title: Bacterial temporal dynamics enable optimal design of antibiotic treatment.
abstract: There is a critical need to better use existing antibiotics due to the urgent threat of antibiotic resistant bacteria coupled with the reduced effort in developing new antibiotics. β-lactam antibiotics represent one of the most commonly used classes of antibiotics to treat a broad spectrum of Gram-positive and -negative bacterial pathogens. However, the rise of extended spectrum β-lactamase (ESBL) producing bacteria has limited the use of β-lactams. Due to the concern of complex drug responses, many β-lactams are typically ruled out if ESBL-producing pathogens are detected, even if these pathogens test as susceptible to some β-lactams. Using quantitative modeling, we show that β-lactams could still effectively treat pathogens producing low or moderate levels of ESBLs when administered properly. We further develop a metric to guide the design of a dosing protocol to optimize treatment efficiency for any antibiotic-pathogen combination. Ultimately, optimized dosing protocols could allow reintroduction of a repertoire of first-line antibiotics with improved treatment outcomes and preserve last-resort antibiotics.
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.
authors.forename: Hannah R
authors.initials: HR
authors.lastname: Meredith
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.
authors.forename: Allison J
authors.initials: AJ
authors.lastname: Lopatkin
authors.affiliation: Division of Infectious Diseases, Department of Medicine, Duke University Medical Center, Durham, North Carolina, United States of America; Duke Infection Control Outreach Network, Duke University Medical Center, Durham, North Carolina, United States of America.
authors.forename: Deverick J
authors.initials: DJ
authors.lastname: Anderson
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America; Center for Systems Biology, Duke University, Durham, North Carolina, United States of America; Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, United States of America.
authors.forename: Lingchong
authors.initials: L
authors.lastname: You
mesh_terms: D018407:Bacterial Physiological Phenomena / Q000187:drug effects*; D002470:Cell Survival / Q000187:drug effects / Q000502:physiology; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D004334:Drug Administration Schedule; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D013997:Time Factors; D018440:beta-Lactam Resistance / Q000187:drug effects / Q000502:physiology*; D001618:beta-Lactamases / Q000378:metabolism*; D047090:beta-Lactams / Q000008:administration & dosage*
chemical_list: D047090:beta-Lactams; D001618:beta-Lactamases