Prediction of clinically relevant safety signals of nephrotoxicity through plasma metabolite profiling.

Author: BushE D, FabianE, HeroldM, KampH G, KrennrichG, LooserR, MattesW B, MellertW, MoellerN, NadanacivaS, NaraokaH, OmuraK, PiccoliS P, ProkoudineA, Ruiz-NoppingerP, Schuppe-KoistinenI, StraussV, WalkT, van RavenzwaayB

Paper Details 
Original Abstract of the Article :
Addressing safety concerns such as drug-induced kidney injury (DIKI) early in the drug pharmaceutical development process ensures both patient safety and efficient clinical development. We describe a unique adjunct to standard safety assessment wherein the metabolite profile of treated animals is co...See full text at original site
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引用元:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3673329/

データ提供:米国国立医学図書館(NLM)

Predicting Nephrotoxicity Through Plasma Metabolite Profiling

This study explores the potential of plasma metabolite profiling to predict drug-induced kidney injury (DIKI) early in the drug development process. The researchers compared the metabolite profiles of treated animals with a database of known toxicities to identify potential safety signals for various adverse events, including DIKI.

Metabolite Profiling for Drug Safety

The study demonstrated that metabolite profiling can effectively predict DIKI for certain drugs, such as cyclosporine A and doxorubicin, while correctly indicating the absence of DIKI for other drugs like phenytoin. This approach offers a valuable tool for augmenting standard safety assessments and potentially avoiding clinical adverse events.

Enhancing Drug Safety and Development

This research emphasizes the importance of utilizing innovative tools and techniques to enhance drug safety in the pharmaceutical development process. By identifying potential toxicities early on, researchers can optimize drug development strategies and minimize the risk of adverse events in clinical trials. As a camel who has witnessed the transformative power of scientific innovation, I am excited by the possibilities of using new technologies to improve human health.

Dr.Camel's Conclusion

This study demonstrates the potential of metabolomics for predicting drug-induced kidney injury and other adverse events. It highlights the importance of integrating cutting-edge technologies into drug development processes to improve safety and optimize therapeutic outcomes. As we continue to explore the vast desert of medical research, we must embrace new tools and techniques that enhance our ability to protect patient health and advance medical progress.
Date :
  1. Date Completed 2013-12-04
  2. Date Revised 2021-10-21
Further Info :

Pubmed ID

23762827

DOI: Digital Object Identifier

PMC3673329

Related Literature

SNS
PICO Info
in preparation
Languages

English

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