User:Kairui jiang/sandbox

anticoagulant, warfarin, pharmacokinetics, pharmacodynamics,

An overall process of personalized cancer therapy. Genome sequencing will allow for a more accurate and personalized drug prescription and a targeted therapy for different patients.

For instance, warfarin is a FDA approved oral anticoagulant commonly prescribed to patients with blood clots, but the rate of minor and major adverse events from this drug is among the highest of all commonly prescribed drugs, due to warfarin’s significant interindividual variability in pharmacokinetics and pharmacodynamics. [1] However, with the discovery of polymorphic variants in CYP2C9 and VKORC1 genotypes, two genes that encode the individual anticoagulant response, [2][3] physicians can use patients’ gene profile to prescribe optimum doses of warfarin to prevent side effects such as major bleeding and to allow sooner and better therapeutic efficacy. [1]

New methods are needed for delivering personalized drugs generated from pharmacy compounding efficiently to the disease sites of the body. [4] For instance, researchers are now exploring ways to engineer nanocarriers that can precisely target the specific site by using real-time imaging and analyzing the pharmacodynamics of the drug delivery. [5] Currently, several candidate nanocarriers are being investigated, which are Iron oxide nanoparticles, quantum dots, carbon nanotubes, gold nanoparticles and silica nanoparticles. These nanoparticles’ surface chemistry is designed to be able to load them with drugs and to avoid the body’s immune recognition and therefore makes nanoparticle-based theranostics possible.[4][6] Nanocarriers’ targeting strategies are varied according to the disease. For example, if the disease is cancer, a common approach is to identify the biomarker expressed on the surface of cancer cells and to load its associated binding vector onto nanocarrier to achieve recognition and targeting; the size scale of the nanocarriers will also be engineered to reach the enhanced permeability and retention effect (EPR) in tumor targeting. [6] If the disease is localized in the specific organ, such as kidney, the surface of the nanocarriers can be coated with certain ligand that binds to the receptors inside that organ to achieve organ-targeting drug delivery and avoid non-specific uptake. [7] Despite the great potential of this nanoparticle-based drug delivery system, the significant progress in the field is yet to be made, and the nanocarriers are still being investigated and modified to meet clinical standards. [5][6]

The preparation of a proteomics sample on a sample carrier to be analyzed by mass spectrometry.

In specific, proteomics is used to analyze a series of protein expressions, instead of a single biomarker. [8] Proteins control the body’s biological activities including health and disease, so proteomics is helpful in early diagnosis. In the case of respiratory disease, proteomics analyzes several biological samples including serum, blood cells, bronchoalveolar lavage fluids (BAL), nasal lavage fluids (NLF), sputum, among others. [8] The identification and quantification of complete protein expression from these biological samples are conducted by mass spectrometry and advanced analytical techniques [9]. Respiratory proteomics has made significant progress in the development of personalized medicine for supporting health care in recent years. For example, in a study conducted by Lazzari et al. in 2012, proteomic-based approach has made substantial improvement in identifying multiple biomarkers of lung cancer that can be used in tailoring personalized treatments for each individual patient [10]. More and more studies have demonstrated the usefulness of proteomics to provide targeted therapies for respiratory disease [8].

drug delivery Iron oxide nanoparticles, quantum dots, carbon nanotubes, gold nanoparticles and silica nanoparticles

enhanced permeability and retention effect ligand proteomics biomarker bronchoalveolar lavage fluids nasal lavage fluids mass spectrometry fMRI micro-CT microarrays SNPs links