Target assessments took a full quarter. Now, AI agents synthesize 1,000+ datasets to finish in hours.
A UK-based biotech company merging biology and computation to accelerate the discovery of RNA interference (RNAi) medicines for diseases with significant unmet needs.
Traditional drug discovery timelines were prohibitively slow, with document processing taking weeks and target-indication assessments requiring a...
“We need the best of the best LLMs at any given time. Everything we’ve done is modular, extensible, and changeable, so that as we get increasingly better technology, we can just plug it in.”
Biotech platform for computational drug discovery and RNAi medicines.
Cloud computing platform and on-demand infrastructure services.
Related implementations across industries and use cases
Matching phages required screening trillions of options. Gen AI simulates interactions, cutting discovery from 10 years to 2 months.
Predicting a single protein binding took 2,000 hours. Deep learning models now complete the task in just 15 minutes.
Manual synthesis bottlenecked research. Chemists now use conversational AI to configure robots that synthesize and test compounds.
Matching phages required screening trillions of options. Gen AI simulates interactions, cutting discovery from 10 years to 2 months.
Predicting a single protein binding took 2,000 hours. Deep learning models now complete the task in just 15 minutes.
Manual Excel models bottlenecked the network. Now, AI optimizes inventory while bots provide 24/7 service.
Manual scheduling trapped recruiters in logistics. AI now automates interview coordination, freeing teams for strategic work.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Custom hardware bottlenecked imaging. A switch to software-defined GPUs now renders photorealistic 3D hearts in real time.
Target assessments took a full quarter. Now, AI agents synthesize 1,000+ datasets to finish in hours.
A UK-based biotech company merging biology and computation to accelerate the discovery of RNA interference (RNAi) medicines for diseases with significant unmet needs.
Traditional drug discovery timelines were prohibitively slow, with document processing taking weeks and target-indication assessments requiring a...
“We need the best of the best LLMs at any given time. Everything we’ve done is modular, extensible, and changeable, so that as we get increasingly better technology, we can just plug it in.”
Biotech platform for computational drug discovery and RNAi medicines.
Cloud computing platform and on-demand infrastructure services.
Related implementations across industries and use cases
Matching phages required screening trillions of options. Gen AI simulates interactions, cutting discovery from 10 years to 2 months.
Predicting a single protein binding took 2,000 hours. Deep learning models now complete the task in just 15 minutes.
Manual synthesis bottlenecked research. Chemists now use conversational AI to configure robots that synthesize and test compounds.
Matching phages required screening trillions of options. Gen AI simulates interactions, cutting discovery from 10 years to 2 months.
Predicting a single protein binding took 2,000 hours. Deep learning models now complete the task in just 15 minutes.
Manual Excel models bottlenecked the network. Now, AI optimizes inventory while bots provide 24/7 service.
Manual scheduling trapped recruiters in logistics. AI now automates interview coordination, freeing teams for strategic work.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Custom hardware bottlenecked imaging. A switch to software-defined GPUs now renders photorealistic 3D hearts in real time.