Stratified medicine in European Medicines Agency licensing : a systematic review of predictive biomarkers

K. Malottki, M. Biswas, J. J. Deeks, R. D. Riley, Charles Craddock, P. Johnson, L. Billingham

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16 Citations (Scopus)
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Abstract

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.
Original languageEnglish
Pages (from-to)e004188-e004188
JournalBMJ open
Volume4
Issue number1
DOIs
Publication statusPublished - 27 Jan 2014

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