AI scores every new paper against your research focus — daily.
Built with researchers in Human Genetics, Cancer Biology, and Immunology
Over 4,000 papers are published every day across life sciences. No researcher can keep up manually.
Reading abstracts to decide what to read is not research. It's overhead. The average PhD student loses 4–6 hours per week to literature management.
Search terms don't know the difference between a landmark study and a methods footnote. PubMed returns 50 results. All of them look relevant.
The paper that changes your approach was published Tuesday. You found it three months later — after you already went down a dead end.
Built specifically for life science researchers — not a generic RSS reader.
Every paper scored 1–10 for Relevance, Novelty, and Signal relative to your specific project. Composite score weighted 50/30/20.
Every Monday, your highest-signal paper with a structured breakdown — key finding, what it challenges, and discussion questions for your lab.
PubMed, OpenAlex, bioRxiv, and medRxiv. Deduplicated by DOI so you never see the same paper twice across sources.
When a paper scores 9.0 or above, you get an email immediately. At most one per day so your inbox stays clean.
No import wizard. No configuration maze. Just tell us about your project.
Enter your focus, disease areas, methods of interest, and NIH grant number. Takes 3 minutes.
Papers fetched from four sources, deduplicated, and scored by Claude AI every 24 hours.
Breakthrough alerts for 9.0+ papers. Weekly digest every Monday. Save and annotate anything.
Scored literature that keeps pace with your field. Pay annually and get 2 months free — built for grant cycles.
Researcher
For the individual scientist
billed annually
Lab
Up to 15 members
billed annually
Department
Multiple labs, one roof
billed annually
Institution
Custom
Campus-wide
annual, grant-friendly
Join the waitlist — we’re onboarding research labs now. No credit card required.
NovelLens started because I was drowning in papers and couldn’t find a tool that actually understood what I was working on.
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I built NovelLens because I was spending more time searching PubMed than thinking about science. I want every researcher to have a tool that makes the literature work for them, not the other way around.
Jadon Porch
Founder, NovelLens · PhD Candidate, Human Genetics, VCU
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The idea that an AI can score a paper's relevance to my exact project — not just keyword-match it — changes what it means to stay current in a field that moves this fast.
Early access researcher
Cancer biology lab, East Coast R1
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My PI started using it and now the whole lab gets a shared reading list. Journal club preparation went from two hours of searching to fifteen minutes of actually reading.
Early access researcher
Immunology PhD student
PubMed, OpenAlex, bioRxiv, and medRxiv. Papers are deduplicated by DOI across sources so you never see the same paper twice. New papers are fetched every 24 hours.
Each paper's title, abstract, journal, and citation count are scored against your project profile — your keywords, disease areas, and methods — using Claude AI. The composite score weights relevance (50%), novelty (30%), and signal/impact (20%). Scores are 1–10 with one decimal place.
Yes. Your project profile, notes, and saved papers are private to you (or your lab, if you share them). Your data is never used to train AI models or shared across users.
Yes — the Lab Plan (coming soon) lets a PI create a lab space, invite members with a code, and share a reading list. Every member still gets their own personal feed scored against their own project.
The primary focus is life sciences — cancer biology, genetics, immunology, neuroscience, pharmacology. The scoring model works for any biomedical or clinical field covered by PubMed. Other scientific domains are on the roadmap.
PubMed alerts keyword-match. Google Scholar tracks citations. Neither understands what your project is actually about. NovelLens reads the abstract and scores it against your specific research context — disease area, methods, prior work — and ranks papers by how useful they are to you, not just whether a keyword appeared.
Start reading what matters.
Free for researchers · No credit card required