# Every resistance mechanism found in a patient must be rebuilt in the laboratory

Source: https://onco.cc/ideas/idea-bio1-reverse-translation-resistance-models/  
OnCo record `idea-bio1-reverse-translation-resistance-models` (Idea). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

When doctors discover how a tumour escaped a drug, that finding usually stops at a paper. Recreating it in a model gives everyone a system to test the next drug against.

## Summary

Clinically observed resistance mechanisms (mutations, bypass activation, lineage switch) are frequently reported but rarely converted into a distributed, isogenic model. A standing reverse-translation facility would engineer each reported mechanism into relevant backgrounds, verify the resistance phenotype, and distribute the lines openly, creating a growing panel that drug developers must test new candidates against.

## Fields

- Kind: Idea
- Last checked: 2026-09-08
- Hypothesis: A public panel of clinically derived resistance models identifies cross-resistance for a substantial fraction of next-generation agents before they enter trials, and correctly anticipates their clinical failure settings.
- Rationale: Next-generation inhibitors are often developed against laboratory-derived resistance that does not match what patients actually develop; a clinically anchored panel aligns discovery with reality.
- Proposed test: Build 50 clinically derived resistance models for three drug classes, profile ten clinical-stage successor agents against them blinded, and compare with subsequent trial results.
- Maturity: speculative
- Actor: research

## Sources

- Bottleneck evidence (Lab models that fail to predict what happens in patients): Wong, Siah & Lo, Estimation of clinical trial success rates (Biostatistics 2019): https://doi.org/10.1093/biostatistics/kxx069

## Connected records

- technologies: [CRISPR functional genomics](https://onco.cc/technologies/crispr-screens/), [Functional (ex vivo) drug testing](https://onco.cc/technologies/functional-drug-testing/)
- terms: [Drug resistance (primary and acquired)](https://onco.cc/terms/resistance/)
- bottlenecks: [Acquired resistance to every therapy](https://onco.cc/bottlenecks/b-resistance/), [Lab models that fail to predict what happens in patients](https://onco.cc/bottlenecks/b-preclinical-models/)
- key papers: [Estimation of clinical trial success rates and related parameters](https://onco.cc/key-papers/paper-wong-biostatistics/)

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