Area:
decision-making, neuroeconomics
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High-probability grants
According to our matching algorithm, Jian Li is the likely recipient of the following grants.
| Years |
Recipients |
Code |
Title / Keywords |
Matching
score |
| 2014 — 2018 |
Li, Jian
Tsuji, Brian |
R01Activity Code Description:
To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Novel Pk/Pd Strategies For Polymyxin Combinations Against Gram-Negative Superbugs @ State University of New York At Buffalo
DESCRIPTION (provided by applicant): Multidrug-resistant Gram-negative 'superbugs' are causing a global health crisis. Due to a marked decline in the discovery of antibiotics and the current shortage of new antibiotics, clinicians are often left with little option but to use the polymyxins (polymyxin B and colistin, i.e. polymyxin E). Polymyxins first came onto the market more than 50 years ago and have been used rarely, until recent times. Unfortunately, there is mounting evidence that resistance to polymyxins is increasing. A major factor promoting resistance is that plasma concentrations of polymyxins at recommended daily doses are sub-optimal in a significant proportion of critically-ill patients. Unfortunately, simply increasing th polymyxin daily dose is not an option because kidney toxicity (up to 60% incidence with current regimens) is the major dose-limiting adverse effect. Emergence of resistance to polymyxins is a significant risk with monotherapy and, because of the 'last-line' status, implies resistance to all current antibiotics. This highlights the urgent need to explore novel, highly active dosing strategies with polymyxin combinations. The central aim of the present project is to evaluate novel dosing regimens for polymyxin combinations to maximize antibacterial activity and minimize emergence of resistance and toxicity. Our research strategy involves a systematic evaluation of the effectiveness of novel 'burst', 'front-loading' (e.g. high dose, short duration dosing at the beginning of therapy) and 'sequential' polymyxin combination dosing strategies. The research plan incorporates a multi-tiered approach across a range of in vitro and rabbit infection models. First, in vitro models will be used to simulate the conditions of infection and drug concentration-time profiles in the human body to devise combination dosing strategies that most effectively kill both polymyxin-susceptible and polymyxin-resistant bacteria. Next, promising dosing strategies for the polymyxin combinations will be tested for resistance suppression against clinical isolates in a hollow-fiber infection model. Cutting-edge genomics/transcriptomics/metabolomics studies will guide selection of optimal regimens by characterizing the global bacterial responses (including emergence of resistance) to the novel combination dosing strategies. Finally, prospective validation studies for our superior regimens will be conducted in 10-day immune-compromised and -competent rabbit infection models for prospective evaluation of resistance suppression and toxicity. Each progressive stage will provide key information to uniquely inform the development of innovative mechanism-based mathematical models that will be used to translate across all experimental tiers. The final translation will be performed by mechanism-based Monte Carlo Simulations to propose novel dosing strategies for polymyxin combinations that maximize antibacterial activity and minimize resistance and toxicity for future testing in humans.
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