drug discovery. Small molecule cytokine antagonists and a versatile ELISA for PPI inhibitor screening are among the key findings.
This issue highlights advancements in drug discovery, synthetic biology, and laboratory digitalization. SLAS Technology emphasizes scientific and technical advances that enable improved biomedical research and development.
The latest SLAS Technology volume showcases how AI, automation, and portable technologies are transforming drug discovery and diagnostics. This advancement enables the development of innovative therapeutic solutions and improved patient care.
Researchers at Goethe University are developing non-hormonal contraceptives to address declining pill use and side effects. The PREVENT project aims to create safe and effective alternatives, focusing on small molecules that block proteins in sperm or egg cells.
Researchers have developed a bacterial system to create millions of potential drug molecules that can target difficult-to-treat cancers. The approach combines chemical peptide stabilisation with the TBS assay to screen for effective peptides, which can then be tested in more complex tissue models and animal studies.
Researchers developed a novel method to immobilize proteins onto magnetic microbeads, allowing precise measurement of binding strength and efficient selection of target peptides. The technique achieved a 10,000-fold concentration in a single sorting step, significantly enhancing the efficiency of drug discovery research.
Researchers developed a new technique called CLASSIC that enables large-scale testing of complex DNA circuits in human cells. The approach uses artificial intelligence and machine learning to analyze vast numbers of complete circuits at once, providing scientists with a clearer picture of the rules governing genetic part behavior.
Researchers at the University of Virginia Health System have developed a new treatment for acute myeloid leukemia, a deadly form of blood cancer. The FDA-approved medication works by disrupting cellular protein interactions that drive leukemia cell growth and survival, offering patients a potential cure.
A team of scientists at the University of Tokyo has developed an automated, high-throughput system that uses machine learning to analyze droplets of biofluids for disease diagnosis. The technology relies on imaging drying processes to distinguish between normal and abnormal samples.
Scientists have created a micro-algal platform that allows for automated and fast testing of chloroplast genetic modifications, opening up plant chloroplasts to high-throughput applications. This platform enables researchers to fine-tune genetic circuits and identify which modifications have real potential.
The latest issue of SLAS Technology highlights significant advancements in biomedicine and diagnostics, with AI-powered tools achieving 99.9% accuracy in detecting monkeypox. Additionally, the journal showcases innovative lab technologies, including multi-camera zebrafish assays and infection-proof titanium implants.
The journal features novel FAK-paxillin inhibitors, a venom toxin screening platform, and AI-driven solubility prediction for compound discovery. SLAS Discovery highlights innovative technologies to understand and treat human disease.
The Society for Laboratory Automation and Screening's two scientific journals, SLAS Discovery and SLAS Technology, have achieved substantial impact factor increases due to open access publishing. This shift has led to higher citations and visibility for authors, with SLAS Technology experiencing a notable rise of 1.2 points to 3.7.
Researchers tackle pressing challenges in drug discovery with innovative approaches, including high-throughput TRIP13 inhibitors and tau aggregation blockers. The journal focuses on advancing life sciences discovery and technology via education, knowledge exchange and global community building.
This issue of SLAS Technology features a high-precision microfluidic flow splitter that outperforms commercial alternatives, enabling even flow division and simplifying multi-inlet perfusion. The journal showcases technological leaps in the life sciences, including rapid pathogen detection and AI-driven insights into schizophrenia.
Critical Path Institute's Translational Therapeutics Accelerator awards $250,000 to researchers advancing a promising therapeutic pathway for type 1 diabetes. The project aims to address key challenges in T1D treatment, including beta-cell preservation and immune system modulation.
A recent study identifies 11 natural compounds that can inhibit the SARS-CoV-2 spike protein, including caffeine, which exhibits high binding stability and excellent solubility. The discovery highlights the potential of natural products in combating COVID-19 and demonstrates the versatility of widely known compounds like caffeine.
Researchers developed FAST-NPS, a new automated method to discover and scale up bioactive natural products from Streptomyces. The method uses self-resistance genes as markers to prioritize biosynthetic gene clusters with bioactivity.
The team's novel technique enables high-throughput screening of nanoparticle shapes, sizes, and modifications, reducing associated screening costs. The research demonstrates the distinct preferences of tumour cells for certain nanoparticle configurations, enabling personalized cancer treatments that are safer and more effective.
Genetic testing using high-throughput sequencing (HTS) technology has significantly improved detection rates for thalassemia, offering a valuable model for high-prevalence regions. HTS-based genetic testing offers greater sensitivity and specificity without adding significant costs.
Researchers have developed a large-scale drug screening technique that tracks drug targets inside cells, allowing for the identification of potential new drugs. The technology screens candidate drugs 100 times faster than standard manual techniques, enabling the discovery of previously unknown drugs.
A research team at SickKids and U of T has developed a robotic system that allows scientists to test numerous potential therapeutics in arrhythmogenic cardiomyopathy, a leading cause of sudden cardiac death among young adults. The technology enables the identification of five potential therapies for the condition.
Researchers will classify autism types, identify responsible genes, and develop precision therapy for autistic patients. The team will employ neural organoids derived from diverse brain samples to accelerate autism research.
A University of Oklahoma researcher has been awarded a NIH grant to evaluate thousands of natural products with therapeutic potential. The goal is to identify specific components of these products that have anticancer properties and understand how they work.
Researchers at City University of Hong Kong announce an advanced sperm selection system that signals a breakthrough in assisted reproduction. The system, called BLASTO-chip, uses microfluidic droplet technology to select live sperm from immotile samples with over 90% accuracy.
Researchers developed a novel EIT-EVA PCB sensor for non-invasive assessment of drug inhibition on ion channels. The system enables real-time monitoring of ion flow changes in response to drug exposure, offering a faster and more efficient alternative to traditional methods.
A new machine-learning model using serum fusion-gene levels predicts HCC with an accuracy of 83-91%, significantly improving upon current biomarkers like serum alpha-fetal protein. This breakthrough tool may help identify patients at risk and monitor cancer recurrence, leading to improved survival rates.
SourceElsevier·JournalAmerican Journal Of Pathology·TypeComputational simulation/modeling·DateJun 17, 2024
The latest SLAS Technology issue highlights recent breakthroughs in skin cutaneous melanoma, glycan-bead coupling, and acoustic ejection mass spectrometry. Researchers adapt technological advancements for life sciences exploration and experimentation in biomedical research and development.
Researchers develop an in vitro model to study tau aggregation, a process linked to neurodegenerative diseases like Alzheimer's and frontotemporal dementia. The approach offers a short timeline for generating data and facilitates the study of potential therapeutic interventions.
Researchers at University of Kansas discover a new compound that inhibits SARS-CoV-2 replication in cell models by targeting the 'Mac-1' protein. This finding offers hope for developing new treatments and preventing future pandemics.
A Dartmouth Engineering-led study discovered a new high-performance solar absorber material that is stable and earth-abundant. The researchers used a unique high-throughput computational screening method to evaluate approximately 40,000 candidate materials, leading to the discovery of the Zintl-phosphide BaCd2P2.
The lack of synergy between academia and industry in drug discovery hinders the development of effective treatments. Researchers discuss why many therapeutic molecules fail to reach clinical trials despite pre-clinical efficacy.
The University of Rochester is establishing a new NIH-funded center focused on developing FDA-qualified drug development tools related to barrier functions in disease. Researchers will create microphysiological systems with ultrathin membranes of human cells, aiming to reduce animal trials and improve drug efficacy.
Scientists have created a self-organizing neuromuscular junction model from human pluripotent stem cells to study complex neuromuscular diseases. The 2D and 3D cultures mimic the physiological situation, allowing researchers to perform high-throughput drug screening for novel treatments.
This special collection in SLAS Discovery highlights the significant impact of high-content imaging in basic and translational research. Researchers have made advancements in cell painting and phenotypic profiling, offering new therapeutic approaches for diseases such as Gaucher's.
The SLAS Technology October 2023 issue focuses on reducing laboratory automation waste through machine learning and novel systems. Researchers adapt technological advancements for life sciences exploration and experimentation, enabling improved biomedical research and development.
A study involving 119,606 Chinese newborns found that concurrent hearing and high-throughput genetic screening significantly enhances congenital hearing loss management. The detection rate of certain gene mutations was also reported, highlighting the importance of considering multiple factors for accurate diagnosis.
SourceBGI Genomics·JournalInternational Journal of Pediatric Otorhinolaryngology·TypeRandomized controlled/clinical trial·DateOct 12, 2023
The August 2023 issue of SLAS Technology features original research articles on nanodiamonds, automated buffer exchange, and epidermal growth factor. A new scheduling method called SAGAS is proposed to optimize life science experiments in laboratory automation.
A new study improves the chances of finding the right drug to kill individual cancers in children by incorporating high-throughput drug screening into precision medicine. The approach reveals additional drug sensitivities and predicts clinical response, leading to better treatment options.
The latest issue of SLAS Discovery features novel technologies and approaches to develop and characterize chemical and biological tools for human disease treatment. The journal reports on high-throughput screening-related research, including fluorescence polarization assay use and glycomimetics.
The June special issue of SLAS Technology highlights the latest developments in bioprinting, a transformative technology poised to revolutionize many aspects of medicine. Bioprinting is advancing at a rapid pace, with novel materials, fabrication techniques, and bio-ink compositions being developed.
A proof-of-concept study demonstrates the effectiveness of two supporting matrices in growing spheroids derived from patient cells for 3D drug sensitivity and resistance testing. This finding offers promising prospects for automating this process in drug testing.