back to company universe
AI infrastructure

Arpeggio Bio

Arpeggio Bio is a pioneering pharmaceutical company that develops drugs targeting transcription factors using AI and high-throughput RNA-sequencing. With $20M in venture funding, we've targeted "undruggable" proteins like NRF2, TEAD, and GPX4 where our lead program is rapidly progressing towards a DC for the treatment of IO-resistant melanoma. With partnerships with J&J and FORMA, we've validated our platform in rare disease and inflammation with a significant Phase I success.

sources
1
Evidence entries preserved.
affiliations
1
Y Combinator
competitors
6
Mapped from High Signal graph features.
status
generated
D1 lookup
last updated
2026-07-15
16:41 UTC
source evidence
Why this company exists here

Y Combinator

yc-company-directory #1496

Arpeggio Bio is a pioneering pharmaceutical company that develops drugs targeting transcription factors using AI and high-throughput RNA-sequencing. With $20M in venture funding, we've targeted "undruggable" proteins like NRF2, TEAD, and GPX4 where our lead program is rapidly progressing towards a DC for the treatment of IO-resistant melanoma. With partnerships with J&J and FORMA, we've validated our platform in rare disease and inflammation with a significant Phase I success.

source
generated read
High Signal interpretation

Arpeggio Bio is classified as AI infrastructure from source descriptions and fund-directory context. Similar companies below are ranked from offline product facets and meaningful description overlap; category and source affiliation can only strengthen an existing product match. For lookup-created rows, the profile starts as pending enrichment until deeper source collection runs.

offline extraction
Product facets
AIhigh-throughput RNA-sequencing
mapping method
Similarity graph

Local clusters rerank extracted product concepts and description terms. The generated graph remains the fallback for sparse descriptions: offline reciprocal product-similarity graph: extracted concepts + description terms + bounded category/affiliation boosts. Minimum fallback score: 0; max competitors: 6.

discovery cluster

Companies similar to Arpeggio Bio

AI infrastructure · 6 peers

A deterministic local cluster built from offline product facets and meaningful description terms. Category and selected-institution affiliation provide bounded tie-breaks. Open any peer to continue exploring its cluster.

Nephrogen

match 72

Nephrogen is a Stanford biotech spin-out developing curative genetic medicines for kidney and pancreatic diseases. Kidney disease alone affects 1 in 7 Americans, and neither indication has any approved gene-based therapies. Nephrogen's underlying platform combines AI and high-throughput screening to engineer safer, more efficient, and less expensive gene delivery vehicles for reaching the kidney and pancreas, and has attracted non-dilutive funding from seven major pharmaceutical companies includ

shared extracted concept terms: high, throughput; shared product terms: pharmaceutical, develop, high, throughput; same category: AI infrastructure; shared affiliation: Y Combinator

Abalone Bio

match 68

Abalone Bio is tackling challenging undrugged targets underlying diseases affecting millions, focusing first cell-specific antibody drugs to treat obesity and metabolic disease without the GI side effects that cause 25% of GLP-1 drug patients to quit after 1 year. + High throughput experimental measurement uniquely leverages AI/ML: We’ve engineered cells to measure antibodies for pharmacological activity, not just structure or binding like others, 100 million at a time, 100X+ the throughput of o

shared product terms: bio, target, disease, drug; same category: AI infrastructure; shared affiliation: Y Combinator

Algen Biotechnologies

match 60

Algen is using CRISPR to uncover disease-driving RNA messages to find treatments for cancer, inflammation and diseases with high unmet needs. We are harnessing the power of CRISPR and machine learning to find first-in-class drugs that modulate RNA messages at single-cell resolution. Algen's founders are bioengineer from Jennifer Doudna Lab and biotech commercialization expert, teamed up with experienced pharmaceutical executives.

shared product terms: disease, rna, treatment, inflammation; same category: AI infrastructure; shared affiliation: Y Combinator

Rosebud Biosciences

match 57

Rosebud Biosciences accelerates drug development by screening drugs against organoids (micro-organs) that have the same gene mutations as the patients. We partner with therapeutics companies to screen their drugs, and we perform our own drug discovery for rare diseases that have no existing treatments. Our organoids are also fetal-like and enable discovery of novel drug targets for pediatric diseases. This technology was validated at Stanford, published in a prestigious journal, and has already

shared product terms: drug, target, like, treatment; shared affiliation: Y Combinator

Nomic Bio

match 57

Nomic is doing for protein profiling, what Illumina did for DNA sequencing. Our core technology, the nELISA, is a next-gen immunoassay platform that transforms the ELISA into a high-throughput, high-content, and high-versatility tool. Today we developed the nELISA for high-throughput drug discovery scientists, enabling them profile 100s of proteins at 10x higher throughput and 10x lower cost compared to existing solutions. We're offering the nELISA through early access programs to HTS groups in

shared product terms: develop, drug, high, throughput; shared affiliation: Y Combinator

Humane Genomics

match 51

Humane Genomics has developed a platform to engineer cancer killing viruses. We have taken a first principles approach to design and make oncolytic viral therapies. Using a highly lytic RNA virus engineered with "2 factor authentication" (using selective infection and selective replication) they have an on-target to off-target kill ratio > 1000. We are working on our first indication, pediatric liver cancer (hepatoblastoma), with our partners at Texas Children's Hospital, who are world leading e

shared extracted concept terms: rna; shared product terms: develop, target, factor, rna; shared affiliation: Y Combinator