Article

Successes achieved and challenges ahead in translating biomarkers into clinical applications.

Department of Nephrology, Monash Medical Center, Clayton, Victoria, Australia.
The AAPS Journal (Impact Factor: 3.91). 03/2010; 12(3):243-53. DOI: 10.1208/s12248-010-9182-4
Source: PubMed

ABSTRACT Biomarkers are important tools for identifying and stratifying diseases, predicting their progression and determining the effectiveness, safety, and doses of therapeutic interventions. This is important for common chronic diseases such as diabetic nephropathy, osteoporosis, and rheumatoid arthritis which affect large numbers of patients worldwide. This article summarizes the current knowledge of established and novel biomarkers for each of these diseases as presented at the 2008 AAPS/ACCP joint symposium "Success Achieved and Challenges Ahead in Translating Biomarkers into Clinical Applications," in Atlanta, Georgia. The advantages and disadvantages of various proteomic, metabolomic, genomic, and imaging biomarkers are discussed in relation to disease diagnosis and stratification, prognosis, drug development, and potential clinical applications. The use of biomarkers as a means to determine therapeutic interventions is also considered. In addition, we show that biomarkers may be useful for adapting therapies for individual needs by allowing the selection of patients who are most likely to respond or react adversely to a particular treatment. They may also be used to determine whether the development of a novel therapy is worth pursuing by informing crucial go/no go decisions around safety and efficacy. Indeed, regulatory bodies now suggest that effective integration of biomarkers into clinical drug development programs is likely to promote the development of novel therapeutics and more personalized medicine.

Full-text

Available from: Shashi Amur, Apr 20, 2015
0 Followers
 · 
96 Views
  • Source
    101 edited by Paul C Guest and Sabine Bahn, 11/2011; Academic Press., ISBN: 0123877180
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Translational medicine is a rollercoaster with occasional brilliant successes and a large majority of failures. 'LiT1', beginning in the 1950's, was a golden era built on earlier advances in experimental physiology, biochemistry and pharmacology, with a dash of serendipity, that led to discovery of many new drugs for serious illnesses. LiT2 saw the large scale industrialisation of drug discovery using high throughput screens and assays based on affinity for the target molecule. The links between drug development and university sciences and medicine weakened, but there were still some brilliant successes. In LiT3 the coverage of translational medicine, expanded from molecular biology to drug budgets, with much greater emphasis on safety and official regulation. Compared to R&D expenditure the number of breakthrough discoveries in LiT3 was disappointing but monoclonal antibodies (mAbs) for immunity and inflammation brought in a new golden era and kinase inhibitors such as imatinib were breakthroughs in cancer. The pharmaceutical industry is trying to revive the LiT1 approach by using phenotypic assays and closer links with academia. LiT4 faces a data explosion generated by the genome project, GWAS, ENCODE and the 'omics' that is in danger of leaving LiT4 in a computerised cloud. Industrial labs are filled with masses of automated machinery while the scientists sit in a separate room viewing the results on their computers. Big Data will need Big Thinking in LiT4 but with so many unmet medical needs and so many new opportunities being revealed there are high hopes that the rollercoaster will ride high again.
    British Journal of Pharmacology 01/2014; DOI:10.1111/bph.12580 · 4.99 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: RA is a complex disease that develops as a series of events often referred to as disease continuum. RA would benefit from novel biomarker development for diagnosis where new biomarkers are still needed (even if progresses have been made with the inclusion of ACPA into the ACR/EULAR 2010 diagnostic criteria) and for prognostic notably in at risk of evolution patients with autoantibody-positive arthralgia. Risk biomarkers for rapid evolution or cardiovascular complications are also highly desirable. Monitoring biomarkers would be useful in predicting relapse. Finally, predictive biomarkers for therapy outcome would allow tailoring therapy to the individual. Increasing numbers of cytokines have been involved in RA pathology. Many have the potential as biomarkers in RA especially as their clinical utility is already established in other diseases and could be easily transferable to rheumatology. We will review the current knowledge's relation to cytokine used as biomarker in RA. However, given the complexity and heterogeneous nature of RA, it is unlikely that a single cytokine may provide sufficient discrimination; therefore multiple biomarker signatures may represent more realistic approach for the future of personalised medicine in RA.
    Mediators of Inflammation 03/2014; 2014:545493. DOI:10.1155/2014/545493 · 2.42 Impact Factor