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Identifies compounds with high risk of adverse effects.","intents":["I want to identify compounds likely to have off-target effects","I need to predict toxicity risks before advancing compounds to testing","I want to filter out compounds with high probability of safety issues"],"best_for":["safety-focused drug discovery programs","teams advancing compounds toward preclinical testing","organizations prioritizing early toxicity prediction"],"limitations":["Predictions based on known toxicity mechanisms may miss novel risks","Off-target prediction depends on coverage of relevant protein targets","In vivo toxicity is complex and may not be fully captured by in vitro predictions"],"requires":["compound structures","information on known toxicity targets and mechanisms","off-target protein panel or database"],"input_types":["compound structures (SMILES, MOL, SDF)","off-target protein information"],"output_types":["off-target binding predictions","toxicity risk scores","specific toxicity mechanism warnings","safety assessment reports"],"categories":["drug-discovery","safety-assessment","toxicology"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_leash-biosciences__cap_9","uri":"capability://drug.discovery.lead.series.expansion","name":"lead-series-expansion","description":"Generates or recommends structural analogs and chemical series expansions around known active compounds. Suggests modifications to improve binding affinity, selectivity, or ADMET properties while maintaining core activity.","intents":["I want to generate new analogs of my lead compound with predicted improvements","I need suggestions for chemical modifications to improve drug-like properties","I want to explore chemical space around my active series systematically"],"best_for":["lead optimization teams with active compounds","medicinal chemistry groups seeking design suggestions","programs in advanced optimization stages"],"limitations":["Generated analogs may not be synthetically feasible","Suggestions depend on training data and may be biased toward common scaffolds","Synthetic accessibility not explicitly considered in recommendations"],"requires":["lead compound structures with known activity","target protein information","optimization objectives (affinity, selectivity, ADMET)"],"input_types":["lead compound structures (SMILES, MOL, SDF)","activity and property data for leads","optimization parameters and constraints"],"output_types":["analog suggestions with predicted properties","chemical series expansions","property improvement predictions","design rationale and explanations"],"categories":["drug-discovery","computational-chemistry","lead-optimization"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":44,"verified":false,"data_access_risk":"high","permissions":["protein structure or sequence information","compound chemical structures (SMILES or 3D coordinates)","target protein class within model training domain","compound chemical structures","target indication or therapeutic area context","understanding of ADMET property relevance to program","compound structures","structures or sequences of target and off-target proteins","selectivity criteria and thresholds","information on available synthetic methods and reagents"],"failure_modes":["Less accurate for novel or understudied protein targets","Optimized for traditional small-molecule drugs, not biologics","Predictions depend on quality and quantity of training data for target class","Predictions less reliable for novel chemical scaffolds outside training data","May not capture complex drug-drug interactions or metabolic pathways","Performance varies across different ADMET properties","Selectivity prediction depends on availability of structural data for all targets","May not capture cellular selectivity or tissue-specific effects","Predictions less reliable for distantly related proteins","Synthetic accessibility assessment is heuristic and may not reflect actual difficulty","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.39999999999999997,"quality":0.82,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:31.446Z","last_scraped_at":"2026-04-05T13:23:42.546Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=leash-biosciences","compare_url":"https://unfragile.ai/compare?artifact=leash-biosciences"}},"signature":"4hz0dYhIWkfyfJLa1/qNaW1IsPaDPjiwGG9hP4eXGMw2S69jXSGqGWS3jXkLKqf1ELdpDS+NjQ7xz/aMRZREDw==","signedAt":"2026-06-23T00:32:55.720Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/leash-biosciences","artifact":"https://unfragile.ai/leash-biosciences","verify":"https://unfragile.ai/api/v1/verify?slug=leash-biosciences","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}