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In this first interview of a two-part series, Andreas Kolleger explores the convergence of knowledge graphs and large language models. As the head of GenAI innovation at Neo4j, Andreas brings a unique cross-industry perspective on how these technologies can enhance life sciences workflows.
A new AI-powered approach is tackling the challenge of 'undruggable' diseases by designing peptides that can bind to and destroy previously untreatable proteins.
Results from Pistoia Alliance’s Lab of the Future survey has shared important findings about the challenges life science companies face.
16 September 2024 | By Drug Target Review
The increasing use of AI in the life science field marks a pivotal point in history. Although AI is now an indispensable tool in drug discovery, promising to save vast amounts of time and money, there are still many hurdles scientists encounter. This webinar will explore these challenges and offer…
There have been a slew of announcements over the past few months from AI-led biotechs around the potential of Large Language Models (LLM) in early drug discovery. In the third of a three-part series, Dr Raminderpal Singh presents some pragmatic guidelines for scientists in accessing and obtaining value from LLMs.
Traditional wet lab scientists working on target discovery, drug identification and drug optimisation have an opportunity to catch up with their AI-enabled peers – but why should they, and how? In this article – the second of a three-part series – Dr Raminderpal Singh touches on methods that are being…
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.
A new learning-based framework enables patients and caregivers to predict the timing of any of the five clinical groups of AD development.
The guide provides examples of how Transcreener allowed rapid assay development to enable screening for kinases in innate immune pathways.
Learn more about Euretos computational disease model and how it predicts many of the known drug targets for RA.
This ebook outlines Euretos’ approach to target discovery and indication expansion. Whilst also discussing data-driven target selection.
24 August 2023 | By Bio-Rad Laboratories Inc.
Watch our industry experts to learn about the tangible benefits and best practice of custom flow cytometry automation projects. You’ll discover how to reduce your challenges implementing tailored automation, controlling the quality of the data produced and improving the reliability of your data acquisition.
La Jolla biologists harness machine learning and computational tools to make sense of immune system data.
This article is the second part of Drug Target Review’s Izzy Wood’s discussion with Olivia Cavlan, Chief Corporate Development and Strategy Officer at Alchemab Therapeutics Ltd, exploring the role of AI in target discovery, its applications in personalised medicine, and the evolving landscape of pharmaceutical development.
The decisions you make about your biologics candidates early in the pipeline ultimately affect their success as therapeutics. Combine sizing and stability information to develop successful biologics.
