ReviewBritish journal of clinical pharmacology2002
Maximizing the value of medicines by including pharmacogenetic research in drug development and surveillance.
Review in British journal of clinical pharmacology, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 26 citations in OpenAlex.
- Clinical pharmacology: special safety considerations in drug development and pharmacovigilance.Drug safety · 2004Review
- Linking pharmacovigilance with pharmacogenetics.Drug safety · 2004Article
- Evidence-based medicine, heterogeneity of treatment effects, and the trouble with averages.The Milbank quarterly · 2004Article
- Genotyping of drug targets: a method to predict adverse drug reactions?Drug safety · 2002Review
- Pharmacovigilance in a genomic era.The pharmacogenomics journalArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genetics provides significant opportunities to maximize the safety and efficacy of medicines. Over the next 3--5 years, it may be possible to develop tools that use selective information from patients' DNA to enable healthcare professionals to predict more accurately those patients at risk of serious adverse events to some medicines currently available. This is likely to be followed, over the next 5--10 years, by the application of the technology to predict more accurately if individual patients will obtain a therapeutic benefit from a particular medicine. The ability to accurately predict patient response will inevitably change the way medicines are developed, evaluated, and prescribed. Advances in single nucleotide polymorphism (SNP) map technology are likely to drive this innovation. Abbreviated SNP profiles will provide the means to define medicine response tests, thereby allowing clinicians to select the medicine to which the patient is likely to gain the greatest benefit and least risk. This will help to maximize efficacy and reduce the incidence of drug-related adverse events. It may be possible to identify SNP profiles during larger Phase II clinical trials which predict efficacy, and use these to form the basis of Phase III entry criteria. As a result, Phase III trials may be streamlined for many medicines making them smaller, more efficient, and more focused. In addition it may be possible to incorporate pharmacogenetics into postmarketing surveillance strategies to provide a means to identify SNPs which predict uncommon serious adverse drug reactions, and so refine the initial medicine response test. The ability to develop drugs with a predictable response will allow clinicians to provide targeted treatment for patients, with greater confidence of safety and efficacy. Patients therefore will receive more efficacious, timely, and well-tolerated medicines. The challenge for those involved in drug development is to model and evaluate the application of pharmacogenetics so that steps can be taken to realize this potential.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.