Emilia Javorsky
speaker
1,653 appearances
2 recordings
1 series
first heard Mar 2026
last heard 20 Mar
Emilia Javorsky’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 2 in all, peaking in Mar 2026 with 2.
Appearances
Consequently, new therapies most often meet patients in advanced stages of disease.
When the body is worn down and the cancer is aggressive, medical, regulatory, and financial institutions continue to grapple with financial and ethical frameworks for deploying such therapies earlier than studied in trials.
But given the life-or-death stakes and high costs, there are few clear answers.
These dynamics help to explain why we have so few treatments for the prevention and early treatment of some of the most pressing unsolved diseases.
The clinical trials are long and often require a large study population to detect a significant effect.
Together, these factors equate to prohibitive development costs.
Let's look at the data.
On the average amount of time in years it takes to detect a primary clinical outcome in Phase 3 trials, broken down into different treatment areas such as cancer prevention, Alzheimer's prevention, kidney disease, stroke prevention, diabetes, and more.
The data shows that cancer prevention demands 5 to 10 years of follow-up, watching for cancer incidence in asymptomatic populations.
Alzheimer's prevention requires four to five years tracking cognitive decline.
Early-stage cancer treatment requires three to five years for disease-free survival.
But most notably, late-stage cancer treatment requires just 1.5 to 2.5 years to measure overall or progression-free survival.
The contrast is brutal.
Preventing a disease takes years of patient follow-up.
Treating the same disease after it has metastasized takes months.
This key difference, combined with patient clocks that tick regardless of trial length,
creates an institutional structure that starves treatments focused on prevention and early intervention of resources, and instead channels innovation toward end-stage interventions, where trials can be completed before patients expire.
Now, when we compare the average number of participants per Phase III trial, broken down by the same treatment areas, we see the same stark institutional bias embedded in clinical trial design.
Cancer prevention requires the largest trials by far, 30,000 participants on average, while early-stage cancer treatment requires only 3,000.
Late-stage cancer treatment needs just 600 participants.
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