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The role of infection models and PK/PD modelling for optimising care of critically ill patients with severe infections.

Identifieur interne : 000155 ( PubMed/Checkpoint ); précédent : 000154; suivant : 000156

The role of infection models and PK/PD modelling for optimising care of critically ill patients with severe infections.

Auteurs : T. T Ngdén [Suède] ; V. Ramos Martín [Royaume-Uni] ; T W Felton [Royaume-Uni] ; E I Nielsen [Suède] ; S. Marchand [France] ; R J Brüggemann [Pays-Bas] ; J B Bulitta [États-Unis] ; M. Bassetti [Italie] ; U. Theuretzbacher [Autriche] ; B T Tsuji [États-Unis] ; D W Wareham [Royaume-Uni] ; L E Friberg [Suède] ; J J De Waele [Belgique] ; V H Tam [États-Unis] ; Jason A. Roberts [Australie]

Source :

RBID : pubmed:28409203

Abstract

Critically ill patients with severe infections are at high risk of suboptimal antimicrobial dosing. The pharmacokinetics (PK) and pharmacodynamics (PD) of antimicrobials in these patients differ significantly from the patient groups from whose data the conventional dosing regimens were developed. Use of such regimens often results in inadequate antimicrobial concentrations at the site of infection and is associated with poor patient outcomes. In this article, we describe the potential of in vitro and in vivo infection models, clinical pharmacokinetic data and pharmacokinetic/pharmacodynamic models to guide the design of more effective antimicrobial dosing regimens. Individualised dosing, based on population PK models and patient factors (e.g. renal function and weight) known to influence antimicrobial PK, increases the probability of achieving therapeutic drug exposures while at the same time avoiding toxic concentrations. When therapeutic drug monitoring (TDM) is applied, early dose adaptation to the needs of the individual patient is possible. TDM is likely to be of particular importance for infected critically ill patients, where profound PK changes are present and prompt appropriate antibiotic therapy is crucial. In the light of the continued high mortality rates in critically ill patients with severe infections, a paradigm shift to refined dosing strategies for antimicrobials is warranted to enhance the probability of achieving drug concentrations that increase the likelihood of clinical success.

DOI: 10.1007/s00134-017-4780-6
PubMed: 28409203


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<div type="abstract" xml:lang="en">Critically ill patients with severe infections are at high risk of suboptimal antimicrobial dosing. The pharmacokinetics (PK) and pharmacodynamics (PD) of antimicrobials in these patients differ significantly from the patient groups from whose data the conventional dosing regimens were developed. Use of such regimens often results in inadequate antimicrobial concentrations at the site of infection and is associated with poor patient outcomes. In this article, we describe the potential of in vitro and in vivo infection models, clinical pharmacokinetic data and pharmacokinetic/pharmacodynamic models to guide the design of more effective antimicrobial dosing regimens. Individualised dosing, based on population PK models and patient factors (e.g. renal function and weight) known to influence antimicrobial PK, increases the probability of achieving therapeutic drug exposures while at the same time avoiding toxic concentrations. When therapeutic drug monitoring (TDM) is applied, early dose adaptation to the needs of the individual patient is possible. TDM is likely to be of particular importance for infected critically ill patients, where profound PK changes are present and prompt appropriate antibiotic therapy is crucial. In the light of the continued high mortality rates in critically ill patients with severe infections, a paradigm shift to refined dosing strategies for antimicrobials is warranted to enhance the probability of achieving drug concentrations that increase the likelihood of clinical success.</div>
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<Title>Intensive care medicine</Title>
<ISOAbbreviation>Intensive Care Med</ISOAbbreviation>
</Journal>
<ArticleTitle>The role of infection models and PK/PD modelling for optimising care of critically ill patients with severe infections.</ArticleTitle>
<Pagination>
<MedlinePgn>1021-1032</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1007/s00134-017-4780-6</ELocationID>
<Abstract>
<AbstractText>Critically ill patients with severe infections are at high risk of suboptimal antimicrobial dosing. The pharmacokinetics (PK) and pharmacodynamics (PD) of antimicrobials in these patients differ significantly from the patient groups from whose data the conventional dosing regimens were developed. Use of such regimens often results in inadequate antimicrobial concentrations at the site of infection and is associated with poor patient outcomes. In this article, we describe the potential of in vitro and in vivo infection models, clinical pharmacokinetic data and pharmacokinetic/pharmacodynamic models to guide the design of more effective antimicrobial dosing regimens. Individualised dosing, based on population PK models and patient factors (e.g. renal function and weight) known to influence antimicrobial PK, increases the probability of achieving therapeutic drug exposures while at the same time avoiding toxic concentrations. When therapeutic drug monitoring (TDM) is applied, early dose adaptation to the needs of the individual patient is possible. TDM is likely to be of particular importance for infected critically ill patients, where profound PK changes are present and prompt appropriate antibiotic therapy is crucial. In the light of the continued high mortality rates in critically ill patients with severe infections, a paradigm shift to refined dosing strategies for antimicrobials is warranted to enhance the probability of achieving drug concentrations that increase the likelihood of clinical success.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y">
<Author ValidYN="Y">
<LastName>Tängdén</LastName>
<ForeName>T</ForeName>
<Initials>T</Initials>
<AffiliationInfo>
<Affiliation>Department of Medical Sciences, Section of Infectious Diseases, Uppsala University, Uppsala, Sweden.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Ramos Martín</LastName>
<ForeName>V</ForeName>
<Initials>V</Initials>
<AffiliationInfo>
<Affiliation>Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Felton</LastName>
<ForeName>T W</ForeName>
<Initials>TW</Initials>
<AffiliationInfo>
<Affiliation>Intensive Care Unit, University Hospital of South Manchester, Manchester, UK.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Nielsen</LastName>
<ForeName>E I</ForeName>
<Initials>EI</Initials>
<AffiliationInfo>
<Affiliation>Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Marchand</LastName>
<ForeName>S</ForeName>
<Initials>S</Initials>
<AffiliationInfo>
<Affiliation>Inserm U1070, Pole Biologie Santé, Poitiers, France.</Affiliation>
</AffiliationInfo>
<AffiliationInfo>
<Affiliation>UFR Médecine-Pharmacie, Université de Poitiers, Poitiers, France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Brüggemann</LastName>
<ForeName>R J</ForeName>
<Initials>RJ</Initials>
<AffiliationInfo>
<Affiliation>Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Bulitta</LastName>
<ForeName>J B</ForeName>
<Initials>JB</Initials>
<AffiliationInfo>
<Affiliation>Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Bassetti</LastName>
<ForeName>M</ForeName>
<Initials>M</Initials>
<AffiliationInfo>
<Affiliation>Infectious Diseases Division, Santa Maria della Misericordia University Hospital and University of Udine, Udine, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Theuretzbacher</LastName>
<ForeName>U</ForeName>
<Initials>U</Initials>
<AffiliationInfo>
<Affiliation>Center for Anti-Infective Agents, Vienna, Austria.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Tsuji</LastName>
<ForeName>B T</ForeName>
<Initials>BT</Initials>
<AffiliationInfo>
<Affiliation>School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Wareham</LastName>
<ForeName>D W</ForeName>
<Initials>DW</Initials>
<AffiliationInfo>
<Affiliation>Antimicrobial Research Group, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Friberg</LastName>
<ForeName>L E</ForeName>
<Initials>LE</Initials>
<AffiliationInfo>
<Affiliation>Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>De Waele</LastName>
<ForeName>J J</ForeName>
<Initials>JJ</Initials>
<AffiliationInfo>
<Affiliation>Department of Critical Care Medicine, Ghent University Hospital, Ghent, Belgium.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Tam</LastName>
<ForeName>V H</ForeName>
<Initials>VH</Initials>
<AffiliationInfo>
<Affiliation>Department of Pharmacy Practice and Translational Research, University of Houston College of Pharmacy, Houston, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Roberts</LastName>
<ForeName>Jason A</ForeName>
<Initials>JA</Initials>
<Identifier Source="ORCID">http://orcid.org/0000-0001-6218-435X</Identifier>
<AffiliationInfo>
<Affiliation>Burns, Trauma and Critical Care Research Centre and Centre for Translational Anti-infective Pharmacodynamics, The University of Queensland, Brisbane, Australia. j.roberts2@uq.edu.au.</Affiliation>
</AffiliationInfo>
<AffiliationInfo>
<Affiliation>Departments of Intensive Care Medicine and Pharmacy, Royal Brisbane and Women's Hospital, Level 3, Ned Hanlon Building, Herston, Brisbane, QLD, 4029, Australia. j.roberts2@uq.edu.au.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<CollectiveName>Infection Section for the European Society of Intensive Care Medicine, the Pharmacokinetics and Pharmacodynamics Study Group of the European Society of Clinical Microbiology and Infectious Diseases, the International Society of Anti-Infective Pharmacology and the Critically Ill Patients Study Group of European Society of Clinical Microbiology and Infectious Diseases</CollectiveName>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList>
<PublicationType UI="D016428">Journal Article</PublicationType>
<PublicationType UI="D016454">Review</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic">
<Year>2017</Year>
<Month>04</Month>
<Day>13</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo>
<Country>United States</Country>
<MedlineTA>Intensive Care Med</MedlineTA>
<NlmUniqueID>7704851</NlmUniqueID>
<ISSNLinking>0342-4642</ISSNLinking>
</MedlineJournalInfo>
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<KeywordList Owner="NOTNLM">
<Keyword MajorTopicYN="N">Antibiotics</Keyword>
<Keyword MajorTopicYN="N">Individualised dosing</Keyword>
<Keyword MajorTopicYN="N">Mathematical modelling</Keyword>
<Keyword MajorTopicYN="N">Pharmacodynamics</Keyword>
<Keyword MajorTopicYN="N">Pharmacokinetics</Keyword>
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<Month>10</Month>
<Day>31</Day>
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<Year>2017</Year>
<Month>03</Month>
<Day>18</Day>
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<Year>2017</Year>
<Month>4</Month>
<Day>15</Day>
<Hour>6</Hour>
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<li>Australie</li>
<li>Autriche</li>
<li>Belgique</li>
<li>France</li>
<li>Italie</li>
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<li>Royaume-Uni</li>
<li>Suède</li>
<li>États-Unis</li>
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<li>East Middle Sweden</li>
<li>Grand Londres</li>
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<li>Poitou-Charentes</li>
<li>Svealand</li>
<li>Texas</li>
<li>Vienne (Autriche)</li>
<li>État de New York</li>
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<li>Buffalo (New York)</li>
<li>Houston</li>
<li>Londres</li>
<li>Manchester</li>
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<li>Poitiers</li>
<li>Uppsala</li>
<li>Vienne (Autriche)</li>
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