# Drug discovery roadmap: screening in mice → maps of dependency → designing in silico

Source: https://onco.cc/roadmaps/drug-discovery-roadmap/  
OnCo record `drug-discovery-roadmap` (Roadmap). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

Finding the next cancer drug used to mean testing compounds on mice and cell lines and hoping. It now means mapping which genes each cancer cannot live without, growing a patient's tumour in a dish, and designing molecules on a computer; the job is making those tools predict what happens in people.

## Summary

Nine in ten cancer drugs that work in mice fail in humans, and most of the history of drug discovery is the attempt to close that gap. Natural-product screening found vincristine and paclitaxel; target-based discovery, structural biology and high-throughput screening produced the kinase inhibitors. What they could not do was predict which patients a drug would help or which combination would hold.

The present toolkit attacks that directly. Genome-wide CRISPR screens (DepMap) map the dependencies of a thousand cancer cell lines and expose synthetic-lethal targets; patient-derived organoids and xenografts keep a tumour's biology closer to the patient's; functional testing of drugs on a patient's own cells is being run alongside trials. Structure prediction (AlphaFold 3, Boltz, Chai) and generative design have put the first AI-designed molecules into oncology trials, and perturbation datasets of a hundred million cells are training models that try to predict a drug's effect before the experiment.

The pace is set by the predictive validity of models, by the half of landmark findings that do not reproduce, by the valley between an academic discovery and a funded programme, and by the secrecy that keeps compound libraries and negative results locked up.

## Fields

- Kind: Roadmap
- Last checked: 2026-09-10

## Sources

- DepMap portal: https://depmap.org/portal/
- AlphaFold 3 (Nature 2024): https://doi.org/10.1038/s41586-024-07487-w
- Tahoe-100M single-cell perturbation atlas: https://www.tahoebio.ai/

## Connected records

- collections: [AACR Project GENIE](https://onco.cc/collections/genie/), [Arc Virtual Cell Atlas](https://onco.cc/collections/arc-virtual-cell-atlas/), [Cancer Models (PDCM Finder) & HCMI](https://onco.cc/collections/cancer-models/), [CPTAC (Clinical Proteomic Tumor Analysis Consortium)](https://onco.cc/collections/cptac/), [DepMap (Cancer Dependency Map)](https://onco.cc/collections/depmap/), [Tahoe-100M](https://onco.cc/collections/tahoe-100m/), [TCGA / NCI Genomic Data Commons](https://onco.cc/collections/tcga-gdc/)
- roadmaps: [ADC roadmap: from Mylotarg to bispecific and dual-payload ADCs](https://onco.cc/roadmaps/adc-generations/), [AI in oncology roadmap: pattern readers → foundation models → agents in the workflow](https://onco.cc/roadmaps/ai-oncology-roadmap/), [Virtual cell roadmap: from bulk omics to a predictive model of a cancer cell](https://onco.cc/roadmaps/virtual-cell/)
- ideas: [A guaranteed purchase prize for the first drug against a named hard target](https://onco.cc/ideas/idea-bio1-undruggable-market-commitment/), [A registry for preclinical experiments that did not work](https://onco.cc/ideas/idea-tr2-preclinical-negative-registry/), [A shared compound library that rare cancer researchers can actually use](https://onco.cc/ideas/idea-bio2-shared-compound-access-pool/), [Every cancer biology PhD begins with a funded replication of a published finding](https://onco.cc/ideas/idea-tr2-phd-replication-year/), [Grow each trial patient's tumour as organoids to decide which platform arm opens next](https://onco.cc/ideas/idea-tr2-organoid-coclinical-arms/), [In silico trials to choose the dose before the first patient](https://onco.cc/ideas/idea-bio1-in-silico-trials-dose/), [Linked human organ chips to predict side effects before people are dosed](https://onco.cc/ideas/idea-bio1-multi-organ-chip-tox/), [Shared reference organoid and PDX panels that every lab can test against](https://onco.cc/ideas/idea-tr2-reference-model-panels/)
- fronts: [Drug Discovery Platforms](https://onco.cc/fronts/drug-discovery/)
- technologies: [AI-driven drug & target discovery](https://onco.cc/technologies/ai-drug-design/), [AlphaFold 3](https://onco.cc/technologies/alphafold3/), [BH3 profiling (functional apoptosis testing)](https://onco.cc/technologies/bh3-profiling/), [Boltz-1 / Boltz-2 (MIT, open)](https://onco.cc/technologies/boltz/), [Chai-1 / Chai-2](https://onco.cc/technologies/chai-1/), [Chemistry42 and Pharma.AI (Insilico)](https://onco.cc/technologies/chemistry42/), [CRISPR functional genomics](https://onco.cc/technologies/crispr-screens/), [De novo designed protein binders](https://onco.cc/technologies/de-novo-protein-design/), [Degrader-antibody conjugate (DAC)](https://onco.cc/technologies/degrader-antibody-conjugate/), [Digital twins and virtual control arms](https://onco.cc/technologies/digital-twins-trials/), [ESM3 (EvolutionaryScale)](https://onco.cc/technologies/esm3/), [Functional (ex vivo) drug testing](https://onco.cc/technologies/functional-drug-testing/), [Geneformer](https://onco.cc/technologies/geneformer/), [High-throughput screening and DNA-encoded libraries](https://onco.cc/technologies/high-throughput-screening-libraries/), [Molecular glue discovery platforms](https://onco.cc/technologies/molecular-glue-platforms/), [Oligonucleotide therapeutics](https://onco.cc/technologies/antisense-sirna/), [Organoid-guided therapy at scale](https://onco.cc/technologies/organoid-guided-therapy-scale/), [Patient-derived organoids](https://onco.cc/technologies/organoids/), [Patient-derived xenografts](https://onco.cc/technologies/pdx-models/), [PDAC organoid pharmacotyping](https://onco.cc/technologies/pdac-organoid-pharmacotyping/), [Peptide-drug & small-molecule-drug conjugates](https://onco.cc/technologies/peptide-drug-conjugate/), [Phenom-2 and Recursion OS](https://onco.cc/technologies/phenom-2/), [PROTACs & molecular glues (targeted protein degradation)](https://onco.cc/technologies/protac-degrader/), [Proteomics & phosphoproteomics](https://onco.cc/technologies/proteomics/), [RFdiffusion / RFdiffusion2 and ProteinMPNN (Baker Lab)](https://onco.cc/technologies/rfdiffusion/), [scGPT](https://onco.cc/technologies/scgpt/), [State (Arc Institute perturbation model)](https://onco.cc/technologies/state-arc/), [Structural biology infrastructure (cryo-EM, synchrotrons, AlphaFold)](https://onco.cc/technologies/structural-biology-infrastructure/), [Synthetic lethality approaches](https://onco.cc/technologies/synthetic-lethality-approaches/)
- drugs: [Dactinomycin (actinomycin D)](https://onco.cc/drugs/dactinomycin/), [Imatinib](https://onco.cc/drugs/imatinib/), [Paclitaxel / nab-paclitaxel](https://onco.cc/drugs/paclitaxel/), [Sotorasib](https://onco.cc/drugs/sotorasib/), [Vincristine](https://onco.cc/drugs/vincristine/)
- companies: [Araris Biotech (Taiho)](https://onco.cc/companies/araris/), [Bicycle Therapeutics](https://onco.cc/companies/bicycle-therapeutics/), [Chai Discovery](https://onco.cc/companies/chai-discovery/), [Champions Oncology](https://onco.cc/companies/champions-oncology/), [Curesponse](https://onco.cc/companies/curesponse/), [Exscientia](https://onco.cc/companies/exscientia/), [Frontier Medicines](https://onco.cc/companies/frontier-medicines/), [Generate:Biomedicines](https://onco.cc/companies/generate-biomedicines/), [Google DeepMind (and Google Research)](https://onco.cc/companies/google-deepmind/), [HUB Organoids](https://onco.cc/companies/hub-organoids/), [Insilico Medicine](https://onco.cc/companies/insilico-medicine/), [Isomorphic Labs](https://onco.cc/companies/isomorphic-labs/), [Recursion Pharmaceuticals](https://onco.cc/companies/recursion/), [SEngine Precision Medicine](https://onco.cc/companies/sengine/), [Vevo Therapeutics](https://onco.cc/companies/vevo-therapeutics/), [Xaira Therapeutics](https://onco.cc/companies/xaira-therapeutics/)
- institutions: [Arc Institute](https://onco.cc/institutions/arc-institute/), [National Cancer Institute (NIH)](https://onco.cc/institutions/nci/)
- bottlenecks: [Failures are hidden](https://onco.cc/bottlenecks/b-negative-results/), [Lab models that fail to predict what happens in patients](https://onco.cc/bottlenecks/b-preclinical-models/), [Preclinical results do not reproduce](https://onco.cc/bottlenecks/b-reproducibility/), [Secrecy and intellectual property block collaboration](https://onco.cc/bottlenecks/b-ip-collaboration/), [The undruggable drivers](https://onco.cc/bottlenecks/b-undruggable-targets/), [The valley of death between lab and product](https://onco.cc/bottlenecks/b-translational-valley/)
- key papers: [Accurate structure prediction of biomolecular interactions with AlphaFold 3](https://onco.cc/key-papers/paper-abramson-nature/)

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JSON: https://onco.cc/api/v1/entities/drug-discovery-roadmap.json