Biomarker and IVD Validation
Gain Time Through a Faster Biomarker and Diagnostics/IVD Validation
Expert skills in Biomarker Validation and Diagnostics/IVD Validation
IDDI has developed a Bayesian approach to accelerate the development and validation of Biomarkers. This methodology, which provides a more intelligent, faster and cheaper biomarker validation and development process, has been tested for Alzheimer’s Disease (AD) and is also suitable for biomarkers in other areas. We take advantage of Bayesian statistical methods, which can incorporate prior knowledge and integrate different sources of information, in combination with adaptive design concepts, which tailor features based on ongoing information.
Our expertise can help you develop diagnostic, prognostic, predictive and surrogate biomarkers.
IDDI has advanced knowledge and extensive real-world experience delivering innovative analytical strategies to pharmaceutical and biotech companies.
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Long-Standing Experience in Identifying and Validating Single Biomarkers, Biomarker Profiles, Diagnostics and IVD:
The development and qualification of biomarkers are keys to the future of drug development and personalized medicine. Precision medicine relies on validated biomarkers that allow classification of patients by their probable disease risk, prognosis, or response to treatment. Moreover, our statisticians have developed methods and published extensively on surrogate endpoints and biomarker-based endpoints to expedite drug development in precision medicine, notably in cancer research.
IDDI Projects in Biomarker Validation and Diagnostics/IVD Validation:
- DIAGNOSTIC BIOMARKERS
- Construct BIOMARKER PROFILES based on multiple biomarkers.
- PROGNOSTIC BIOMARKERS: Affect the outcome of patients in terms of clinical endpoint: Useful primarily to adjust therapy, with patients with poor prognosis being treated more aggressively than patients with good prognosis
- PREDICTIVE BIOMARKERS: Affect the effect of a specific treatment on a clinical endpoint. Used to select subsets of patients who derive the most benefit (or the least toxicity) from a new treatment, in order to limit clinical trials to this subset and/or to stratify patients according to the biomarker
- SURROGATE BIOMARKERS: Aim at replacing a clinical endpoint in clinical trials carried out to evaluate the effect of a specific treatment.
IDDI has experience in the challenging statistical issues that characterize the identification and validation of biomarkers of diagnostic utility, prognostic and/or predictive ability, and those that can potentially be used as surrogate endpoints in clinical trials.
READ : ‘Transferring Cut-off Values between Assays for Cerebrospinal Fluid Alzheimer’s Disease Biomarkers‘ by Leandro Garcıa Barrado, Els Coart, Hugo M.J. Vanderstichele and Tomasz Burzykowski