Which drugs target my gene?
It is the first question you ask about any hit — a gene from a screen, a differentially expressed surface protein, a candidate from your own data. Is there already a drug against it? What does that drug treat? How far did it get? BioTransfer's Drug Target Explorer answers that in one search, for a single gene or a whole gene set, and now shows CAR-T and cell-therapy trials alongside conventional drugs. It also works in reverse: give it a disease or a signalling pathway and it returns the druggable genes underneath.
Why "associated diseases" was the wrong answer
The original gene view showed what Open Targets is best known for: evidence-ranked target–disease associations. Search MYCN and you got Feingold syndrome, score 0.82. Technically correct, computationally impressive, and almost never what a bench scientist wanted. Nobody working on MYCN in neuroblastoma is asking which rare syndrome it associates with. They are asking whether it can be drugged.
So the view was rebuilt around that question. Search MYCN today and the answer is blunt and useful: no drug or clinical candidate targets MYCN. Tractability evidence exists for small-molecule and PROTAC approaches, but nothing has reached the clinic. That is the real state of a famously hard target, delivered in one line.
Four ways to explore
1 · By gene → every drug acting on it
Enter a gene and you get each drug and clinical candidate that acts on it, with its mechanism of action, the diseases it is approved or trialled for, and its highest clinical stage. Approved drugs come first. Search ALK and you get twelve drugs, seven of them approved — alectinib, brigatinib, crizotinib and lorlatinib against non-small cell lung carcinoma, with ensartinib in Phase 3 and earlier candidates behind them.
The view is often most interesting for genes you did not expect to be druggable. CACNA2D3, a calcium-channel subunit studied in neuroblastoma, returns ten drugs and seven approvals — gabapentin, pregabalin and bepridil, licensed for epilepsy, neuropathic pain and angina. That is a repurposing lead you would not find by looking for cancer drugs.
2 · By gene set → triage a whole hit list
Paste up to 25 gene symbols — comma, space or newline separated — and each gets its own drug table. Genes carrying an approved drug are sorted to the top, so a screen hit list or a differential-expression shortlist effectively ranks itself by how actionable it is. Genes with nothing in the clinic fall to the bottom with an explicit statement of why.
3 · By disease → ranked target genes, each with its drugs
Search a disease and you get its top target genes ranked by association score, each paired with the pipeline drugs that act on it. Search neuroblastoma and ALK tops the list, sitting next to lorlatinib, ceritinib and crizotinib — the real ALK inhibitors used in ALK-driven disease. No guessing which drug hits which gene; the link is explicit.
4 · By pathway → its druggable nodes & their drugs
Pick a signalling pathway and the tool shows its key druggable nodes, each with the drugs targeting it, approved first. Open RTK → RAS–RAF–MEK–ERK and you get 25 druggable nodes carrying nearly 300 distinct drugs — EGFR with afatinib and cetuximab, KRAS with sotorasib and adagrasib, BRAF with its inhibitors — the pathway's whole druggable surface on one screen.
New: CAR-T and cell-therapy trials
Conventional drug records miss an entire modality. Open Targets is keyed on drug–target pairs, so an antigen with no small molecule or antibody reads as "undrugged" even while CAR-T trials run against it — and GD2, the leading neuroblastoma CAR-T target, is a glycolipid with no gene at all, so it cannot appear in a gene-indexed database by construction.
Every gene now carries a CAR-T & cell therapy section drawn live from ClinicalTrials.gov, with each trial's phase, recruitment status, condition and a direct NCT link. Search GPC2 — nearly empty in conventional drug data — and two active CAR-T trials appear, in relapsed neuroblastoma and medulloblastoma. Because trials name the antigen rather than the gene, the tool maps symbols to antigen names automatically (CD276 → B7-H3, TNFRSF17 → BCMA, B4GALNT1 → GD2).
Read the full write-up on finding CAR-T targets and trials by gene →
What different genes actually return
| Gene | What you get | Why it is useful |
|---|---|---|
| EGFR | 82 drugs, 28 approved | A mature target — the question is which drug, not whether |
| ALK | 12 drugs, 7 approved | Validated in the clinic; competitor landscape at a glance |
| CACNA2D3 | 10 drugs, 7 approved (gabapentin, pregabalin) | Repurposing lead from outside oncology |
| TP53 | 9 candidates, 0 approved (Phase 3 max) | Heavily pursued, still unvalidated — a warning sign |
| GPC2 | ~0 conventional drugs, 2 active CAR-T trials | Would look dead without the cell-therapy view |
| MYCN | 0 drugs, tractability only | Honest negative — do not spend a year rediscovering it |
How it works
Everything comes live from two free public APIs — the Open Targets GraphQL API for drugs and targets, and the ClinicalTrials.gov API for cell-therapy trials. No API key, no login, no stored copy of the data. A gene set of 25 resolves in two batched Open Targets calls, and CAR-T trials load per gene on demand so a long list never fires 25 trial requests at once. Every gene, drug, disease and trial links back to its source record.
Honest about the limits
- Scores are computational. Association scores aggregate evidence (genetics, somatic mutations, known drugs, pathways, expression, literature). They are for target prioritisation and discovery, not clinical or prescribing advice.
- Clinical stage is "any indication." A drug marked Approved is approved for something — not necessarily for the disease you care about. Use the indication column, and disease mode when you need a disease-specific pipeline.
- Pathways use curated nodes. Each pathway is a hand-picked set of its key druggable nodes, not the full Reactome membership — kept focused so a pathway resolves in two fast calls.
- Trial matching is text-based. Short gene symbols can over-match, so the tool requires the antigen in a trial's title or intervention name; trials that name only a product code cannot be attributed automatically. Treat trial counts as a well-filtered starting point, not a complete registry.
No login. A gene, a gene set, a disease or a pathway — every drug acting on it, what it treats, how far it got, and any CAR-T trials against it.
Open the tool →Frequently asked questions
How do I find out which drugs target a specific gene?
Enter the gene symbol in the Drug Target Explorer. It returns every drug and clinical candidate acting on that gene, each with its mechanism of action, the diseases it is approved or trialled for, and its highest clinical stage, with approved drugs listed first. It also shows any CAR-T or cell-therapy trial targeting the gene.
Can I check druggability for a whole list of genes at once?
Yes — paste up to 25 symbols separated by commas, spaces or newlines. Each gene gets its own drug table, and genes carrying an approved drug sort to the top, so a hit list orders itself by how actionable it is.
Is MYCN druggable?
No drug or clinical candidate currently targets MYCN. Tractability evidence exists for small-molecule and PROTAC approaches, but nothing has reached the clinic. As an intracellular transcription factor it is also ruled out for CAR-T, which recognises cell-surface antigens only.
What does the clinical stage mean?
It is the highest point that drug reached in development for any indication — Approved for a marketed drug, or Phase 1 to Phase 4 for one still in trials. It tells you how far the target has been validated in humans, which is often more informative than an association score.
Is it free? Do I need a login or an API key?
Free, no login, no key. It queries the public Open Targets and ClinicalTrials.gov APIs live, stores nothing, and links every result back to its original record.
Related tools
- Finding CAR-T targets and trials by gene — why gene databases miss GD2 and GPC2, and how to search around it.
- GEO Dataset Finder — expression datasets to check where your candidate is actually expressed.
- Neuroblastoma Surface Targets — surfaceome atlas for immunotherapy target discovery.
- qPCR Primer Designer — validate that expression at the bench.