How to Evaluate Research Partnerships Well
Learn how to evaluate research partnerships by assessing scientific rigor, IP alignment, reproducibility, governance, and development readiness early.
Author Archive for: GenBio Inc.
Entries by GenBio Inc.
10 Best Natural Product Databases for Discovery
Compare the best natural product databases for rigorous discovery, from structure and spectra to source, bioactivity, prior art, and candidate planning.
Discovery Program Valuation: What Evidence Counts?
Discovery program valuation depends on reproducible evidence, defensible IP, and a credible plan to convert early activity into a development candidate.
Patent Landscape Analysis in Natural-Product Discovery
A patent landscape helps natural-product programs assess prior art, freedom-to-operate questions, and defensible paths for candidate development planning.
Crude Extracts Versus Pure Compounds in Discovery
Crude extracts versus pure compounds play distinct roles in natural-product discovery, informing evidence-based, clear candidate selection and planning.
What a Preclinical Candidate Dossier Must Show
A preclinical candidate dossier organizes evidence needed to assess identity, activity, reproducibility, safety signals, and a credible development path.
Target Versus Phenotype in Drug Discovery
Target versus phenotype approaches answer different discovery questions. Disciplined programs connect biological relevance, reproducibility, and selection.
Can Extract Activity Be Patented? Key Limits
Can extract activity be patented? Learn how evidence, composition, use, and reproducible claims shape intellectual-property strategy for natural products.
How to Assess the Best Natural Product CROs
Learn how to assess the best natural product CROs by examining fractionation, analytical rigor, reproducibility, IP strategy, and development planning.
Extract to Lead Case Study in Natural Products
This extract to lead case study shows how disciplined fractionation, characterization, and selection can prioritize natural-product development candidates.
