1. There appear to be lots of competing biosimilars in insulin.
1. There appear to be lots of competing biosimilars in insulin.
4. Develop “diagnostic tests” that will allow effects of policy to be forecast partway through implementation.
4. Develop “diagnostic tests” that will allow effects of policy to be forecast partway through implementation.
1. Something such as measures of phase 1 trials and phase 2 trials to predict phase 3 & approval rates.
1. Something such as measures of phase 1 trials and phase 2 trials to predict phase 3 & approval rates.
Possible Hypotheses
## Possible Hypotheses
Do Probabilities of Success differ significantly when estimated on normalized or denormalized paths?
Do Probabilities of Success differ significantly when estimated on normalized or denormalized paths?
• With the FDA data, this will be uniquely answerable. Not sure though what those implications of interest are though.
• With the FDA data, this will be uniquely answerable. Not sure though what those implications of interest are though.
• The value proposition here is that it might “measure” the risk reducing effect of that extra knowledge from previous studies, evidence, etc. I wonder if this could act as an instrument on the effect of unknown risk when starting a new compound?
• The value proposition here is that it might “measure” the risk reducing effect of that extra knowledge from previous studies, evidence, etc. I wonder if this could act as an instrument on the effect of unknown risk when starting a new compound?
◦ The underlying assumption is that the path depends heavily on whether the compound has been studied previously or not. That may not be true.
◦ The underlying assumption is that the path depends heavily on whether the compound has been studied previously or not. That may not be true.
@ -57,6 +60,7 @@ Do Probabilities of Success depend on reimbursment rate?
• Requires some sort of reimbursement/pricing data. Not necessarily available, and would require a natural experiment.
• Requires some sort of reimbursement/pricing data. Not necessarily available, and would require a natural experiment.
Intermediate goals
Intermediate goals
1. Find literature that describes each difficult section of the R&D to successful launch process, focusing on the second section.
1. Find literature that describes each difficult section of the R&D to successful launch process, focusing on the second section.
Policy questions/ topics
Policy questions/ topics
@ -65,14 +69,15 @@ Precision medicines & trials
Insurers paying for participants in a clinical trial. Medicare pays for many, but what effect does this have on recruitment? Possible variation across drugs (legislatively), as identification.
Insurers paying for participants in a clinical trial. Medicare pays for many, but what effect does this have on recruitment? Possible variation across drugs (legislatively), as identification.
• Endpoint doesn’t matter for recruiting
- Endpoint doesn’t matter for recruiting
• Our data may show the “rate” at which people join trials.
- Our data may show the “rate” at which people join trials.
◦ Does medicare coverage for the trial speed that up?
- Does medicare coverage for the trial speed that up?
Use of surragate endpoints. Risk sharing between insurer and developer.
Use of surragate endpoints. Risk sharing between insurer and developer.
• Cancer: survival rates vs what happened to the cancer
• Reduces length of trial, but requires phase 4 trials
- Cancer: survival rates vs what happened to the cancer
• Effects on recruiting/timing
- Reduces length of trial, but requires phase 4 trials
Will King
4 years ago