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Initial Drug Candidate Generation
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Linked challenge: Generative AI-Driven Optimization for Novel Multi-Target Drug Candidates
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Linked challenge
Generative AI-Driven Optimization for Novel Multi-Target Drug Candidates
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Original prompt text with formatting preserved for inspection.
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Your task is to generate 5-10 initial, diverse small-molecule drug candidates that could act as multi-target agonists for GLP-1R, GIPR, and GCGR. Use Llama 3.1 via Groq and Semantic Kernel to propose these structures in SMILES format, along with basic physiochemical descriptors (MW, cLogP). Document your prompt engineering strategy.
Adaptation plan
Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.
Keep stable
Preserve the role framing, objective, and reporting structure so comparison runs stay coherent.
Tune next
Swap in your own domain constraints, anomaly thresholds, and examples before you branch variants.
Verify after
Check whether the prompt asks for the right evidence, confidence signal, and escalation path.