Evidence map›Paper›PMID 29736688›Full record

ArticleInflammopharmacology2018

Is the pharmaceutical industry's preoccupation with the monotherapy drug model stifling the development of effective new drug therapies?

Ian Edwin Cock

Abstract read
PubMed Publisher
In one paragraph

Article in Inflammopharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.8field-weighted citation impact, top 8% of its field
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

10 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. An assessment of the growth inhibition profiles ofJournal of traditional and complementary medicine · 2021
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  5. Chemical Composition, Antibacterial Activity, and Antibiotic Potentiation ofEvidence-based complementary and alternative medicine : eCAM · 2021
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
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 at 1 institution in 1 country.

Ian Edwin CockEnvironmental Futures Research Institute, Nathan Campus, Griffith University, 170 Kessels Rd, Nathan, QLD, 4111, Australia. I.Cock@griffith.edu.au.
Griffith University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug discovery and development is heavily biased towards the development of monotherapies. Screening, testing, and evaluation of mono-entity drugs are generally much simpler than drug combinations, and are generally easier to get approval from the regulatory authorities for their clinical use. However, monotherapy drugs may not have optimal activity, may have associated toxicities, or may lose activity over time as their target develops resistance. Drug combinations, often developed from existing monotherapies, may have improved efficacy and/or be less toxic. Furthermore, the existing drugs which have lost efficacy due to the development of resistance can often be re-activated by combining them with other chemical entities. Thus, whilst the current climate for drug approval, registration, and clinical use drives the majority of drug development research towards the development of monotherapies, combinations are often a substantial improvement on the original drug. This commentary examines monotherapy and combinational therapy models and discusses the benefits and limitations of each model.

Indexed as

Drug DesignDrug ApprovalDrug DiscoveryDrug IndustryDrug Therapy, CombinationHumansPharmaceutical PreparationsPharmaceutical PreparationsCombinational therapiesComplementary therapiesDrug repurposingNatural productsSynergyTraditional medicine

Identifiers

PMID29736688
OpenAlexW2802771978

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.