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9 April 2024 | By Eurofins Discovery
Join Dr Carleton Sage to learn about predicting ADME properties as a key approach to improving the efficiency of small molecule drug discovery. AI ADME model development approaches and case studies within drug discovery projects will be discussed.
Dr Richard Cote and Dr Ramaswamy Govindan of the Washington University School of Medicine elucidate how AI, particularly deep learning networks, could identify histopathologic features in non-small cell lung cancer, and impact the treatment approach for early-stage patients.
Natural products play an underappreciated role in drug discovery. Tandem mass spectrometry (MS/MS)-based metabolomics coupled with machine learning is allowing new, highly diverse molecules from natural products to be identified, revealing bioactive compounds and pinpointing promising drug targets. The additional dimension provided by trapped ion mobility (TIMS) enables researchers to…
Six molecules that had potent antibacterial effect against one of the world’s most dangerous antibiotic-resistant bacteria were generated.
Scientists have examined gene activity in mice models, noting important indicators of liver disease severity which may be used as therapeutic strategies.
Researchers have developed an algorithm which could improve diagnostics of ovarian high-grade serous carcinoma.
We had the privilege of speaking to Dr Víctor Sebastián Pérez, Associate Director of Computational Drug Design, following his presentation at ELRIG UK 2023. He shares his insights into how Exscientia is using AI to design drug candidates for cancer treatment.
Amidst the transformative era of AI in drug discovery, this report focuses on recent advancements, notably the development of highly accurate drug target models, and how AI is revolutionising precision in identifying drug targets.
Researchers have developed a computational analysis tool which will improve patient stratification and enable personalised medicine.
The ML algorithm explores how genetic mutations collectively influence a tumour’s reaction to drugs impeding DNA replication.
Learn more about Euretos computational disease model and how it predicts many of the known drug targets for RA.
Using an AI algorithm to predict glioblastoma’s most active kinase, researchers hope for a next-generation precision therapy targeting resistant cancers.
Dr Ketan Patel, Clarivate, shares his insights about the use of Real-World Data and genomic biomarker data and discusses how researchers can use these to better detect and diagnose diseases.
In the rapidly evolving landscape of mRNA biology and artificial intelligence (AI), Anima Biotech stands at the forefront, a unique approach that reshapes our understanding of diseases and transforms the drug discovery process. mRNA biology holds immense potential with RNAi drugs in the market and mRNA vaccines showing promise, particularly…
New software can make protein molecules that bind with high affinity and specificity to many biomarkers, including human hormones.
