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The potential of deep learning: generating drug targets
Researchers have designed synthetic, soluble versions of cell membrane proteins, which will enable faster and easier screening for new drugs.
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Artificial Intelligence
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Changing the paradigm of drug discovery processes with AI
We had the privilege of speaking to Cellarity’s CEO, Fabrice Chouraqui, about how the company is leveraging AI to completely revolutionise the drug discovery process and unlock treatments for a vast array of diseases, even in the absence of known targets.
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Part one: what can scientists do with LLMs today?
Recently there have been a flurry of announcements from AI-led biotechs around the potential of Large Language Models (LLM) in early drug discovery. In the first of a three-part series, Dr Raminderpal Singh explores what LLMs are, how early stage biotechs can take advantage of them, and what challenges they…
news
New AI process for accurate enrolment of patients to clinical trial
The AI model screened the medical records of heart failure patients more accurately, quickly and cheaply, compared to study staff.
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Kickstarting the use of AI for biotechs: part three
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 third of a three-part series – Dr Raminderpal Singh touches on the decisions that need…
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New algorithm forms atlas of histomorphological phenotypes
The algorithm can accurately diagnose cases of lung adenocarcinoma, determining structural features that are statistically most significant for assessing disease severity and likelihood of tumour recurrence.
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Kickstarting the use of AI for biotechs: part two
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…
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Kickstarting the use of AI for biotechs: part one
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 first of a three-part series – Dr Raminderpal Singh seeks to demystify the topic by outlining…
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Biomarker identification in the realm of rare diseases
In this Q&A, Debiopharm’s Principal Scientist Dr Luke Piggott defines the critical requirement of biomarkers for identifying rare diseases. He illuminates how AI-enhanced approaches are accelerating the drug discovery process, particularly regarding clinical trial enrolment, and the breakthroughs he hopes to see in the future.
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Machine learning’s growing importance in researching cells
As we move towards more generalised AI models, neural networks and natural language interfaces, we’re starting to see machine learning take the place of higher order reasoning and data analysis “sense making.” Traditional scientific inquiry has typically been about asking specific questions of a specific model system under specific conditions.…
webinar
SAFIRE: AI predicted ADME for drug discovery: leveraging BioPrint
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.
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Using AI to predict metastatic behaviour of NSCLC
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.
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Unlocking the potential of natural products in drug discovery
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…
news
New AI model could help to overcome antibiotic resistance
Six molecules that had potent antibacterial effect against one of the world’s most dangerous antibiotic-resistant bacteria were generated.
news
Improved understanding of the liver fibrosis process
Scientists have examined gene activity in mice models, noting important indicators of liver disease severity which may be used as therapeutic strategies.