%0 Journal Article %1 Jenkins2011 %A Jenkins, Martin %A Flynn, Aiden %A Smart, Trevor %A Harbron, Chris %A Sabin, Tony %A Ratnayake, Jayantha %A Delmar, Paul %A Herath, Athula %A Jarvis, Philip %A Matcham, James %D 2011 %J Pharmaceutical statistics %K BiologicalMarkers BiologicalMarkers:analysis DrugDiscovery DrugDiscovery:statistics&numericaldata Humans IndividualizedMedicine IndividualizedMedicine:methods IndividualizedMedicine:statistics&numericalda ResearchDesign ResearchDesign:statistics&numericaldata ToxicityTests ToxicityTests:statistics&numericaldata %N 6 %P 494-507 %R 10.1002/pst.532 %T A statistician's perspective on biomarkers in drug development. %U http://dx.doi.org/10.1002/pst.532 http://www.ncbi.nlm.nih.gov/pubmed/22162336 %V 10 %X Biomarkers play an increasingly important role in many aspects of pharmaceutical discovery and development, including personalized medicine and the assessment of safety data, with heavy reliance being placed on their delivery. Statisticians have a fundamental role to play in ensuring that biomarkers and the data they generate are used appropriately and to address relevant objectives such as the estimation of biological effects or the forecast of outcomes so that claims of predictivity or surrogacy are only made based upon sound scientific arguments. This includes ensuring that studies are designed to answer specific and pertinent questions, that the analyses performed account for all levels and sources of variability and that the conclusions drawn are robust in the presence of multiplicity and confounding factors, especially as many biomarkers are multidimensional or may be an indirect measure of the clinical outcome. In all of these areas, as in any area of drug development, statistical best practice incorporating both scientific rigor and a practical understanding of the situation should be followed. This article is intended as an introduction for statisticians embarking upon biomarker-based work and discusses these issues from a practising statistician's perspective with reference to examples. %@ 1539-1612

@article{Jenkins2011, abstract = {Biomarkers play an increasingly important role in many aspects of pharmaceutical discovery and development, including personalized medicine and the assessment of safety data, with heavy reliance being placed on their delivery. Statisticians have a fundamental role to play in ensuring that biomarkers and the data they generate are used appropriately and to address relevant objectives such as the estimation of biological effects or the forecast of outcomes so that claims of predictivity or surrogacy are only made based upon sound scientific arguments. This includes ensuring that studies are designed to answer specific and pertinent questions, that the analyses performed account for all levels and sources of variability and that the conclusions drawn are robust in the presence of multiplicity and confounding factors, especially as many biomarkers are multidimensional or may be an indirect measure of the clinical outcome. In all of these areas, as in any area of drug development, statistical best practice incorporating both scientific rigor and a practical understanding of the situation should be followed. This article is intended as an introduction for statisticians embarking upon biomarker-based work and discusses these issues from a practising statistician's perspective with reference to examples.}, added-at = {2023-02-03T11:44:35.000+0100}, author = {Jenkins, Martin and Flynn, Aiden and Smart, Trevor and Harbron, Chris and Sabin, Tony and Ratnayake, Jayantha and Delmar, Paul and Herath, Athula and Jarvis, Philip and Matcham, James}, biburl = {https://www.bibsonomy.org/bibtex/2d6db792285e93fd4ddf42a26c711aa20/jepcastel}, doi = {10.1002/pst.532}, interhash = {9778ca3636d5fe74e0247d00f438b7ec}, intrahash = {d6db792285e93fd4ddf42a26c711aa20}, isbn = {1539-1612}, issn = {1539-1612}, journal = {Pharmaceutical statistics}, keywords = {BiologicalMarkers BiologicalMarkers:analysis DrugDiscovery DrugDiscovery:statistics&numericaldata Humans IndividualizedMedicine IndividualizedMedicine:methods IndividualizedMedicine:statistics&numericalda ResearchDesign ResearchDesign:statistics&numericaldata ToxicityTests ToxicityTests:statistics&numericaldata}, note = {6456<m:linebreak></m:linebreak>Mesures de resultats; Surrogate endpoints}, number = 6, pages = {494-507}, pmid = {22162336}, timestamp = {2023-02-03T11:44:35.000+0100}, title = {A statistician's perspective on biomarkers in drug development.}, url = {http://dx.doi.org/10.1002/pst.532 http://www.ncbi.nlm.nih.gov/pubmed/22162336}, volume = 10, year = 2011 }