Is the target cohort realistically identifiable and recruitable?
Scientific eligibility is not the same as operational availability. Review the full pathway from diagnosis and testing through prior therapy, referral, competition, and screening.
Oncology trial strategy & execution intelligence
Validate the patients, sites, and investigators behind your oncology trial plan.
OncoLattice helps sponsors and CRO partners test patient availability, site fit, investigator workload, competitive pressure, and protocol assumptions before plans become expensive to change.
AI-assisted · Evidence-traceable · Expert-reviewed · Compliance-aware
Cohort feasibilitySite & PI prioritizationCompetitive trial pressureSponsor- and CRO-ready decision questions
ANONYMIZED REPRESENTATIVE OUTPUTAsset X · Indication Y
Index 100Index 42Index 18
Site 01Diligence First
Site 02Validate
Site 03Hold
Site 04Backup
Investigator A
Investigator B
Investigator C
Investigator D
Cohort feasibility
Assess biomarker burden, line-of-therapy constraints, diagnosis pathways, testing requirements, screen-failure pressure, and competing studies.
- Diligence First
- Validate
- Hold
Illustrative, anonymized representation of an OncoLattice deliverable. It is not a real hospital ranking, patient-level dataset, enrollment forecast, or clinical recommendation.
Representative output
See the decision—not just the methodology.
OncoLattice converts fragmented public, operational, and permissioned feasibility signals into a reviewable decision package. Each conclusion should show the evidence behind it, the uncertainty that remains, and the next question to validate.Illustrative, anonymized representation of an OncoLattice deliverable. It is not a real hospital ranking, patient-level dataset, enrollment forecast, or clinical recommendation.
The decisions underneath execution
Four questions determine whether a trial plan can execute.
Which sites combine patient access with actual early-phase execution fit?
Reputation alone is insufficient. Compare activation behavior, relevant trial history, protocol fit, patient pathways, competitive density, and regional constraints.
Which investigators have relevant experience without hidden capacity risk?
Evaluate recent workload, adjacent-mechanism overlap, team support, public recruitment activity, and viable alternatives.
Which protocol, timeline, and feasibility assumptions still need evidence?
Turn unresolved assumptions into a prioritized validation plan before startup commitments and leadership narratives harden.
Built for the teams making the decision
One intelligence layer. Two ways to use it.
For Sponsors
Pressure-test the development plan before operational commitments become expensive to reverse.
- Validate cohort, country, site, and investigator assumptions.
- Compare or challenge feasibility logic without turning the relationship adversarial.
- Prepare management-, board-, and partner-ready decision materials.
- Identify what to validate before accepting a first-wave site plan.
For CRO Partners
Add a focused oncology intelligence layer to feasibility, site strategy, and sponsor communication.
- Sharpen patient-distribution and site-prioritization discussions.
- Provide more transparent evidence behind recommended site archetypes.
- Identify unresolved assumptions earlier in the startup process.
- Complement feasibility and operations teams without replacing execution.
OncoLattice does not replace CRO execution. We help make the strategy, diligence, and questions surrounding that execution more precise.
How the intelligence is built
Evidence is layered—not blended into a black box.
Public trial intelligence
Trial registries, publications, conference signals, investigator activity, site footprints, mechanism history, indication context, and competitor movement.
Permissioned real-world feasibility
De-identified or appropriately permissioned cohort and site-level feasibility signals where contractually and legally available.
AI-assisted analysis
Structured comparison, signal detection, evidence organization, competitive-overlap review, and reproducible ranking workflows.
Clinical and operational review
Human review of assumptions, uncertainty, clinical relevance, operational plausibility, and the questions that still require validation.
Scope the decision → Map the evidence → Challenge the assumptions → Deliver the next-action memo
Data availability varies by project. Public intelligence, third-party data, and permissioned real-world workflows are clearly distinguished in every scope.
Illustrative scenario
Biomarker-defined oncology program: from broad site list to focused diligence plan.
Hypothetical context: Illustrative scenario: a hypothetical sponsor evaluates a U.S. early-phase strategy for a biomarker-defined oncology cohort with uncertainty around patient availability, competing studies, and first-wave site selection.Questions reviewed
- Where could protocol constraints and testing requirements reduce the addressable cohort?
- Which site archetypes had relevant early-phase and mechanism experience?
- Which investigators showed possible workload or overlap risk?
- What should the sponsor validate with its CRO before accepting the initial site plan?
Illustrative analysis
- Mapped relevant public trial and competitor activity.
- Reviewed candidate-site and investigator signals.
- Developed an anonymized diligence-priority framework.
- Prepared CRO-facing validation questions and a management-ready decision memo.
Decision output
- Diligence-first site archetypes.
- Backup and hold criteria.
- Investigator workload flags and alternatives.
- Uncertainty register and next-action questions.
This illustrative workflow shows how a focused, evidence-traceable diligence plan could be produced. It does not describe a customer engagement or claim an enrollment outcome or site-performance guarantee.
Engagement options
Start with the smallest review that can resolve the current decision.
01 — Rapid Feasibility Review
A focused sponsor-side assessment of the most important patient, protocol, competitive, and execution risks.
- Best for
- Defined asset and indication; one or two urgent decisions before deeper planning.
- Typical output
- Concise diagnostic memo, risk register, evidence gaps, and readout call.
- Commercial display
- Starting from US$10,000 · Typically 7–10 business days
02 — Trial Strategy & Site Intelligence
The core OncoLattice engagement for patient feasibility, competitor mapping, site and PI prioritization, and sponsor/CRO decision questions.
- Best for
- Draft synopsis or early execution plan with unresolved U.S. or global assumptions.
- Typical output
- Strategy report, executive decision deck, diligence priorities, and CRO-ready question set.
- Commercial display
- Custom scope · Typically 3–4 weeks
03 — RWD-Enabled Cohort & Site Strategy
An advanced engagement that can incorporate de-identified or permissioned real-world feasibility signals where available.
- Best for
- Biomarker-, treatment-line-, or cohort-defined programs requiring deeper patient and site feasibility support.
- Typical output
- Cohort-feasibility framework, protocol-risk review, site-archetype strategy, and executive readout.
- Commercial display
- Custom scope · Third-party data costs quoted separately
CRO collaboration can be scoped within any engagement when a sponsor already has an execution partner.
Why OncoLattice
Focused judgment for decisions that generic data and standard feasibility forms do not resolve.
Oncology-specific context
Interpret site, investigator, protocol, and competitor signals within the mechanism, indication, modality, and early-phase setting.
Evidence traceability
Separate observed evidence, analytical inference, uncertainty, and recommended validation steps.
Sponsor–CRO alignment
Help both parties enter execution discussions with clearer assumptions and more focused questions.
China-to-global perspective
Translate China-origin asset context into U.S. and global development questions without treating geography as a substitute for evidence.
Leadership
Commercial translation, medical judgment, and AI systems.
Zhipei Luo
Chief Executive Officer · Commercial Strategy & PartnershipsComputer Engineering background at the University of Waterloo. Leads company strategy, commercialization, client development, and partnerships, translating technical analysis into decision materials for oncology development teams.
Lun-Hsiang Yuan, MD, PhD
Chief Technology Officer · Medical AI SystemsPhysician-scientist and medical AI technology expert leading technical strategy, clinical-intelligence methodology, data-product architecture, and quality boundaries for interpretable, reviewable oncology development intelligence.
Advisors and project experts are identified publicly only with explicit authorization. Their professional affiliations do not imply institutional endorsement.
OncoLattice draws on research foundations from the broader Apex AI ecosystem while commercial engagements remain separately governed.
Start with the decision
Bring the asset, indication, and question you need to resolve.
Share non-confidential context about the program, current development stage, target geography, and the decision in front of your team. We will determine whether a focused review can add value before requesting additional materials.
Discuss a TrialConfidential information can be exchanged after an appropriate CDA/NDA is in place.