Health-based pharmaceutical pay-for-performance risk-sharing agreements
Bibliographic record
Abstract
Many new drugs, such as biologics and cancer drugs, are very costly. However, their effectiveness outside of clinical trial settings is often uncertain at the time they gain market approval. This uncertainty may reflect a lack of real-world outcomes data, as opposed to clinical trials data, for a typical patient population. A risk-sharing agreement is a contract between a drug manufacturer and a healthcare payer to help manage uncertainties regarding the cost and effectiveness of those drugs. In this paper, we model a risk-sharing agreement in which a proportion of total sales is rebated. We model disease progression using a continuous time Markov chain with uncertain transition rates. We examine the performance of this risk-sharing agreement from the manufacturer’s perspective and investigate the conditions under which the manufacturer will make a profit. We illustrate with a numerical model parameterized using data from a Phase 2 clinical trial of an oncology drug that was subjected to a risk-sharing agreement in the UK.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".