Use Case: Benchmarking Risk Across Therapeutic Areas

Challenge

In clinical development, who runs a trial matters as much as what is being tested. Investors and analysts want to know whether a sponsor has the track record to complete a study successfully. Pharma companies and CROs need to evaluate potential partners before committing to collaborations. First-time sponsors may lack infrastructure, while large, experienced organisations often have stronger operational capacity. Without reliable benchmarks, sponsor credibility is reduced to reputation and guesswork.

Solution with this dataset

The Clinical Trial Success Probability Dataset introduces a Sponsor Reliability Index — a transparent, data-driven measure of sponsor performance. It combines past trial volume, completion history, and sponsor type (industry vs public vs NIH) to create a single interpretable metric. By including historical completion rates and first-time sponsor risk, the dataset offers a practical way to compare organisations on an even playing field.

Example Insight

The dataset shows that sponsor reliability varies widely. Industry sponsors and large research institutions often demonstrate higher completion consistency, while small or first-time sponsors tend to carry greater uncertainty. By quantifying this risk, users can benchmark sponsors across portfolios and therapeutic areas rather than relying on anecdotal evidence.

Impact

• Investors & Analysts – Prioritise diligence on high-value trials led by credible sponsors, while discounting those from organisations with weaker track records.

• Pharma & CROs – Use the Sponsor Reliability Index to vet licensing opportunities and select outsourcing partners with confidence.

• Consultancies – Deliver objective, evidence-backed sponsor assessments to clients during M&A, BD, or pipeline reviews.
  
  
  

Graph 1 – Sponsor Reliability

Illustrative example: Sponsors differ in reliability, with experienced organisations trending higher than first-time entrants.