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The latest in drug discovery, from novel targets and screening tools through to automation and computational chemistry

Top R&D Stories of 2023

Through captivating articles, insight pieces, and spotlight interviews, we delve into the remarkable innovations, breakthroughs, and scientific marvels that have defined the landscape of research over the past year.
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Oxford Global's R&D Key 40 Stories 2022

Download a copy of the R&D Key 40 Stories 2022 eBook today.
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AI, Machine Learning & Computational Drug Design

Using Breakthrough Computational Tools for Drug Design and Discovery: AI/ML and Quantum Computing

How quantum annealers, which use quantum mechanics to solve optimisation problems by finding the lowest energy state of a system, are being used for drug discovery.
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Targeted Protein Degradation

Interview with Felix Hausch, Professor for Structure Based Drug Research at TU Darmstadt

Felix will deliver his presentation 'Clues for Molecular Glues' at Drug Discovery Europe 2023.
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AI, Machine Learning & Computational Drug Design

Using ML with DEL: Philogen and Google Partner in New Study

The partnership has developed a new machine learning assisted-technique for DEL screening.
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Neuroscience Discovery

Interview with Nicolas Vachicouras, CEO, Neurosoft Bioelectronics: Subdural Brain Interfaces

Talking with Nicolas Vachicouras, CEO of Neurosoft Bioelectronics about their subdural brain interface and its inaugural clinical testing for recording the human brain in the context of an epilepsy resective surgery.
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Neuroscience Discovery

Interview with Valentina Mosienko, Fellow and Lecturer in Neuroscience, University of Bristol

Navigating the neuroscientific pathways for anxiety towards druggable targets.
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AI, Machine Learning & Computational Drug Design

Revolutionary Organ Transplant Selection with Artificial Intelligence

A new Artificial Intelligence (AI) method enables scientists to cherry-pick organs for transplant.
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Pharma Data

“When Data Lakes Become Data Swamps”: Avoiding the Pitfalls of Data Regret by Implementing a Connected Data Ecosystem

The implementation of a streamlined and connected data ecosystem is critical to the transformation of healthcare technology and circumventing data regret.
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AI, Machine Learning & Computational Drug Design

AI Model Signifies 'Paradigm Shift' for Traumatic Brain Injury Risk

A new AI model shows promise for providing insights into long-term traumatic brain injury risk by accurately modelling the deformations that lead to brain damage.
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SmartLabs & Automation

Flow Robotics: flowbot ONE

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Pharma Data

Regulation & Policy Interview with Damion Nero, Head of Data Science at Takeda

Damion Nero, Head of Data Science at Takeda, discusses the regulatory challenges and opportunities of Real-World Data.
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AI, Machine Learning & Computational Drug Design

Computational Drug Design: Applications of AI and Machine Learning in Development

Recent advances in AI and machine learning have huge potential to improve the accuracy and speed of drug design. This discussion group report explores some of the current applications of different AI/ML approaches, including deep learning techniques.
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