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Stratified medicine in European Medicines Agency licensing: a systematic review of predictive biomarkers
OBJECTIVES: Stratified medicine is often heralded as the future of clinical practice. Key part of stratified medicine is the use of predictive biomarkers, which identify patient subgroups most likely to benefit (or least likely to experience harm) from an intervention. We investigated how many and w...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3913033/ https://www.ncbi.nlm.nih.gov/pubmed/24468721 http://dx.doi.org/10.1136/bmjopen-2013-004188 |
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author | Malottki, Kinga Biswas, Mousumi Deeks, Jonathan J Riley, Richard D Craddock, Charles Johnson, Philip Billingham, Lucinda |
author_facet | Malottki, Kinga Biswas, Mousumi Deeks, Jonathan J Riley, Richard D Craddock, Charles Johnson, Philip Billingham, Lucinda |
author_sort | Malottki, Kinga |
collection | PubMed |
description | OBJECTIVES: Stratified medicine is often heralded as the future of clinical practice. Key part of stratified medicine is the use of predictive biomarkers, which identify patient subgroups most likely to benefit (or least likely to experience harm) from an intervention. We investigated how many and what predictive biomarkers are currently included in European Medicines Agency (EMA) licensing. SETTING: EMA licensing. PARTICIPANTS: Indications and contraindications of all drugs considered by the EMA and published in 883 European Public Assessment Reports and Pending Decisions. PRIMARY AND SECONDARY OUTCOME MEASURES: Data were collected on: the type of the biomarker, whether it selected a subgroup of patients based on efficacy or toxicity, therapeutic area, marketing status, date of licensing decision, date of inclusion of the biomarker in the indication or contraindication and on orphan designation. RESULTS: 49 biomarker–indication–drug (B-I-D) combinations were identified over 16 years, which included 37 biomarkers and 41 different drugs. All identified biomarkers were molecular. Six drugs (relating to 10 B-I-D combinations) had an orphan designation at the time of licensing. The identified B-I-D combinations were mainly used in cancer and HIV treatment, and also in hepatitis C and three other indications (cystic fibrosis, hyperlipoproteinaemia type I and methemoglobinaemia). In 45 B-I-D combinations, biomarkers were used as predictive of drug efficacy and in four of drug toxicity. It appeared that there was an increase in the number of B-I-D combinations introduced each year; however, the numbers were too small to identify any trends. CONCLUSIONS: Given the large body of literature documenting research into potential predictive biomarkers and extensive investment into stratified medicine, we identified relatively few predictive biomarkers included in licensing. These were also limited to a small number of clinical areas. This might suggest a need for improvement in methods of translation from laboratory findings to clinical practice. |
format | Online Article Text |
id | pubmed-3913033 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-39130332014-02-04 Stratified medicine in European Medicines Agency licensing: a systematic review of predictive biomarkers Malottki, Kinga Biswas, Mousumi Deeks, Jonathan J Riley, Richard D Craddock, Charles Johnson, Philip Billingham, Lucinda BMJ Open Pharmacology and Therapeutics OBJECTIVES: Stratified medicine is often heralded as the future of clinical practice. Key part of stratified medicine is the use of predictive biomarkers, which identify patient subgroups most likely to benefit (or least likely to experience harm) from an intervention. We investigated how many and what predictive biomarkers are currently included in European Medicines Agency (EMA) licensing. SETTING: EMA licensing. PARTICIPANTS: Indications and contraindications of all drugs considered by the EMA and published in 883 European Public Assessment Reports and Pending Decisions. PRIMARY AND SECONDARY OUTCOME MEASURES: Data were collected on: the type of the biomarker, whether it selected a subgroup of patients based on efficacy or toxicity, therapeutic area, marketing status, date of licensing decision, date of inclusion of the biomarker in the indication or contraindication and on orphan designation. RESULTS: 49 biomarker–indication–drug (B-I-D) combinations were identified over 16 years, which included 37 biomarkers and 41 different drugs. All identified biomarkers were molecular. Six drugs (relating to 10 B-I-D combinations) had an orphan designation at the time of licensing. The identified B-I-D combinations were mainly used in cancer and HIV treatment, and also in hepatitis C and three other indications (cystic fibrosis, hyperlipoproteinaemia type I and methemoglobinaemia). In 45 B-I-D combinations, biomarkers were used as predictive of drug efficacy and in four of drug toxicity. It appeared that there was an increase in the number of B-I-D combinations introduced each year; however, the numbers were too small to identify any trends. CONCLUSIONS: Given the large body of literature documenting research into potential predictive biomarkers and extensive investment into stratified medicine, we identified relatively few predictive biomarkers included in licensing. These were also limited to a small number of clinical areas. This might suggest a need for improvement in methods of translation from laboratory findings to clinical practice. BMJ Publishing Group 2014-01-25 /pmc/articles/PMC3913033/ /pubmed/24468721 http://dx.doi.org/10.1136/bmjopen-2013-004188 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 3.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/3.0/ |
spellingShingle | Pharmacology and Therapeutics Malottki, Kinga Biswas, Mousumi Deeks, Jonathan J Riley, Richard D Craddock, Charles Johnson, Philip Billingham, Lucinda Stratified medicine in European Medicines Agency licensing: a systematic review of predictive biomarkers |
title | Stratified medicine in European Medicines Agency licensing: a systematic review of predictive biomarkers |
title_full | Stratified medicine in European Medicines Agency licensing: a systematic review of predictive biomarkers |
title_fullStr | Stratified medicine in European Medicines Agency licensing: a systematic review of predictive biomarkers |
title_full_unstemmed | Stratified medicine in European Medicines Agency licensing: a systematic review of predictive biomarkers |
title_short | Stratified medicine in European Medicines Agency licensing: a systematic review of predictive biomarkers |
title_sort | stratified medicine in european medicines agency licensing: a systematic review of predictive biomarkers |
topic | Pharmacology and Therapeutics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3913033/ https://www.ncbi.nlm.nih.gov/pubmed/24468721 http://dx.doi.org/10.1136/bmjopen-2013-004188 |
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