Diabetes R&D: Disease Modification, Cell Replacement, and Data Infrastructure

Contributed by: Suchithra V Mallan

Diabetes research and development includes therapies that delay disease onset and approaches aimed at replacing destroyed beta cells. This post reviews the current state of the science as of October 2025 and examines data management considerations across the diabetes R&D process.

Recent Developments in Diabetes Treatment Approaches

Type 1 diabetes (T1D) and type 2 diabetes (T2D) are associated with cardiovascular events, renal failure, blindness, and early mortality. The current pipeline includes immune-modulating antibodies and stem cell-derived islet replacement products.

In 2022, the FDA approved teplizumab (TZIELD), a monoclonal antibody that delays progression from pre-symptomatic stages of T1D to overt disease. This established a regulatory precedent for therapies that intervene before clinical disease onset.

Stem cell-derived islet (SC-islet) technologies have demonstrated the ability to restore glucose-responsive insulin secretion and reverse diabetes in animal models. Translation to human therapies faces challenges related to scalability, safety, and cost-effectiveness.

Drug Discovery: Target Identification and Data Integration

Current diabetes research spans immune modulation, beta-cell survival, islet regeneration, metabolic signaling, and organ interactions. Large-scale omics and longitudinal cohort datasets provide genetic, transcriptional, and immunologic information associated with disease progression, treatment response, and complications.

Machine learning models applied to curated and standardized datasets can:

• Identify endotypes of T1D and T2D that respond differently to therapies
• Predict progression from prediabetes or stage 2 T1D to clinical disease

Preclinical Development: Stem Cell-Derived Islets

Human induced pluripotent stem cell-derived islets (SC-islets) provide glucose-responsive insulin release, enriched beta-cell composition, and can reverse diabetes in toxin-induced mouse models.

Current SC-islet protocols face:

• Difficulty translating bench-scale differentiation into large, GMP-grade batches while maintaining yield and consistency
• Off-target cell populations and batch-to-batch variability

Research has demonstrated linear scale-up of SC-islet production from 0.1 L to 0.5 L bioreactors with increases in islet equivalents without compromising structure or function. 3D suspension bioreactors and optimized differentiation pipelines can improve scale and quality.

Regulatory Pathways

The regulatory framework for diabetes therapies includes:

• Immune therapies such as teplizumab follow biologic pathways for risk-benefit assessment in high-risk populations
• Islet transplantation has been recognized in the United States under a Biologics License Application framework, with requirements for cGMP manufacturing, purity, potency, and batch characterization
• Devices and drug-device combinations (encapsulation systems, biosensors integrated with insulin delivery) follow device or combination product pathways

Manufacturing Considerations

Biologics Manufacturing

The teplizumab program involved partnership with CDMOs managing process performance qualification (PPQ), scale-up, and validation under cGMP. CDMOs with multi-line mammalian cell culture facilities provide capacity and technology transfer capabilities for late-stage diabetes biologics.

Considerations for biologics manufacturing include:

• Maintaining product quality and comparability during scale-up or site changes
• Documenting process knowledge for technology transfer
• Monitoring tech transfer performance and detecting process drift

Cell Therapy Manufacturing

Islet transplantation and SC-islet replacement therapies face constraints related to limited donor pancreata (plural of pancreas) for primary islets and complex, multi-stage differentiation and aggregation workflows for stem cell-derived products.

Research has shown linear scale-up of SC-islet production with substantial increases in islet equivalents without compromising structure or function. cGMP cell therapy facilities are needed to ensure consistent quality, potency, and purity.

Current Treatment Modalities

 Data Management in Diabetes R&D

Diabetes R&D involves fragmented data from EHR systems, registries, biobanks, single-cell atlases, and trial datasets in incompatible formats. When curated, standardized, and linked, this data supports:

• Cross-trial analytics for treatment response, safety signals, and disease progression
• Machine learning models for target discovery, patient stratification, and process optimization
• Integration of preclinical pharmacology, toxicology, and translational biomarkers

Saturo Global Services

Saturo Global provides data services for life sciences organizations:

Data Curation Services: Standardization, annotation, and harmonization of heterogeneous datasets across clinical trials, registries, omics studies, and manufacturing records

Indexing & Abstracting Services: Transformation of research and patent information into searchable, structured knowledge

IP Research: Patent landscape mapping, whitespace identification, and support for technology transfer and licensing strategies

Data Visualization: Multi-layered technical data converted into visualizations for decision-making

 REFERENCES

[1] AGC Biologics (2023). AGC Biologics to commercially manufacture Provention Bio diabetes therapy TZIELD

[2] Tondin AR et al. (2025). Islet cell replacement and regeneration for type 1 diabetes. Frontiers in Endocrinology

[3] Frontiers in Transplantation (2025). The future of islet transplantation beyond the BLA approval

[4] Hogrebe NJ et al. (2023). Developments in stem cell-derived islet replacement therapies for diabetes

[5] Dadheech N et al. (2025). Scale up manufacturing approach for production of human iPSC-derived islets. Frontiers in Endocrinology