Computational biology applied to type 2 diabetes research — modeling metabolic pathways, insulin signaling, and pancreatic beta-cell dysfunction through systems-level approaches.
Applying computational biology and systems-level modeling to understand the molecular mechanisms driving type 2 diabetes. Our endocrinology cohort works at the intersection of metabolic science and computational research, supervised by Dr. Oteng'o with active expertise in gene therapy and diabetes pathology.
Type 2 diabetes affects over 24 million people across sub-Saharan Africa, a number projected to double by 2045 — yet computational approaches to understanding its molecular drivers remain critically underdeveloped on the continent. Hela Bio's endocrinology program addresses this gap by training cohort members in the computational tools required to model diabetes at the systems level — from insulin receptor dynamics to pancreatic beta-cell failure cascades.
The program uses systems biology frameworks to model how metabolic disruptions propagate through insulin signaling pathways, and computational approaches to simulate beta-cell compensation and failure — laying the groundwork for novel diagnostic biomarkers and targeted therapeutic strategies for T2D in African populations.
Cohort members are trained in computational tools including metabolic flux analysis, kinetic modeling, and machine learning for multi-omics data integration. Each research project is designed to produce publishable results in international peer-reviewed journals, with patent consultation available for novel diagnostic and therapeutic discoveries.
"Type 2 diabetes is reshaping Africa's health landscape faster than infrastructure can respond. Computational approaches give us the tools to understand the disease at a molecular level — and train the next generation of researchers who will develop solutions designed for African populations."
Dr. Oteng'o — PhD Fellow, Endocrinology Program SupervisorThe endocrinology program follows Hela Bio's four-pillar model: academic–industry partnerships provide access to metabolic research labs and computational resources; PhD supervision guides experimental design through manuscript preparation; patent consultancy protects novel diagnostic discoveries; and the open-source IP framework (OpenMTA/BioBricks) ensures that foundational tools remain accessible to the broader diabetes research community.
Research associates work in project teams alongside ambassadors with clinical and industry experience in metabolic disease, under the direction of the PhD supervisor. This layered structure ensures that clinical insight informs computational work, and junior members develop both the technical fluency and domain expertise needed to advance diabetes research on the continent.
| Component | Description | Status |
|---|---|---|
| Insulin Signaling Pathway Modeling | Receptor dynamics & downstream cascades | Active |
| Beta-Cell Compensation Modeling | Pancreatic islet simulation | Active |
| Metabolic Flux Analysis | Whole-body metabolic modeling | In Development |
| T2D Biomarker Discovery | ML-driven multi-omics integration | In Development |
| Patent Filing | Novel discoveries from cohort work | Ongoing Consultation |
| Publication Pipeline | International peer-reviewed journals | In Preparation |
Our endocrinology team is available to discuss cohort enrollment, research collaboration, or supervisory partnerships. We respond to all qualified enquiries within 48 hours.
