Evidence map›Paper›PMID 32036574›Full record

ArticlePharmaceutical medicine2020

Automation Opportunities in Pharmacovigilance: An Industry Survey.

Rajesh Ghosh, Dieter Kempf, Angela Pufko, Luisa Fernanda Barrios Martinez, Chris M Davis, Sundeep Sethi

Abstract read
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In one paragraph

Article in Pharmaceutical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

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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

6 authors.

Rajesh GhoshInnovation, Chief Medical Office and Patient Safety, Novartis Pharma New Jersey, 1 Health Plaza, East Hanover, NJ, 07936, USA. rajesh.ghosh@novartis.com.ORCID 0000-0001-8749-4979
Dieter KempfGenentech, A Member of the Roche Group, South San Francisco, CA, USA.
Angela PufkoMerck & Co., Inc., Lebanon, NJ, USA.
Luisa Fernanda Barrios MartinezMerck Sharp & Dohme (MSD), Bogota, Colombia.
Chris M DavisGlobal Patient Safety, Eli Lilly and Company, Indianapolis, IN, USA.
Sundeep SethiSafety Operations, AbbVie Inc, North Chicago, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTransCelerate's Intelligent Automation Opportunities (IAO) in Pharmacovigilance initiative has been working to evaluate various pharmacovigilance processes to facilitate systematic innovation with intelligent automation across the entire area. The individual case safety report (ICSR) process was the first process selected for evaluation because of its resource-intensive nature, risk of errors, and operational inefficiencies.

objectivesTransCelerate's IAO in Pharmacovigilance initiative initially worked to articulate an end-to-end ICSR process that would generically apply to various pharmacovigilance organizations, despite organizational variations in specific ICSR process steps. This paper aims to address the need for a systematic review framework for automation of the ICSR process from the value, impact, perceived risk, and opportunity point of view.

methodsThe generic ICSR process, which starts with receipt of an adverse event report, was grouped into three process blocks: case intake, case processing, and case reporting. Each of these was then further detailed in individual process steps. A total of 19 TransCelerate member companies were invited to complete a survey designed to facilitate understanding of automation opportunities across the ICSR process. Heat maps of the current level of effort, expected benefit of automation, and perceived risk of automation were compiled from responses to identify intelligent automation opportunities for specific ICSR process steps. Relevant experts on the TransCelerate evaluation team analyzed and interpreted the anonymized and aggregated results.

resultsIn total, 15 TransCelerate member companies responded to the survey and indicated that ICSR process steps with current high effort, expected high automation benefit, low or manageable automation risk, and low levels of current automation present the best opportunities for future automation. Such steps include language translations, case verification, in-line quality control, prioritization/triage, data entry, alerts for cases of interest, workflow management, and monitoring. Some steps (e.g., submission) have been automated for a number of years and appear on the heat map as having low potential for further automation. The survey responses implied that, despite successful use of intelligent automation technologies in other areas, adoption within pharmacovigilance and the ICSR process in particular remains limited. The perceived high risk to patient safety is expected to decrease with additional successful applications in pharmacovigilance.

conclusionsOur results highlight the areas of greatest opportunity for intelligent automation based on the potential benefits of applying intelligent automation and the perceived risks associated with each ICSR process step. Responding TransCelerate member companies already automate many steps to varying degrees. However, a significant opportunity remains for automation to penetrate further. Additionally, the pharmacovigilance industry culture needs to change in order to reduce the perceived risk of automation and to encourage a more progressive approach to intelligent automation. Increased automation is crucial to empower agile and efficient pharmacovigilance.

Indexed as

Adverse Drug Reaction Reporting SystemsAutomationDrug-Related Side Effects and Adverse ReactionsHumansPharmacovigilanceTechnology Assessment, Biomedical

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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.