Who Tells You Whether the Molecule Your AI Just Designed Is Any Good?

VIDRAFT’s FINAL-Bench Open Discovery Challenge is a public leaderboard for AI-designed malaria drug candidates targeting the Plasmodium falciparum DHODH enzyme while avoiding the related human enzyme, addressing a claimed gap between increasingly accessible molecule generation and less accessible computational verification. The platform scores submitted SMILES or InChI structures across predicted whole-cell activity, target binding, selectivity, ADMET properties, novelty, and synthetic feasibility, with published scoring details, reference compounds, uncertainty penalties, and automatic rejection rules for duplicates, certain reactive or promiscuous motifs, and oversized molecules. Its developers describe identifying and correcting multiple scoring defects during validation, including thresholds that excluded approved drugs, size-normalization biases, inadequate inactive training data, software-call errors, fingerprint reconstruction issues, and miscalibrated confidence bounds. Entrants may use any AI model or other design method, receive public score explanations to support iteration, and retain ownership of their molecules, although public disclosure may affect patentability. The first malaria season closes on September 30, 2026, offers a USD 1,000 prize for the top entry, and emphasizes that leaderboard results are computational assessments rather than evidence of real-world efficacy or safety, which would require experimental validation.

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