Personal medicine—The new banking crisis

Center for Biomedical Ethics, Stanford, California, USA.
Nature Biotechnology (Impact Factor: 41.51). 05/2012; 30(2):141-7. DOI: 10.1038/nbt.2116
Source: PubMed


As the healthcare industry moves from a twentieth century approach of providing treatments of last resort to a future of individualized medicine, biobanks will play a pivotal role in this transition. Yet at the cutting edge of biobanking research are new ethical, social and policy challenges beyond those familiar to basic biomedical research.

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Available from: Christopher Thomas Scott
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    • "See Hayden (2014). 11 Kohane (2011), Jensen et al. (2012), Scott et al. (2012) and Guarda (2013). 12 Rosenthal et al. (2010) and Stein (2010). "

    Full-text · Article · Dec 2015
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    • "Kaiser's Research Program on Genes, Environment and Health (RPGEH) attempts to triage genetic, environmental and medical information, to allow for better interpretation of health outcomes and has also resulted in the largest DNA biobank in the US. Similarly, Genethon (Paris) is one of Europe's largest cell and tissue repositories (Scott et al., 2012). Important biobanking projects in Asia include NUS-NUH Tissue Repository, SingHealth Tissue Repository , Singapore, UMCRI Tumour Tissue Bank, Cryocord Premiere stem cell bank, Malaysia, RIKSEN Bioresource center cell bank, Japan; "
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    ABSTRACT: While the potential for the application of pharmacogenomics and theranostics to develop personalized healthcare solutions is enormous, multiple challenges will need to be addressed to get there. Understanding the complex interactions and detailed characterization of the functional variants of individual ADME (Absorption Distribution Metabolism Excretion) genes and drug target genes is needed to demonstrate clinical utility, using both a bottoms-up as well as a top–down approach. Clinical trials need to be designed appropriately so as to identify not only individual but also population variations. The impact of non-genetic and environmental factors, epigenetic variations and circadian rhythms on an individual's response need to be assessed to make pharmacogenomics clinically indicated. More advanced algorithms and appropriate study designs need to be developed to allow this pipeline to grow and to be used effectively in the clinical setting. Another challenge lies in the value proposition to the pharmaceutical industry. Fearing the impact of the slice and dice approach on revenues, companies are going slow on developing pharmacogenomic solutions; yet many are hedging their bets, amassing huge amounts of single nucleotide polymorphisms (SNP) data. They are being used as predictors of drug efficacy and safety to zero in on subpopulations that are at risk for either a bad response or no response in clinical trials, supporting the Fail fast, Fail cheap approach. In addition, the growth of theranostics is impeded by the fear that the approval of both the diagnostic and the drug would get delayed. Education of the health care provider, payor, regulator and the patient is also required and an exercise of change management needs to occur. Countries such as India should exploit the joint benefit of the reduced cost of tests today, complemented by a large and a highly genetically diverse population.
    Full-text · Article · Dec 2013 · Applied and Translational Genomics
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    • "The Cancer Genome Atlas Project (an NCI initiative) assessed the quality of samples acquired from dozens of tissue banks and produced the surprising result that only one percent of the samples assessed were viable. In addition, most of the tissue banks that supplied these samples had no proper catalog of samples that were stored in their facilities [55, 56]. "
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    ABSTRACT: Personalized medicine promises patient-tailored treatments that enhance patient care and decrease overall treatment costs by focusing on genetics and "-omics" data obtained from patient biospecimens and records to guide therapy choices that generate good clinical outcomes. The approach relies on diagnostic and prognostic use of novel biomarkers discovered through combinations of tissue banking, bioinformatics, and electronic medical records (EMRs). The analytical power of bioinformatic platforms combined with patient clinical data from EMRs can reveal potential biomarkers and clinical phenotypes that allow researchers to develop experimental strategies using selected patient biospecimens stored in tissue banks. For cancer, high-quality biospecimens collected at diagnosis, first relapse, and various treatment stages provide crucial resources for study designs. To enlarge biospecimen collections, patient education regarding the value of specimen donation is vital. One approach for increasing consent is to offer publically available illustrations and game-like engagements demonstrating how wider sample availability facilitates development of novel therapies. The critical value of tissue bank samples, bioinformatics, and EMR in the early stages of the biomarker discovery process for personalized medicine is often overlooked. The data obtained also require cross-disciplinary collaborations to translate experimental results into clinical practice and diagnostic and prognostic use in personalized medicine.
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