Neotask brings Open Targets biomedical intelligence into your research workflow - explore drug targets, diseases, and genetic evidence in plain English.
Search targets, diseases, drugs, and genetic variants across the Open Targets platform
Explore GWAS studies and credible sets for genetic association evidence
Cross-reference drug-target-disease relationships without writing GraphQL by hand
What You Can Do
Seven core capabilities cover the entire biomedical research workflow:
Target lookup - retrieve detailed information on any gene or protein target, including tractability assessments and known drug interactions
Disease exploration - query disease profiles with associated targets, therapeutic areas, and ontology mappings
Drug queries - look up approved and experimental drugs, their mechanisms of action, and clinical trial phases
Variant analysis - examine genetic variants with their functional consequences and associated traits
Study browsing - explore GWAS and other genomic studies with sample sizes, populations, and publication references
Credible set inspection - review fine-mapped credible sets from genetic association studies to identify causal variants
Platform search - free-text search across all entity types to find the right starting point for your research
Every action runs autonomously or requires your approval - you decide.
Try Asking
"What drugs are in clinical trials targeting BRAF?"
"Show me the top 20 targets associated with Crohn's disease by association score"
"Find all GWAS studies related to type 2 diabetes published after 2022"
"What is the tractability assessment for the ACE2 protein?"
"Search for variants in the APOE gene region linked to Alzheimer's disease"
"List credible sets for the lead variant rs7903146"
"What diseases are associated with the drug adalimumab?"
"Search for 'inflammatory bowel disease' and summarize the top results"
Pro Tips
Start broad with the search tool, then drill into specific targets or diseases once you have entity IDs.
Association scores range from 0 to 1 - filter by threshold to focus on the strongest evidence.
Multi-agent teams can research multiple therapeutic areas in parallel, then compile findings into a single report.
Combine target and drug queries to build a competitive landscape for a therapeutic area in one conversation.
Credible set data is most useful when you already have a lead variant - use study browsing first to find leads.
Multiple workspaces and capacity for larger teams.
Works Well With
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