Answering "What is the role of KRAS in colorectal cancer?" takes a PhD-level scientist 11-16 hours manually. With Galactic AI, it takes 3 hours and covers all 22,500 relevant papers, not just 15.
Open each section to explore the time cost of manual target biology research, how Galactic AI compresses the search-and-synthesis phase, and the portfolio-wide impact at scale.
A PhD-level research team was investing significant time and budget in target prioritisation workflows that relied on fragmented data sources, manual expert input and slow iteration cycles. Answering a single complex target biology query took 11-16 hours manually and covered only a fraction of the relevant literature.
Biorelate's knowledge graph and AI-assisted query interface enabled researchers to interrogate causal biological evidence across disease areas in real time, covering all relevant publications rather than a manual subset. The platform consolidated disparate data sources and surfaced ranked target hypotheses, compressing the time from question to evidence-backed decision.
The client realised $1.2M in research cost savings and freed over 10,000 analyst hours in the first deployment period. Target prioritisation was accelerated by 72%, and the AI assistant resolved 1,291 research queries — reducing dependency on manual data retrieval and enabling researchers to focus on higher-order scientific judgement.
We'll demonstrate a live analysis from query to mechanistic pathway in under 5 minutes.