ArticlePharmacoEconomics2006
Economic and developmental considerations for pharmacogenomic technology.
Article in PharmacoEconomics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Economic evaluation and cost-effectiveness thresholds: signals to firms and implications for R & D investment and innovation.PharmacoEconomics · 2009Article
- The future costs, risks and rewards of drug development: the economics of pharmacogenomics.PharmacoEconomics · 2009Article
- Can the Spanish care system assume the new costs of medications against cancer?Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2008Review
- Letter from the Commissioner's Office at the US FDA.PharmacoEconomics · 2007Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The pharmaceutical industry's core business is the innovation, development and marketing of new drugs. Pharmacogenetic (PG) testing and technology has the potential to increase a drug's value in many ways. A critical issue for the industry is whether products in development should be teamed with genetic tests that could segment the total population into responders and non-responders. In this paper we use a cost-effectiveness framework to model the strategic decision-making considerations by pharmaceutical manufacturers as they relate to drug development and the new technology of PG (the science of using genetic markers to predict drug response). In a simple, static, one-period model we consider three drug development strategies: a drug is exclusively developed and marketed to patients with a particular genetic marker; no distinguishing among patients based on the expression of a genetic marker is made (traditional approach); and a strategy whereby a drug is marketed to patients both with and without the genetic marker but there is price discrimination between the two subpopulations. We developed three main principles: revenues under a strategy targeting only the responder subpopulation will never generate more revenue than that which could have been obtained under a traditional approach; total revenues under a targeted PG strategy will be less than that under a traditional approach but higher than a naive [corrected] view would believe them to be; and a traditional [corrected] approach will earn the same total revenues as a price discrimination strategy, assuming no intermarket arbitrage. While these principles relate to the singular (and quite narrow) consideration of drug revenues, they may nevertheless partially explain why PG is not being used as widely as was predicted several years ago when the technology first became available, especially in terms of pharmaceutical manufacturer-developed tests.
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.