Under the hood: 5 practical lessons from developing Large Language Model Applications for Drug Discovery
The biotech industry has been quick to explore the potential of Large Language Models, yet practical insights remain scarce. In a field that is both art and science, experience is key. Here we share our lessons learned from building LLM applications in drug discovery.
From the Depths of Literature: How Large Language Models Excavate Crucial Information to Scale Drug Discovery
In drug discovery, excavating the right information about potential drug targets and molecules from the depths of the scientific literature is key to success in biotech. Large Language Models will change the nature of this game. Here is how, in three concrete examples.
No-nonsense: How ChatGPT-Technology helps Biotechs find better Drug Targets faster
Large Language Models are poised to become an indispensable tool for biotechs looking to find their ideal drug targets. Evidence-grounded LLMs can sift through millions of publications, finding highly specific pieces of evidence in seconds, unlocking overlooked drug target opportunities.
Data management for early-stage biotechs: how to get started on the right path
Data management at a biotech needs to work for everyone – from CEO’s courting investors to lab scientists designing the next experiment. Get it wrong and you’ll either need to put up with your system’s foibles or go through a painful migration to a new system.
Why science-focused biotechs should be early adopters of cloud computing
For biotechs, cloud computing is a crucial ingredient to accelerate R&D through shorter cycle times, better collaboration and less distraction from what matters: the science.
Open goals: will AlphaFold2’s ‘open science’ usher in a drug discovery revolution?
DeepMind's release of AlphaFold2 created a lot of excitement, almost on par with the Human Genome Project. But what exactly are AlphaFold's groundbreaking applications in drug discovery?
'We are just starting to see the full spectrum of data science applications in agriculture'
With climate change and a growing world population, the agricultural industry needs to find greener solutions. Artificial intelligence and machine learning will be crucial, says Robert Berendes of Flagship Pioneering.
Into the unknown: biotech’s quest to target the 'undruggable' proteome
Novel therapeutic modalities, such as PROTACs, allow access to formerly undruggable parts of the proteome, shifting the frontiers of drug discovery. Artificial intelligence-based target scoring algorithms can help biotechs prioritize disease-relevant proteins as modality tailored drug targets.
AlphaFold: from accuracy to application?
AlphaFold has been called a revolution for drug discovery. Here we discuss potential use cases of AlphaFold, from fostering disease understanding, to aiding structural drug discovery.