Evidence map›Paper›PMID 15693724›Full record

ReviewPharmacoEconomics2005

Role of pharmacoeconomic analysis in R&D decision making: when, where, how?

Paul Miller

Abstract readReview
PubMed Publisher
In one paragraph

Review in PharmacoEconomics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Supporting translation with early health technology assessment: from definition to action.International journal of technology assessment in health care · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Paul MillerAstraZeneca R&D, Lund, Sweden. Paul.Miller3@astrazeneca.com

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pharmacoeconomics is vitally important to drug manufacturers in terms of communicating to external decision-makers (payers, prescribers, patients) the value of their products, achieving regulatory and reimbursement approval and contributing to commercial success. Since development of new drugs is long, costly and risky, and decisions must be made how to allocate considerable research and development (R&D) resources, pharmacoeconomics also has an essential role informing internal decision-making (within a company) during drug development. The use of pharmacoeconomics in early development phases is likely to enhance the efficiency of R&D resource use and also provide a solid foundation for communicating product value to external decision-makers further downstream, increasing the likelihood of regulatory (reimbursement) approval and commercial success. This paper puts the case for use of pharmacoeconomic analyses earlier in the development process and outlines five techniques (clinical trial simulation [CTS], option pricing [OP], investment appraisal [IA], threshold analysis [TA] and value of information [VOI] analysis) that can provide useful input into the design of clinical development programmes, portfolio management and optimal pricing strategy. CTS can estimate efficacy and tolerability profiles before clinical data are available. OP can show the value of different clinical programme designs, sequencing of studies and stop decisions. IA can compare expected net present value (NPV) of different product profiles or study designs. TA can be used to understand development drug profile requirements given partial data. VOI can assist risk management by quantifying uncertainty and assessing the economic viability of gathering further information on the development drug. No amount of pharmacoeconomic data can make a bad drug good; what it can do is enhance the drug developers understanding of the characteristics of that drug. Decision-making, in light of this information, is likely to be better than that without it, whether it leads to faster termination of uneconomic projects or the allocation of more appropriate resources to attractive projects.

Indexed as

Decision Making, OrganizationalDrug DesignDrug IndustryEconomics, PharmaceuticalHumansModels, EconomicResearch

Identifiers

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.