ReviewAAPS pharmSci2000
Pharmacogenomics: the promise of personalized medicine.
Review in AAPS pharmSci, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 2 of them syntheses that pooled 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.
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
48 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Drug-gene interactions and the search for missing heritability: a cross-sectional pharmacogenomics study of the QT interval.The pharmacogenomics journal · 2014Pooled it
- Do economic evaluations of targeted therapy provide support for decision makers?The American journal of managed care · 2011Pooled it
- The critical need to implement pharmacogenomics in public health services: Mexico in the global picture.Frontiers in public health · 2026Article
- Applications of Metabolomics in the Development of Biomedicine and Biotechnology.Advances in experimental medicine and biology · 2026Review
- Most Custom Oral Appliances for Obstructive Sleep Apnea Do Not Meet the Definition of Custom.Bioengineering (Basel, Switzerland) · 2025Review
- Proteogenomic Approaches for Diseasome Studies.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Revolutionizing Personalized Medicine: Synergy with Multi-Omics Data Generation, Main Hurdles, and Future Perspectives.Biomedicines · 2024Review
- Artificial intelligence for cardiovascular disease risk assessment in personalised framework: a scoping review.EClinicalMedicine · 2024Article
- Challenges and opportunities for SERS in the infrared: materials and methods.Nanoscale advances · 2023Review
- Detection of COVID-19-related biomarkers by electrochemical biosensors and potential for diagnosis, prognosis, and prediction of the course of the disease in the context of personalized medicine.Analytical and bioanalytical chemistry · 2023Review
- Experience with comprehensive pharmacogenomic multi-gene panel in clinical practice: a retrospective single-center study.Croatian medical journal · 2022Article
- A treatment recommender clinical decision support system for personalized medicine: method development and proof-of-concept for drug resistant tuberculosis.BMC medical informatics and decision making · 2022Article
- Article
- The prospects of precision psychiatry.Theoretical medicine and bioethics · 2021Article
- Pharmacogenetics of Drug-Resistant Epilepsy (Review of Literature).International journal of molecular sciences · 2021Review
- Practicality of 3D Printed Personalized Medicines in Therapeutics.Frontiers in pharmacology · 2021Review
- Current Concepts in Pharmacometabolomics, Biomarker Discovery, and Precision Medicine.Metabolites · 2020Review
- Implementation of a Renal Precision Medicine Program: Clinician Attitudes and Acceptance.Life (Basel, Switzerland) · 2020Article
- Intellectual Structure and Evolutionary Trends of Precision Medicine Research: Coword Analysis.JMIR medical informatics · 2020Article
- Whole genome sequencing identifies high-impact variants in well-known pharmacogenomic genes.The pharmacogenomics journal · 2019Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pharmacogenetics and pharmacogenomics deal with the genetic basis underlying variable drug response in individual patients. The traditional pharmacogenetic approach relies on studying sequence variations in candidate genes suspected of affecting drug response. On the other hand, pharmacogenomic studies encompass the sum of all genes, i.e., the genome. Numerous genes may play a role in drug response and toxicity, introducing a daunting level of complexity into the search for candidate genes. The high speed and specificity associated with newly emerging genomic technologies enable the search for relevant genes and their variants to include the entire genome. These new technologies have essentially spawned a new discipline, termed pharmacogenomics, which seeks to identify the variant genes affecting the response to drugs in individual patients. Moreover, pharmacogenomic analysis can identify disease susceptibility genes representing potential new drug targets. All of this will lead to novel approaches in drug discovery, an individualized application of drug therapy, and new insights into disease prevention. Current concepts in drug therapy often attempt treatment of large patient populations as groups, irrespective of the potential for individual, genetically-based differences in drug response. In contrast, pharmacogenomics may help focus effective therapy on smaller patient subpopulations which although demonstrating the same disease phenotype are characterized by distinct genetic profiles. Whether and to what extent this individual, genetics-based approach to medicine results in improved, economically feasible therapy remain to be seen. To exploit these opportunities in genetic medicine, novel technologies will be needed, legal and ethical questions must be clarified, health care professionals must be educated, and the public must be informed about the implications of genetic testing in drug therapy and disease management.
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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.