Rank solid-tumor targets by their full evidence record. Before bench resources commit.
Avenzo pulls structured evidence from millions of papers and trial registries, scores each candidate target against the literature, and delivers a ranked assessment your discovery team can act on.
The target selection problem costs discovery teams months
Oncology research programs screen dozens of candidate targets each cycle. The evidence that separates a high-confidence target from a dead end is scattered across tens of thousands of papers, preprint archives, and trial registries. Synthesizing it manually takes weeks. Avenzo compresses that to hours.
Oncology drug discovery attrition: over 90 percent of candidates that enter clinical development fail, often because target evidence was incomplete at selection.
From query to ranked evidence in one workflow
Define the query
Specify the tumor type, pathway context, and therapeutic hypothesis. Avenzo scopes the evidence search accordingly.
Evidence ingestion and scoring
The platform ingests preclinical literature, clinical context data, and computational predictions. Each target gets a multi-dimensional evidence score.
Ranked report delivery
Targets are ranked by composite evidence depth. Your team receives a structured report with score breakdowns, source counts, and confidence flags.
Where discovery teams use Avenzo
Early target screening
Triage a long list of genomic alterations down to the candidates with the strongest literature support before committing any assay resources.
Learn moreGo/no-go evidence review
Before advancing a target from computational nomination to assay development, validate the evidence depth across independent source types.
Learn morePortfolio triage
Across a broader oncology pipeline, rank multiple active targets by comparative evidence quality to focus resource allocation.
Learn moreEvidence depth that moves faster than manual review
papers and trial records in the evidence corpus
based on our indexed literature database as of early-access beta
median time from query to ranked report
across early-access pilot runs
more evidence sources per target than manual literature review captures in a typical week-long synthesis
internal benchmark across early-access pilots, 8 research queries
founded in San Diego by oncologists and computational biologists
What early-access participants found
We used to spend three weeks synthesizing target evidence before each portfolio review. Avenzo compressed that to an afternoon. The ranked output maps directly onto our go/no-go criteria.
The multi-source scoring is what made it credible for us. We did not want a black box. Seeing the preclinical versus clinical context evidence broken out by source type gave us something we could defend in a target review meeting.
Built by people who have lived the problem
Athena Countouriotis
CEO & Co-FounderOncology clinical development and translational research background. Years building programs that bridge computational target identification and experimental validation in solid tumors.
Ravi Nair
CTO & Co-FounderSpent years building large-scale biomedical text mining and evidence integration systems. Background in natural language processing applied to scientific literature.
Naomi Stein
CSO & Co-FounderBackground in solid tumor biology and computational target validation. Worked on translational oncology programs where target evidence quality directly determined resource commitment decisions.
Join the early-access program
Avenzo is accepting a limited cohort of oncology research teams. Request access and a member of the team will be in touch.