Genmap-Pro™

AI-powered preclinical derisking for biotech, pharma and investors

Genmap-Pro helps biotech companies, pharma R&D teams and investors assess the biological, chemical and translational risk of drug discovery programs before committing significant experimental or financial resources.

A decision-support platform for early R&D and investment decisions

Genmap-Pro is designed to help answer critical questions:

  • Is the biological rationale strong enough?
  • Is the target aligned with the disease mechanism?
  • Are the proposed molecules likely to be active and selective?
  • Are there early ADME/Tox or safety liabilities?
  • What should be tested next experimentally?
  •  Is the program ready for further investment, partnership or due diligence?

Designed for decision-makers



Biotech CEOs & CSOs

Prioritize programs, challenge scientific assumptions and prepare investor-ready narratives.

Pharma R&D teams

Support target assessment, asset evaluation and early preclinical strategy.

Investors & due diligence teams

Obtain an independent, structured and scientifically grounded view of asset risk.

Academic translational teams

Evaluate therapeutic hypotheses and identify the most relevant next experiments.

What we offer

  1. Flash Due Diligence
    A rapid 1–2 week assessment to identify early red flags, opportunities and Go / No-Go signals.
  2. Asset Deep Dive
    A comprehensive scientific evaluation of a drug discovery asset, integrating biology, activity, selectivity, ADME/Tox, safety and strategic recommendations.
  3. Rare Disease Explorer
    A dedicated workflow for rare diseases and poorly documented mechanisms, from biological rationale to candidate prioritization.
  4. Candidate Sprint
    An AI-guided generation and evaluation workflow to explore, rank and prioritize new molecular options.
  5. Strategic Partnership
    A long-term collaboration model for recurring analyses, dashboards, scientific reviews and strategic decision support.

Each offer is designed to help decision-makers understand where a program is strong, where it is fragile, and what should be tested next.

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