Hannah Mamuszka and Lena Chaihorsky take on the drug pricing debate from the patient's side, where the question is not what a drug costs but whether it works for the person taking it. Chaihorsky frames it with a metaphor that runs through the episode: we argue endlessly over the price of milk while ignoring that the whole family is lactose intolerant. Mamuszka tells a story that shaped her career. As a young scientist at a small pharma company, she spent years developing a biomarker for a drug at the FDA's suggestion, only for the agency to drop the requirement and for her CEO, at the launch party, to explain that they would treat every patient the label allowed because there were investors to repay. The drug worked in roughly 38% of patients and caused serious side effects in about 40%, and the biomarker could tell those groups apart. They trace how that logic became structural, including the FDA's early-2000s move toward companion diagnostics for all targeted therapies, which collapsed under industry pushback. Chaihorsky then walks through the economics that decide which drugs patients can get when no biomarker stands in the way: PBM formularies rank-ordered by rebate rather than by mechanism of action, step therapy, and a pharmacy-versus-medical budget split that leaves no one owning the cost of being wrong. Their closing asks are simple. Patients should ask how their doctor knows a drug will work for them. Employers heading into benefits season should ask who their PBM is and what its contract rewards.

Key takeaways

• The price of the drug is only half the conversation, whether it works is the other.
• Response rates are far lower than most people assume. Schork's 2015 Nature analysis found the ten highest-grossing US drugs help between 1 in 25 and 1 in 4 of the people who take them.
• Nothing rewards a higher response rate. A drug's price is the same whether it works in 15% of patients or 80%.
• PBMs are paid on rebates rather than net cost, so formularies are rank-ordered by what pays best rather than by who is likely to respond. Using biomarkers to predict response would break that model, which is a reason to expect resistance rather than a reason it doesn't work.
• Pharmacy and medical spend sit in separate budgets, so a wasted prescription and the hospitalization it causes are never added together, and nobody is accountable for the total.
• The question for patients: how do you know this drug will work for me? The question for employers: who is our PBM, and is our formulary built on rebates or on evidence?

Relevant links

• Schork NJ, "Personalized medicine: Time for one-person trials," Nature 2015;520(7549):609–611 — the source of the "1 in 25 to 1 in 4" figure and the imprecision-medicine graphic Lena describes: https://www.nature.com/articles/520609a
• FTC interim staff report on pharmacy benefit managers (July 2024) — the top three PBMs processed nearly 80% of the ~6.6 billion US prescriptions dispensed in 2023: https://www.ftc.gov/news-events/news/press-releases/2024/07/ftc-releases-interim-staff-report-prescription-drug-middlemen
• Substack, "The Price of Drugs Is Only Half the Problem": https://hannahmamuszka.substack.com/p/the-price-of-drugs-is-only-half-the?r=4n5pb&utm_campaign=post-expanded-share&utm_medium=web