Biotech & Life Sciences

Experiments leave a trail. Nextnet connects the path.

Nextnet connects lab notebooks, assay results, published literature, and commercial assets into a unified knowledge map.

Already querying their own science

MIT
Georgia Tech
MD Anderson Cancer Center
Siren Biotechnology
UC Berkeley
Queen's University Belfast
Emory University
NUHS
UC San Diego
Eisai
Imperial College London
Ben-Gurion University
University of Washington
UCSF
ElevateBio
Georgia Tech
Use cases

Fits into your R&D and commercial pipeline

Research & discovery

Target identification & validation

Researchers spend weeks on bioinformatics scripts and parsing literature to validate a target, often missing hidden chemistry discrepancies in legacy datasets. Nextnet connects internal assay logs and sequencing files to global scientific literature in a knowledge graph, uncovering biases and compressing weeks of analysis into minutes.

Mechanism of action mapping

Generic AI models routinely hallucinate pathway interactions because they lack company-specific assay context. Nextnet anchors internal experiments to open scientific literature, uncovering real gene-pathway-disease links with fully traceable citations and without hallucinations.

Clinical & regulatory

Out-licensing & partnering diligence

Business teams preparing out-licensing due diligence often interrupt bench scientists for preclinical records buried across scattered file shares. Nextnet converts unstructured preclinical files into a secure digital twin, allowing commercial teams to run technical diligence in minutes without interrupting research.

Regulatory filing assembly

Assembling IND filings and toxicology protocols requires weeks of matching trial schedules against regulatory safety limits. Nextnet cross-references internal dosing matrices against historical clinical precedents, automatically flagging safety gaps and building audit-ready regulatory dossiers.

Manufacturing & operations

Bioprocess & culture optimization

Cell therapy manufacturing traditionally relies on 20 days of expensive, trial-and-error lab runs to optimize culture conditions. Nextnet models cell-growth permutations in silico, narrowing experimental variables from dozens to single digits and slashing cycle times by 70%.

CDMO tech transfer & quality control

Handing off manufacturing protocols to contract manufacturers (CDMOs) frequently leads to batch variance, yield losses, and trade secret exposure. Nextnet unifies internal lab notes, flow cytometry logs, and partner CDMO records into a single walled-garden digital twin, enforcing strict quality control while locking down intellectual property.

Academia & funding

Grant & funding proposals

Cross-reference solicitation criteria against years of institutional proposals to find the best-aligned principal investigators (PIs) and necessary equipment.

PI support

Reduce draft-to-submission cycle time for grant proposals, freeing up research leaders from administration.

AI Ontology Infrastructure

Anchoring frontier AI models to deterministic truth.

Nextnet layers a life sciences ontology between your data silos and frontier AI models. Transform LLM word-guessing into deterministic graph-based logic. Zero-hallucination answers, strict permission controls, and flat-rate cost predictability.

Four data sources feeding a governance layer, an ontology engine and an entity graph of compounds, assays, patients, sites and products

See precisely how Nextnet performs in your enterprise. No generic demo. Your data. Your questions. Your requirements.

Proof

Tested in real labs. Proven on real data.

How a top research lab turned months of scattered spreadsheets and lab notes into instant, connected answers.

Top-20 U.S. Life Sciences Academic Lab

Case study · Genomics research division

Verified outcome

report generation

2 weeks → 20 mins

analysis

99% faster

per cycle savings

120 hours

Nextnet unified 6.4M rows of single-cell RNA-seq data across six research silos, previously scattered and disconnected.

Nextnet is a quantum leap for us. It’s like having a Q&A copilot with a colleague knowledgeable in every scientific discipline, giving me insights to iterate my research.

Dr. Timothy FongGenEdit

Links between genes, proteins, and pathways found within seconds that would have otherwise taken me weeks. The knowledge graph has the potential to help me discover previously hidden pathways and design better T cell therapies.

Dr. Cassian YeeMD Anderson Cancer Center

Keep your frontier AI model. Make it safe to deploy.