African Precision Oncology · Intelligence Layer · Research Implementation

The intelligence layer for African precision oncology.

Kebeza is building the intelligence layer for African precision oncology — turning pathology, IHC, genomics, treatment response, recurrence, and survival data into actionable cancer intelligence for pharma, diagnostics, trial sponsors, oncologists, researchers, and AI-health companies.

The African Precision Oncology Atlas by Kebeza is an under-development, partnership-facing platform beginning with breast cancer in Uganda and designed to expand across major African cancers.

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The pain point

Pharma-grade African cancer intelligence does not exist in a clean, linked, usable form.

Precision oncology companies need representative cancer data to discover biomarkers, validate diagnostics, design trials, and understand treatment response. African patients remain underrepresented in these systems, while African cancer data is fragmented across pathology reports, FFPE tissue blocks, IHC results, oncology notes, treatment records, recurrence data, and incomplete follow-up.

Kebeza is designed to convert that fragmentation into a governed, de-identified, queryable cancer intelligence layer that can support African-relevant precision oncology, pharma partnerships, companion diagnostic validation, clinical trial feasibility, and future AI-assisted cancer care.

Why Africa needs this

African cancer patients remain underrepresented in precision oncology datasets, molecular oncology research, biomarker discovery pipelines, and treatment-response evidence systems.

Many African cancer pathways show concerning patterns: younger patients in some cancers, advanced stage at presentation, treatment delays, incomplete access to targeted therapies, poor survival, and uncertain drivers of treatment response. The Atlas is designed to help separate tumor biology, stage, access delays, treatment completion, subtype mix, pharmacogenomics, and health-system constraints.

Why Kebeza can build this

Kebeza is not starting from a blank page. It is grounded in cancer diagnosis, pathology expertise, digital pathology thinking, WhatsApp cancer access tools, Mulago Results Check, regional diagnostic networks, pathology image registry work, and cancer research implementation.

The African Precision Oncology Atlas is the next layer: moving from diagnosis and digital cancer workflows into a governed precision oncology evidence platform built around African pathology, tissue, molecular data, and outcomes.

The Kebeza thesis

Not a sequencing company. The African precision oncology layer.

Kebeza does not need to own sequencing machines to build this company. Sequencing can be outsourced to validated local, regional, or international partners. Kebeza’s defensible role is the clinical-pathology implementation layer: case identification, tissue linkage, report and IHC abstraction, stage and outcome capture, consent and governance design, de-identified data architecture, and the agentic interpretation interface.

The product is not raw data. The product is structured cancer intelligence: molecular tumor board summaries, biomarker-response analysis, cohort discovery, trial feasibility intelligence, companion diagnostic validation support, and AI-health model validation in African cancer populations.

African precision oncology African cancer genomics Tumor-normal sequencing Africa Human-supervised agents Treatment response intelligence Pharma-grade cohorts
Intelligence layers

Three layers that make APOA a startup, not only a research registry.

African Cancer Evidence Layer

Pathology, IHC, stage, epidemiology, FFPE tissue, matched normal status, tumor-normal sequencing, treatment response, recurrence, and survival.

APOA Agentic Interpretation Layer

Human-supervised agents structure reports, generate molecular tumor board style briefs, query cohorts, flag biomarker-response patterns, and produce trial feasibility intelligence.

Precision Oncology Applications

Pharma studies, companion diagnostic validation, African trial feasibility, molecular tumor board support, AI model validation, and biomarker discovery.

Pilot initiative

Phase 1: 100 fully sequenced breast cancer cases

The proposed pilot starts with breast cancer because it is common, clinically important, biologically diverse, and already relies on pathology, IHC, stage, treatment pathway decisions, response assessment, and follow-up.

The minimum credible pilot is 100 fully sequenced breast cancer cases, expandable toward 300 cases if funding allows. Every enrolled pilot case is intended for tumor-normal sequencing where ethics approval, consent, sample quality, and tissue availability allow.

Expansion plan

Phase 2: 1,000+ cases across major African cancers

After the breast cancer pilot, the Atlas can expand into a broader African cancer evidence platform covering common and priority cancers across multiple diagnostic and treatment settings.

  • Breast cancer
  • Colorectal cancer
  • Prostate cancer
  • Cervical cancer
  • Lymphoma
  • Childhood cancers
  • Other priority African cancers
Core data layers

The Atlas links the clinical, pathology, epidemiology, tissue, molecular, and outcome story.

Diagnostic and pathology layer

  • Pathology diagnosis
  • Histologic type and grade
  • IHC results such as ER, PR, HER2, Ki-67 where available
  • Digital pathology images where available

Clinical layer

  • Stage at presentation
  • Treatment given
  • Treatment or chemotherapy response
  • Recurrence or progression
  • Survival and follow-up status

Epidemiology layer

  • Age
  • Sex
  • Region/district
  • Relevant population context variables

Tissue and molecular layer

  • FFPE tissue block status
  • Matched normal sample status
  • Tumor-normal sequencing results
  • Variant and biomarker annotation where available
Economic engine

How APOA can become a venture-scale company.

The business is not charging African clinicians small subscriptions. The business is creating the governed African cancer intelligence layer that pharma, diagnostics companies, trial sponsors, AI-health companies, research groups, and molecular oncology partners need but cannot easily build themselves.

Sponsored cohorts

Disease-specific cohorts linking pathology, genomics, treatment, response, recurrence, and survival.

Trial feasibility

Subtype, biomarker, stage, geography, and outcome intelligence for African oncology studies.

Biomarker validation

Support for companion diagnostic validation and African-relevant biomarker-response studies.

AI-health validation

Governed datasets and workflows for validating oncology AI tools in African cancer populations.

Dashboards and agents

Human-supervised tools for cohort discovery, tumor board briefs, and research intelligence.

Strategic partnerships

Partnerships with sequencing, pharma, diagnostics, CRO, university, and cancer research partners.

Sample de-identified case flow

Illustrative workflow from suspected cancer to Atlas intelligence.

Patient presents with suspected cancerClinical suspicion begins the diagnostic pathway.
Biopsy or surgical specimen is processedThe tissue enters the routine diagnostic workflow.
Pathology confirms diagnosisHistologic type and grade are captured from the report.
IHC and stage are capturedMarkers such as ER, PR, HER2, and Ki-67 are recorded where available, alongside stage.
Epidemiology is recordedAge, sex, region/district, and relevant population context are captured in de-identified form.
FFPE block and matched normal sample are loggedTissue availability is tracked for sequencing readiness.
Tumor-normal sequencing layer is addedSequencing data can be linked through governed research partnerships.
Treatment and response are followedTreatment, response, recurrence, progression, and survival can be updated over time.
APOA agent generates intelligenceThe de-identified linked case supports tumor board briefs, cohort discovery, biomarker hypotheses, and trial feasibility.
Concept dashboard only · illustrative mock data

Illustrative intelligence dashboard

This dashboard is a concept view only. It does not display real patient data. It demonstrates the type of research and intelligence dashboard Kebeza wants to build with partners.

100Minimum phase 1 sequenced cases
BreastStarting cancer
9+Linked data layers
1,000+Scale target cases

Illustrative subtype distribution

ER/PR positive, HER2 negative42%
HER2 positive21%
Triple negative29%
Other / pending8%

Illustrative data completion

Pathology diagnosis100%
IHC captured78%
FFPE block logged64%
Follow-up outcome linked38%

Human-supervised APOA Agent

Sample outputs the agentic layer is designed to support:

Summarise this de-identified case for molecular tumor board review Compare response patterns by subtype, stage, treatment, and region/district Flag cohorts suitable for biomarker validation or trial feasibility review Generate hypotheses from linked pathology, IHC, genomic, and outcome data

All numbers above are illustrative placeholders for concept demonstration only. This is a research and decision-support concept. It does not replace pathologists, oncologists, molecular tumor boards, ethics committees, or clinical judgement.

Governance and ethics

The Atlas is proposed as a responsible, African-led research and implementation platform. It should be built with clear governance before enrollment, sequencing, data sharing, or external analysis.

  • African-led clinical and scientific leadership
  • Local ethics approval before enrollment
  • Informed consent for prospective cohorts
  • De-identification and privacy protection
  • Responsible data-use and material-transfer agreements
  • Benefit-sharing and local capacity building
  • Local authorship and scientific participation
  • Clear separation between research and direct clinical care decisions

Partnership invitation

Kebeza is seeking sequencing, genomics, oncology, AI-health, pathology, pharma, trial, funding, and implementation partners who want to help build African precision oncology infrastructure responsibly.

The immediate opportunity is a proposed pilot beginning with 100 fully sequenced breast cancer cases, expandable toward 300 cases, then scaling into 1,000+ cases across major African cancers.

Email Kebeza WhatsApp Kebeza

Build the African evidence layer for precision cancer care.

Kebeza is open to partnerships that combine cancer diagnostics, pathology, IHC, molecular testing, tumor-normal sequencing, AI-health systems, and real-world African cancer outcome data.

kebezahealth@gmail.com Back to Projects