This issue includes a discussion on the future of high-throughput screening through collaboration, an analysis of mass spectrometry as a structural biology tool and an exploration of the challenges of hit-to-lead when researching tropical diseases. Also in the issue are articles on immuno-oncology and assays.
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The Olympus scanR high-content screening station rapidly acquires quantitative data from cell-based assays
Self-learning microscopy opens new horizons in high-content analysis and advances phenotypic screening.
Research has found that artificial intelligence in drug discovery will be worth $1,434 million by the end of 2024.
On 5-6 November, ACC Liverpool hosted the ELRIG Drug Discovery event, which allowed R&D professionals to come together and discuss the latest industry developments.
New software has been developed that can reveal the detailed RNA-binding properties of proteins, which is important for characterising the pathology of many diseases.
Researchers have created an AI model that analyses the citations of studies, predicting their potential for eventual clinical application.
A new platform combines AI, flow chemistry and robotics to minimise the need for human intervention in the synthesis process.
The memory of mice with Alzheimer's greatly improved after they were injected with two newly discovered short peptides.
An algorithm has been developed which can predict the outcomes of complex chemical reactions with over 90 percent accuracy which can be applied to drug development.
Researchers have developed a new AI system which was able to discover and then successfully test several new compounds within 46 days.
AI has applications in many areas of research, including genomics. Slavé Petrovski of AstraZeneca reveals how AI is used in the study of the human genome and how it may evolve in the future.
Claus Bendtsen at AstraZeneca reveals how AI can be used to improve our understanding of disease, to help identify the causes of conditions and aid in drug discovery.
Designing new drug molecules is crucial to R&D. Dr Sam Genway suggests that one way to improve and speed up this process is using AI inspired by language translation.
Charlotte Walker-Osborn, a Partner and Head of Technology Sector (International) at global law-firm Eversheds Sutherland and a legal expert in technology law, explains some of the challenges and potential future of artificial intelligence (AI) in the field of drug discovery.