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      Impact of Sampling Period on Population Pharmacokinetic Analysis of Antibiotics: Why do You Take Blood Samples Following the Fourth Dose?

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          Abstract

          To date, many population pharmacokinetic models of antibiotics have been developed using blood sampling data after the fourth or fifth dose, which represents steady-state levels. However, if a model developed using blood sampled after the first dose is equivalent to that using blood sampled after the fourth dose, it would be advantageous to utilize the former. The aim of this study was to investigate the effect of blood sampling after the first and/or fourth drug administration on the accuracy and precision of parameter estimates. A previously reported robust, two-compartment model of vancomycin was used for simulation to evaluate the performances of the parameter estimates. The parameter estimation performances were assessed using relative bias and relative root mean square error. Performance was investigated in 72 scenarios consisting of a combination of two blood sampling periods (the first and fourth dose), two total clearances, three infusion times, and four sample sizes. The population pharmacokinetic models from data collected at the first dose and those collected at the fourth dose produced parameter estimates that were similar in accuracy and precision. This study will contribute to increasing the efficiency and simplicity of antibiotic pharmacokinetic studies.

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          A new initiative on precision medicine.

          President Obama has announced a research initiative that aims to accelerate progress toward a new era of precision medicine, with a near-term focus on cancers and a longer-term aim to generate knowledge applicable to the whole range of health and disease.
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            Precision Medicine: From Science To Value

            Precision medicine is making an impact on patients, health care delivery systems, and research participants in ways that were only imagined fifteen years ago when the human genome was first sequenced. Discovery of disease-causing and drug-response genetic variants has accelerated, while adoption into clinical medicine has lagged. We define precision medicine and the stakeholder community required to enable its integration into research and health care. We explore the intersection of data science, analytics, and precision medicine in the formation of health systems that carry out research in the context of clinical care and that optimize the tools and information used to deliver improved patient outcomes. We provide examples of real-world impact and conclude with a policy and economic agenda necessary for the adoption of this new paradigm of health care both in the United States and globally.
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              Individualised antibiotic dosing for patients who are critically ill: challenges and potential solutions.

              Infections in critically ill patients are associated with persistently poor clinical outcomes. These patients have severely altered and variable antibiotic pharmacokinetics and are infected by less susceptible pathogens. Antibiotic dosing that does not account for these features is likely to result in suboptimum outcomes. In this Review, we explore the challenges related to patients and pathogens that contribute to inadequate antibiotic dosing and discuss how to implement a process for individualised antibiotic therapy that increases the accuracy of dosing and optimises care for critically ill patients. To improve antibiotic dosing, any physiological changes in patients that could alter antibiotic concentrations should first be established; such changes include altered fluid status, changes in serum albumin concentrations and renal and hepatic function, and microvascular failure. Second, antibiotic susceptibility of pathogens should be confirmed with microbiological techniques. Data for bacterial susceptibility could then be combined with measured data for antibiotic concentrations (when available) in clinical dosing software, which uses pharmacokinetic/pharmacodynamic derived models from critically ill patients to predict accurately the dosing needs for individual patients. Individualisation of dosing could optimise antibiotic exposure and maximise effectiveness. Copyright © 2014 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Pharmaceuticals (Basel)
                Pharmaceuticals (Basel)
                pharmaceuticals
                Pharmaceuticals
                MDPI
                1424-8247
                16 September 2020
                September 2020
                : 13
                : 9
                : 249
                Affiliations
                [1 ]Department of Pharmacology, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Korea; kswlab2015@ 123456gmail.com
                [2 ]Drug Evaluation Department, National Institute of Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Osong, Cheongju 28159, Korea; nobaes79@ 123456gmail.com
                [3 ]Division of Hematology-Oncology, Department of Internal Medicine, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang 14066, Korea; fhdzang@ 123456gmail.com
                [4 ]Department of Clinical Pharmacology, Hallym University Sacred Heart Hospital, Anyang 14066, Korea
                Author notes
                [* ]Correspondence: dhlee97@ 123456gmail.com ; Tel.: +82-31-380-4778
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-0236-3257
                https://orcid.org/0000-0002-2602-7848
                https://orcid.org/0000-0002-8681-099X
                Article
                pharmaceuticals-13-00249
                10.3390/ph13090249
                7558941
                32947890
                a6d46cd5-65bd-4689-a0df-60d977917515
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 17 August 2020
                : 14 September 2020
                Categories
                Article

                population pharmacokinetics,antibiotics,sampling period,first dose,fourth dose

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