Evidence map›Paper›PMID 31754426›Full record

ArticleF1000Research2019

Precision medicine technology hype or reality? The example of computer-guided dosing.

Thomas M Polasek, Sepehr Shakib, Amin Rostami-Hodjegan

Abstract read
In one paragraph

Article in F1000Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
  2. Virtual twin for healthcare management.Frontiers in digital health · 2023
    Article
  3. 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.

Thomas M PolasekCertara, 100 Overlook Center, Suite 101, Princeton, NJ, 08540, USA.ORCID 0000-0003-1008-5223
Sepehr ShakibDepartment of Clinical Pharmacology, Royal Adelaide Hospital, Adelaide, South Australia, Australia.
Amin Rostami-HodjeganCertara, 100 Overlook Center, Suite 101, Princeton, NJ, 08540, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Novel technologies labelled as 'precision medicine' are targeting all aspects of clinical care. Whilst some technological advances are undeniably exciting, many doctors at the frontline of healthcare view precision medicine as being out of reach for their patients. Computer-guided dosing is a precision medicine technology that predicts drug concentrations and drug responses based on individual patient characteristics. In this opinion piece, the example of computer-guided dosing is used to illustrate eight features of a precision medicine technology less likely to be hyperbole and more likely to improve patient care. Positive features in this regard include: (1) fitting the definition of 'precision medicine'; (2) addressing a major clinical problem that negatively impacts patient care; (3) a track record of high-quality medical science published via peer-reviewed literature; (4) well-defined clinical cases for application; (5) quality evidence of benefits measured by various clinical, patient and health economic endpoints; (6) strong economic drivers; (7) user friendliness, including easy integration into clinical workflow, and (8) recognition of importance by patients and their endorsement for broader clinical use. Barriers raised by critics of the approach are given to balance the view. The value of computer-guided dosing will be decided ultimately by the extent to which it can improve cost-effective patient care.

Indexed as

Delivery of Health CareDrug Therapy, Computer-AssistedPrecision MedicineDose-Response Relationship, DrugHumanscomputer-guided dosingindividualized drug therapymodel-informed precision dosingpersonalized medicineprecision dosingPrecision medicine

Identifiers

PMID31754426
PMCPMC6852323

What OpenQuestion holds

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LicenceCC BY
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.