Open Bench · Unit 3 of 8
Finding a targetIf a disease is a machine, which part do you break?
Students open a real, free drug discovery database used by actual pharmaceutical companies and leave with their own ranked list of candidate targets for eczema, with reasons attached.
Length
60 minutes
Tracks
Explorer (Grades 6–8) · Builder (Grades 9–12)
Cost
Free, permanently
Licence
CC BY 4.0
Objectives
By the end of the hour, a student can do each of these without being prompted.
- 01
Define a drug target in one sentence without using the word target.
- 02
Use the Open Targets Platform to find genes associated with a disease.
- 03
Tell the difference between evidence that a gene is involved and evidence that changing it would help.
- 04
Produce a ranked list and defend the ranking against someone who disagrees.
Run of show
The hour, minute by minute.
Timings are a plan, not a rule. The segment most worth protecting when you run late is noted in the teacher notes below.
- 10 min
Return to your map
Students pull out the Unit 1 drawing. Every step they marked with an X is a candidate target. They already did this; they just did not know the word.
- 15 min
Guided tour of a real database
Open the Open Targets Platform on the board. Search atopic dermatitis together. Show the association scores, then show where the scores come from, which is the part most people skip.
- 20 min
Rank five targets
In pairs, students pick five genes and rank them. The ranking criteria are theirs to choose and must be written down before they rank, not after.
- 10 min
Defend it
Pairs swap lists and attack each other's rankings. The teacher's only job is to keep the attacks about the criteria rather than the people.
- 5 min
Association is not causation, again
Close on the hardest idea in the unit: a gene can be strongly associated with a disease and still be a useless target. Give one concrete example and let it sit.
The activity
Your first ranked target list
- 1
Choose atopic dermatitis or food allergy.
- 2
Write down your ranking criteria before you look at any data.
- 3
Find ten associated genes and keep the five you can say something about.
- 4
Rank them against your own criteria and write one sentence of justification each.
- 5
Only now, compare your ranking to the platform's own prioritisation view, and write a paragraph on every place you disagreed.
What you hand in
A ranked list of five targets with written criteria, justifications, and a disagreement note. This is the first piece of work good enough to show a scientist.
Tools, all free
Free, open source, no account. The same resource real drug hunters use.
Scores targets on clinical precedence, tractability, doability and safety. Students compare their ranking against it afterward, never before.
Explorer track swap
Explorers rank three targets instead of five, using a printed card for each gene with its score and one plain-language fact. The database stays on the teacher's screen.
The misconception to expect
“The gene with the highest association score is the best target.”
The highest score often marks a gene that is essential everywhere in the body, which usually makes it a dangerous thing to block. Being important and being druggable are different properties.
Teaching it
Notes from the room.
How you know it landed
A student has it when they can name a high-scoring gene they deliberately ranked low, and give a reason that is not about the score.
- 01
Insist that criteria are written before ranking. Students who rank first and justify afterward learn the opposite of what this unit teaches.
- 02
The platform occasionally changes its interface. Walk through it yourself the morning of the class rather than trusting last term's screenshots.
- 03
This unit produces the single best artifact for a college application or a science fair in the whole course. Tell students that, and tell them it only counts if the reasoning is theirs.
Reading for this unit
The papers behind the hour.
Optional for Explorers, expected for Builders. Full notes on each one are in the reading room.
- R-15
Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery
Nucleic Acids Research · 2025 · Free full text
A free, open-source knowledge base linking genes to diseases, with a target prioritization view scoring clinical precedence, tractability, doability and safety, and an assessment of whether a variant's effect raises or lowers risk.
- R-16
NCBI GEO: archive for gene expression and epigenomics data sets, 23-year update
Nucleic Acids Research · 2024 · Free full text
A public archive holding over 200,000 studies and 6.5 million samples, now with consistently computed gene expression count matrices for thousands of RNA-seq studies and browser-based differential expression tools.