Evidence map›Paper›PMID 37682462›Full record

ArticleTherapeutic innovation & regulatory science2023

Planning Benefit-Risk Assessments Using Visualizations.

Michael W Colopy, Lovemore Gakava, Chen Chen

Abstract read
PubMed Publisher
In one paragraph

Article in Therapeutic innovation & regulatory science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Michael W ColopyStatistical Sciences & Innovation, UCB Biosciences, Inc, 4000 Paramount Parkway Suite 200, Morrisville, NC, 27560, USA. michael.colopy@ucb.com.ORCID http://orcid.org/0000-0002-1806-8818
Lovemore GakavaStatistical Sciences & Innovation, UCB Celltech, UCB Pharma S.A, Slough, UK.
Chen ChenStatistical Sciences & Innovation, UCB Pharma S.A, Brussels, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A Benefit Risk Assessment Plan (BRAP) describes the assessments planned to determine whether the benefits of an investigational drug outweigh the risks. The plan can have two sections, one with timelines for aligning resources with decision milestones and the other for pre-specifying assessments for decision milestones. Regulatory guidance recommends a proactive planning process over an ad-hoc process. However, very little has been published about proactive plans themselves. This article works through a hypothetical example visualizing a series of assessments across the drug development lifecycle. Based on a regulatory framework, the planning process starts with assessing the medical condition and current treatment options. These early assessments bring out major considerations in assessing the investigational drug.

Indexed as

Drug DevelopmentDrugs, InvestigationalHumansRisk AssessmentDrugs, InvestigationalDecision-makingMCDAPlanningTradeoffUncertainty

Identifiers

PMID37682462

What OpenQuestion holds

Textmetadata
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.