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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.
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…
The model enables researchers to expand the number of tumours that they can study, increasing their ability to detect novel interactions.
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…
The expansion of Sino Biological and BioGeometry’s strategic partnership promises to accelerate drug discovery.
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.
RENAISSANCE can quantify unknown intracellular metabolic states, including metabolic fluxes.
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.
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.
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.
A new neural network computational model has been developed, which more closely reflects the abilities of real neurons and could advance AI progress.
The tool identified patients with high-risk disease, which normally goes unrecognised by traditional diagnostics.
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…
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…
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.
