Built from experience
Augmented by AI

Our AI-powered diligence engine synthesizes clinical, commercial, regulatory, and IP data — producing structured assessments that help support go/no-go decisions aligned with our investment committee recommendations.

• Multi-domain synthesis. Simultaneously pulling from clinical trial results, patent landscapes, regulatory precedents, and commercial benchmarks to produce a comprehensive risk profile.
• Scenario modelling. Generating probabilistic risk profiles across technical, regulatory, and commercial dimensions — with simulations for multiple development paths and deal structures.
• Deal benchmarking. Comparing proposed terms against comparable licensing transactions globally to inform structuring and negotiation strategy at the term-sheet stage.

Before committing capital, we validate assets across multiple evidence dimensions — clinical, translational, mechanistic, and competitive — using a systematic framework refined across hundreds of asset reviews.

• Translational evidence review. Assessing the strength of preclinical-to-clinical translation, biomarker maturity, and mechanistic pathway credibility with our SAB advisors.
• Competitive differentiation. Mapping the asset against current standard of care, pipeline competition, and unmet patient need across the relevant therapeutic area and geography.
• APAC pathway feasibility. Evaluating regulatory pathways, trial infrastructure, site availability, and patient population access across key APAC markets including Australia, Korea, Japan, and China.

Our statistical platform applies rigorous quantitative methods from endpoint selection to interim analysis planning — directly informed by our advisors' deep clinical trial expertise.

• Endpoint optimisation. Using historical trial data and AI modelling to select endpoints that maximise signal detection, regulatory acceptance, and commercial differentiation simultaneously.
• Adaptive trial design. Incorporating biomarker enrichment and response-adaptive randomisation frameworks to improve trial efficiency and overall probability of success.
• Real-world data integration. Anchoring statistical assumptions in RWD to generate more reliable sample size estimates, risk projections, and comparative effectiveness data for APAC regulators.

Diode Bio leverages relationships with leading CROs across Asia Pacific — combined with AI monitoring to deliver efficient, high-quality trial execution.

• Trusted CRO network. Deep relationships with Novotech, ICON, and regional specialist CROs, established through years of clinical operations at J&J, Merck, Parexel, and Sandoz.
• AI-powered monitoring. Real-time data quality monitoring, anomaly detection, and risk-based site oversight — reducing administrative burden and accelerating issue identification and resolution.
• Site performance analytics. Tracking enrollment velocity, protocol deviations, and data quality across sites with automated alerts and predictive risk modelling.