Open Bench · Unit 2 of 8
Why medicine costs so muchWhy does one new drug cost more than a stadium?
Students build the drug discovery funnel out of real published attrition numbers and discover for themselves that the price is mostly paid for the failures, not the success.
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
Name the stages a drug passes through from idea to pharmacy shelf.
- 02
Explain why the cost of one approved drug includes the cost of the ones that failed.
- 03
Calculate what fraction of candidates survive each stage, from published figures.
- 04
Identify the two stages where money is lost fastest, and say why that is where computation helps most.
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
Guess the number
Ask what it costs to bring one new drug to approval. Write every guess down. Reveal the published estimate. The gap between their guesses and the real figure buys you the rest of the hour.
- 15 min
Build the funnel
Walk the stages: target, hit, lead, preclinical, three phases of trials, review. Students build it as a spreadsheet, not a slide, because they will do arithmetic on it in ten minutes.
- 20 min
Do the arithmetic
Fill in published survival rates per stage. Multiply through. Students find the compounding themselves. Someone always says the number must be wrong, which is the right instinct and the right moment to check the source together.
- 10 min
Where would you spend a dollar
Given the funnel they just built, each student picks the single stage where one extra dollar does the most good. Defend it. There is no single correct answer and they should leave knowing that.
- 5 min
The foundation's bet
Show them where WPPF spends: the earliest stage, before money is committed to the wrong target. Let them tell you whether they think that is smart.
The activity
The attrition funnel
- 1
Make a spreadsheet with one row per stage of drug development.
- 2
Fill in a published survival rate for each stage and cite where you got it.
- 3
Multiply the rates to find how many starting candidates you need for one approval.
- 4
Change one rate by ten percent and record how much the final answer moves.
What you hand in
A one-page funnel with every number sourced, plus one sentence on which stage your model is most sensitive to.
Tools, all free
Free. The funnel is a spreadsheet so students can change an assumption and watch the answer move.
Free public registry. Used here only to see how many trials are running right now for one condition.
Explorer track swap
Explorers build the funnel physically with a hundred paper slips, discarding the failures stage by stage. Ten minutes longer and far more memorable than a spreadsheet.
The misconception to expect
“Drugs are expensive because companies are greedy.”
Greed is real and is not the whole mechanism. Most of the cost is the failures, and anything that fails cheaper and sooner lowers the price of everything that succeeds. Students should be able to hold both ideas at once.
Teaching it
Notes from the room.
How you know it landed
A student has it when they can explain, without notes, why a ninety percent success rate at every one of eight stages still means most programs fail.
- 01
The headline cost figure is contested in the literature. Say so. A student who learns that a famous number has critics has learned something more durable than the number.
- 02
Resist moralizing about pharmaceutical companies. The arithmetic is more persuasive than the sermon, and students who feel lectured stop arguing, which is the opposite of what you want.
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.
Generative models screened over ten million chemical fragments in silico and proposed new antibacterial compounds. Of 24 compounds synthesized, seven were selectively antibacterial and two cleared multidrug-resistant infections in mice.