What You Should Know:
– Garden has announced the launch of BLOOM (Branching Lookup Optimized for Organic Molecules), a Markush structure search engine designed to give AI drug-design teams near-instant verification of small-molecule intellectual property (IP) landscapes.
– As AI models accelerate the pace of molecule generation, the critical bottleneck has shifted from discovery to due diligence—ensuring that a new candidate isn’t already patented. BLOOM eliminates this bottleneck, enabling researchers to build legal certainty directly into their design process.
A Smarter Approach to IP Search
BLOOM utilizes a graph-based, agentic traversal method to rapidly compare Markush queries against millions of SMILES strings. By short-circuiting invalid candidates based on local atom and bond features, the system delivers results at unprecedented speed. This process replaces manual, time-consuming checks with a built-in verification step that provides a color-coded mapping to confirm atom- and bond-level compliance.
In benchmark testing, BLOOM demonstrated a 32.44x speed improvement over standard core-extraction string searches, completing comparisons in an average of 0.047 ms. It also proved more accurate, correctly identifying matches that traditional string methods missed. According to Garden’s founder and CEO, Adi Sidapara, “AI can propose thousands of viable chemistries in minutes. BLOOM closes the loop by telling you what’s already fenced off instantly.”
Accuracy and Seamless Integration
Beyond its speed, BLOOM also significantly reduces false positives that plague legacy search methods, which often fail to account for nuanced bond counts and positioning. This accuracy saves drug-design teams from tedious, atom-by-atom verification, making the process both automatic and scalable. The engine is fully integrated with Garden’s patent database, allowing every SMILES match to link directly to its underlying patent record. Garden’s AI agent can then summarize, compare, and help prune the result sets, supporting workflows from rapid novelty triage to freedom-to-operate analysis.
Dr. Kavin Sivakumar, Founding ML Researcher at Garden, highlights the engine’s precision: “Small changes around an R-group can define patentability. BLOOM’s graph reasoning captures those subtleties at speed, so IP checks no longer throttle design.” With BLOOM, drug developers can make critical go/no-go decisions during the ideation phase, rather than waiting weeks for a manual review.
