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RETRACTED ARTICLE

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Pharmacoepidemiol Drug Saf. 2007 Jul;16 Suppl 1:S16-41.

A quantitative approach to benefit-risk assessment of medicines - part 2: the practical application of a new model.

Author information

1
Regulatory Affairs Europe, Merck Sharp & Dohme (Europe) Inc, 5 Lynx Binnenhof, Brussels, B-1200, Belgium.

Erratum in

  • Pharmacoepidemiol Drug Saf. 2007 Aug;16(8):946. Phillips, Lawrence [added].

Abstract

PURPOSE:

Decisions leading to drug approval demand careful attention with respect to balancing benefits and risks. The new benefit-risk assessment model provides reassembling of the pieces of decision-making information using computer software to present a coherent overall picture for decision-makers. The aims of the study were to evaluate content validity of the new model and examine its practical application.

METHODS:

The expert panel (Annex 1) drawn from regulatory agencies in USA and Europe, academia and pharmaceutical industry, were encouraged to frank and open discussions about the way in which important, far-reaching decisions are taken within both companies and regulatory agencies and the potential shortcomings of such processes. The main component of the meeting was an interactive demonstration of the application of the technical model MCDA. The model was discussed using a hypothetical scenario based on safety and efficacy data relating to an atypical antipsychotic agent that was clinically tested against placebo and a comparator compound.

RESULTS:

The expert panel unanimously agreed that the methodology had great potential and it was recommended that it should be explored further as an adjunct to the decision-making process for both companies and regulatory agencies. An important part of this would be to undertake retrospective testing using actual case studies.

CONCLUSIONS:

The outcome of the workshop underpins practical utility of the new benefit-risk assessment MCDA model and provides evidence of its content validity. It is hoped that this encourages acceptability by regulatory agencies and the industry for its use in real scenarios.

PMID:
17546574
DOI:
10.1002/pds.1434
[Indexed for MEDLINE]

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