news
New AI model may enable more targeted prostate cancer treatment
Based on MRI scans from 732 prostate cancer patients, the AI model identified the edges of 85 percent of the most radiologically aggressive lesions.
List view / Grid view
Informatics
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Bridging science and technology: a biotech CEO’s perspective
In this article, Dr Raminderpal Singh speaks to Neil Wilkie of Mironid Ltd. for a biotech CEO’s perspective on the transformative potential of AI, and the importance of bridging communication gaps between scientific and technical teams to drive innovation and efficiency in the pharmaceutical industry.
news
Proscia: advancing pathology AI development
Proscia has launched two new products which will help to accelerate discovery and development of new therapies and diagnostics.
news
The Pistoia Alliance: key findings on AI
Results from Pistoia Alliance’s Lab of the Future survey has shared important findings about the challenges life science companies face.
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AI-driven drug discovery: insights from Cresset
In this in-depth Q&A, Mutlu Dogruel, Vice President of AI at Cresset shares his insights surrounding chatbots, retrieval augmented generation and AI hallucinations, to open up new possibilities for innovation in pharmaceutical research.
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Part four: an industry leader’s perspective on managing data quality
In this four-part series, Dr Raminderpal Singh discusses the challenges surrounding limited data quality and offers some pragmatic solutions. In this fourth article, he talks to John Conway, Chief Visioneer Officer at 20/15 Visioneers for an expert perspective.
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Initial in vivo validation of novel cancer therapeutics using AI
In this Q&A, Dr Alan D. Roth, CEO of Oxford Drug Design, explains how his AI drug discovery company, which develops novel molecules for use in cancer treatments, has completed the first in vivo validation in its potential first-in-class approach against multiple tumours. A 28-day mouse trial showed clear efficacy…
news
New network model efficiently identifies cancer driver genes
The model enables researchers to expand the number of tumours that they can study, increasing their ability to detect novel interactions.
webinar
Overcoming critical challenges in AI-driven drug discovery
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…
news
Sino Biological and BioGeometry: advancing protein R&D
The expansion of Sino Biological and BioGeometry’s strategic partnership promises to accelerate drug discovery.
article
Part three: 15 pragmatic guidelines to handle data quality issues
In this four-part series, Dr Raminderpal Singh will discuss the challenges surrounding limited data quality, and some pragmatic solutions. In this third article, he discusses pragmatic guidelines to help support better data quality.
news
New AI tool accurately portrays metabolic states
RENAISSANCE can quantify unknown intracellular metabolic states, including metabolic fluxes.
article
Part one: an introduction to data quality
In this four-part series, Dr Singh will discuss the challenges surrounding limited data quality, and some pragmatic solutions. In this first article, the key attributes that define data quality and its requirement for data scientists are elucidated.
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Part three: pragmatic guidelines to getting the best out of LLMs
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.
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Part two: how ChatGPT enriched animal study results
Recently there has been a flurry of announcements from AI-led biotechs around the potential of Large Language Models (LLM) in early drug discovery. In the second of a three-part series, Dr Raminderpal Singh presents an example of usage of ChatGPT, which demonstrates how accessible LLMs have become for lab scientists.