Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies
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{"title"=>"Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies", "type"=>"journal", "authors"=>[{"first_name"=>"Pia", "last_name"=>"Abel zur Wiesch", "scopus_author_id"=>"37070258000"}, {"first_name"=>"Fabrizio", "last_name"=>"Clarelli", "scopus_author_id"=>"57194581185"}, {"first_name"=>"Ted", "last_name"=>"Cohen", "scopus_author_id"=>"7202415780"}], "year"=>2017, "source"=>"PLoS Computational Biology", "identifiers"=>{"scopus"=>"2-s2.0-85011349907", "sgr"=>"85011349907", "doi"=>"10.1371/journal.pcbi.1005321", "pui"=>"614304552", "pmid"=>"28060813", "isbn"=>"1111111111", "issn"=>"15537358"}, "id"=>"3faca2ff-7f2b-3b00-b285-6d9b1193b564", "abstract"=>"Identifying optimal dosing of antibiotics has proven challenging-some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood.", "link"=>"http://www.mendeley.com/research/using-chemical-reaction-kinetics-predict-optimal-antibiotic-treatment-strategies", "reader_count"=>20, "reader_count_by_academic_status"=>{"Researcher"=>10, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>3, "Student > Master"=>1, "Other"=>1, "Student > Bachelor"=>3, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_user_role"=>{"Researcher"=>10, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>3, "Student > Master"=>1, "Other"=>1, "Student > Bachelor"=>3, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>3, "Biochemistry, Genetics and Molecular Biology"=>2, "Mathematics"=>1, "Agricultural and Biological Sciences"=>8, "Medicine and Dentistry"=>2, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Chemical Engineering"=>1, "Physics and Astronomy"=>2}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>3}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>8}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}, "Mathematics"=>{"Mathematics"=>1}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Chemical Engineering"=>{"Chemical Engineering"=>1}}, "reader_count_by_country"=>{"Korea (South)"=>1}, "group_count"=>1}

Scopus | Further Information

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