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- AI molecule generation platform
AI molecule generation platform
to speed up early-stage drug discovery in skin rejuvenation.
molecules confirmed active through wet lab validation
faster preclinical narrowing compared to baseline
Accelerating AI-driven molecule generation for a Series B biotech company working on skin rejuvenation therapies.
Pharma & Biotech
Industry
USA
Location
Generative AI modeling, transcriptomic analysis, pathway prediction, model validation
Services
$100,000–$200,000
Budget
Identifying and prioritizing novel small molecules for skin rejuvenation using transcriptomic data and pathway analysis — in a scalable, efficient way to support early-phase drug development.
See what we can do for youSolution
Blackthorn AI delivered a pipeline that combined generative AI, pathway graphs, and omics data ingestion to power molecule generation. The system enabled fast iteration, integration of biological constraints, and reduced reliance on trial-and-error lab synthesis.
Let’s talk about what’s possible
To accelerate molecule discovery, Blackthorn AI used:
Project duration
1–2 Months
Developed baseline predictive models from transcriptomics data and performed differential gene expression analysis.
3–4 Months
Integrated pathway-level biological data to prioritize targets and refine compound features.
5–6 Months
Ingested additional RNASeq datasets and trained PerturbNet for more accurate compound activity prediction.
7–8 Months
Generated thousands of novel compound candidates with skin rejuvenation potential using LLM-based tools.
9–10 Months
Finalized delivery, transferred documentation and results, and prepared for wet-lab validation phase.
Team Size
Delivering Impact
Beyond the values already highlighted, there’s even more to discover. Our commitment to innovation, client success, and impactful results sets us apart.
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moleculesConfirmed active compounds in wet lab — significantly validating model accuracy and ROI.
100%
AI-guided pipelineFully automated platform — no manual compound design or filtering during early-phase analysis.
