Identify targets
How identify targets are reshaped as AGI capability advances.
The bottom line
Roughly 85% of the work in Identify targets is information-shaped — already within reach of AI delivery. The question here is not whether it shifts, but which tasks go first and who staffs the residual.
Why: With no seeded child occupations, this score is derived from the process name 'Identify targets' and its life-sciences/pharmaceutical R&D context. In drug discovery, target identification is heavily analytical, relying on bioinformatics, genomic data analysis, and literature review, making it predominantly digital knowledge work. A band-center digital score of 0.85 reflects this reliance on computational biology and data transformation.
grounded in the economy graph · digital scalar 0.85 · digital
Business-as-Code
Read as an executable program — the work decomposed into Code, Generative, Agentic, and Human.
Identify targets sits inside a larger value-flow — 1 parent structure it composes into. The hierarchy is grounding, not the story: it tells you which aggregate exposure Identify targets inherits.
Where Identify targets sits
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How the work flows
Trigger: An exploratory research initiative is launched to find biological molecules linked to a specific disease pathology.
- Analyze disease pathology and biological pathways
- Conduct genomic and proteomic data mining
- Identify candidate therapeutic macromolecules
- Validate biological relevance through in vitro or in vivo models
- Assess candidate druggability and safety profiles
- Approve the final biological target for development
Outcome: A biologically validated and druggable target is approved for subsequent lead discovery and drug screening.