# A real-world sequencing analysis within a year of every new approval

Source: https://onco.cc/ideas/idea-data-sequencing-analysis-per-approval/  
OnCo record `idea-data-sequencing-analysis-per-approval` (Idea). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

Trials tell us a drug works but not where it fits among the others. Commit to answering 'which order' from hospital data within a year of each approval.

## Summary

The question clinicians face after approval is sequence: first or second line, before or after the previous standard. Trials rarely address it. The proposal is a funded programme that, for every new oncology approval, runs a pre-registered target trial emulation of sequencing strategies in federated data within 12 months, published in a standard format and fed into guidelines as explicitly graded real-world evidence.

## Fields

- Kind: Idea
- Last checked: 2026-09-08
- Hypothesis: Systematic sequencing analyses will change guideline sequencing recommendations for at least a quarter of new approvals within two years of approval, and will identify sequences associated with worse survival that were being used in practice.
- Rationale: Sequencing analyses of ADCs, CDK4/6 inhibitors and immunotherapy have emerged from academic real-world studies years late; making them systematic and timely is a funding and infrastructure decision.
- Proposed test: Run the programme for one year of approvals in one federated network; count analyses delivered on time and guideline citations within 24 months.
- Maturity: speculative
- Actor: research

## Sources

- Bottleneck evidence (Weak real-world evidence and registries): Gyawali, Hey & Kesselheim, Assessment of the clinical benefit of cancer drugs receiving accelerated approval (JAMA Intern Med 2019): https://doi.org/10.1001/jamainternmed.2019.0462

## Connected records

- ideas: [Send the code to the data: a federated analytics network of cancer centres](https://onco.cc/ideas/idea-data-federated-analytics-network/)
- fronts: [AI & Computation](https://onco.cc/fronts/ai-computation/)
- terms: [ADC sequencing](https://onco.cc/terms/adc-sequencing/), [Real-world evidence](https://onco.cc/terms/real-world-evidence/)
- bottlenecks: [Knowledge reaches practice too slowly](https://onco.cc/bottlenecks/b-knowledge-diffusion/), [Too many combinations to test](https://onco.cc/bottlenecks/b-combination-space/), [Weak real-world evidence and registries](https://onco.cc/bottlenecks/b-real-world-evidence/)
- key papers: [Assessment of the Clinical Benefit of Cancer Drugs Receiving Accelerated Approval](https://onco.cc/key-papers/paper-gyawali-jama-intern-med/)

---
JSON: https://onco.cc/api/v1/entities/idea-data-sequencing-analysis-per-approval.json