Use of Preclinical Data for Selection of a Phase II/III Dose for Evernimicin and Identification of a Preclinical MIC Breakpoint
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| Published in: | Antimicrobial Agents and Chemotherapy Vol. 45; no. 1; pp. 13 - 22 |
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| Main Authors: | , , , , , , , |
| Format: | Journal Article |
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01-01-2001
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| AbstractList | One of the most challenging issues in the design of phase II/III clinical trials of antimicrobial agents is dose selection. The choice is often based on preclinical data from pharmacokinetic (PK) studies with animals and healthy volunteers but is rarely linked directly to the target organisms except by the MIC, an in vitro measure of antimicrobial activity with many limitations. It is the thesis of this paper that rational dose-selection decisions can be made on the basis of the pharmacodynamics (PDs) of the test agent predicted by a mathematical model which uses four data sets: (i) the distribution of MICs for clinical isolates, (ii) the distribution of the values of the PK parameters for the test drug in the population, (iii) the PD target(s) developed from animal models of infection, and (iv) the protein binding characteristics of the test drug. In performing this study with the new anti-infective agent evernimicin, we collected a large number (n = 4,543) of recent clinical isolates of gram-positive pathogens (Streptococcus pneumoniae, Enterococcus faecalis and Enterococcus faecium, and Staphylococcus aureus) and determined the MICs using E-test methods (AB Biodisk, Stockholm, Sweden) for susceptibility to evernimicin. Population PK data were collected from healthy volunteers (n = 40) and patients with hypoalbuminemia (n = 12), and the data were analyzed by using NPEM III. PD targets were developed with a neutropenic murine thigh infection model with three target pathogens: S. pneumoniae (n = 5), E. faecalis (n = 2), and S. aureus (n = 4). Drug exposure or the ratio of the area under the concentration-time curve/MIC (AUC/MIC) was found to be the best predictor of microbiological efficacy. There were three possible microbiological results: stasis of the initial inoculum at 24 h (10(7) CFU), log killing (pathogen dependent, ranging from 1 to 3 log(10)), or 90% maximal killing effect (90% E(max)). The levels of protein binding in humans and mice were similar. The PK and PD of 6 and 9 mg of evernimicin per kg of body weight were compared; the population values for the model parameters and population covariance matrix were used to generate five Monte Carlo simulations with 200 subjects each. The fractional probability of attaining the three PD targets was calculated for each dose and for each of the three pathogens. All differences in the fractional probability of attaining the target AUC/MIC in this PD model were significant. For S. pneumoniae, the probability of attaining all three PD targets was high for both doses. For S. aureus and enterococci, there were increasing differences between the 6- and 9-mg/kg evernimicin doses for reaching the 2 log killing (S. aureus), 1 log killing (enterococci), or 90% E(max) AUC/MIC targets. This same approach may also be used to set preliminary in vitro MIC breakpoints. One of the most challenging issues in the design of phase II/III clinical trials of antimicrobial agents is dose selection. The choice is often based on preclinical data from pharmacokinetic (PK) studies with animals and healthy volunteers but is rarely linked directly to the target organisms except by the MIC, an in vitro measure of antimicrobial activity with many limitations. It is the thesis of this paper that rational dose-selection decisions can be made on the basis of the pharmacodynamics (PDs) of the test agent predicted by a mathematical model which uses four data sets: (i) the distribution of MICs for clinical isolates, (ii) the distribution of the values of the PK parameters for the test drug in the population, (iii) the PD target(s) developed from animal models of infection, and (iv) the protein binding characteristics of the test drug. In performing this study with the new anti-infective agent evernimicin, we collected a large number (n = 4,543) of recent clinical isolates of gram-positive pathogens (Streptococcus pneumoniae, Enterococcus faecalis and Enterococcus faecium, and Staphylococcus aureus) and determined the MICs using E-test methods (AB Biodisk, Stockholm, Sweden) for susceptibility to evernimicin. Population PK data were collected from healthy volunteers (n = 40) and patients with hypoalbuminemia (n = 12), and the data were analyzed by using NPEM III. PD targets were developed with a neutropenic murine thigh infection model with three target pathogens: S. pneumoniae (n = 5), E. faecalis (n = 2), and S. aureus (n = 4). Drug exposure or the ratio of the area under the concentration-time curve/MIC (AUC/MIC) was found to be the best predictor of microbiological efficacy. There were three possible microbiological results: stasis of the initial inoculum at 24 h (10 super(7) CFU), log killing (pathogen dependent, ranging from 1 to 3 log sub(10)), or 90% maximal killing effect (90% E sub(max)). The levels of protein binding in humans and mice were similar. The PK and PD of 6 and 9 mg of evernimicin per kg of body weight were compared; the population values for the model parameters and population covariance matrix were used to generate five Monte Carlo simulations with 200 subjects each. The fractional probability of attaining the three PD targets was calculated for each dose and for each of the three pathogens. All differences in the fractional probability of attaining the target AUC/MIC in this PD model were significant. For S. pneumoniae, the probability of attaining all three PD targets was high for both doses. For S. aureus and enterococci, there were increasing differences between the 6- and 9-mg/kg evernimicin doses for reaching the 2 log killing (S. aureus), 1 log killing (enterococci), or 90% E sub(max) AUC/MIC targets. This same approach may also be used to set preliminary in vitro MIC breakpoints. One of the most challenging issues in the design of phase II/III clinical trials of antimicrobial agents is dose selection. The choice is often based on preclinical data from pharmacokinetic (PK) studies with animals and healthy volunteers but is rarely linked directly to the target organisms except by the MIC, an in vitro measure of antimicrobial activity with many limitations. It is the thesis of this paper that rational dose-selection decisions can be made on the basis of the pharmacodynamics (PDs) of the test agent predicted by a mathematical model which uses four data sets: (i) the distribution of MICs for clinical isolates, (ii) the distribution of the values of the PK parameters for the test drug in the population, (iii) the PD target(s) developed from animal models of infection, and (iv) the protein binding characteristics of the test drug. In performing this study with the new anti-infective agent evernimicin, we collected a large number ( n = 4,543) of recent clinical isolates of gram-positive pathogens ( Streptococcus pneumoniae , Enterococcus faecalis and Enterococcus faecium , and Staphylococcus aureus ) and determined the MICs using E-test methods (AB Biodisk, Stockholm, Sweden) for susceptibility to evernimicin. Population PK data were collected from healthy volunteers ( n = 40) and patients with hypoalbuminemia ( n = 12), and the data were analyzed by using NPEM III. PD targets were developed with a neutropenic murine thigh infection model with three target pathogens: S. pneumoniae ( n = 5), E. faecalis ( n = 2), and S. aureus ( n = 4). Drug exposure or the ratio of the area under the concentration-time curve/MIC (AUC/MIC) was found to be the best predictor of microbiological efficacy. There were three possible microbiological results: stasis of the initial inoculum at 24 h (10 7 CFU), log killing (pathogen dependent, ranging from 1 to 3 log 10 ), or 90% maximal killing effect (90% E max ). The levels of protein binding in humans and mice were similar. The PK and PD of 6 and 9 mg of evernimicin per kg of body weight were compared; the population values for the model parameters and population covariance matrix were used to generate five Monte Carlo simulations with 200 subjects each. The fractional probability of attaining the three PD targets was calculated for each dose and for each of the three pathogens. All differences in the fractional probability of attaining the target AUC/MIC in this PD model were significant. For S. pneumoniae , the probability of attaining all three PD targets was high for both doses. For S. aureus and enterococci, there were increasing differences between the 6- and 9-mg/kg evernimicin doses for reaching the 2 log killing ( S. aureus ), 1 log killing (enterococci), or 90% E max AUC/MIC targets. This same approach may also be used to set preliminary in vitro MIC breakpoints. One of the most challenging issues in the design of phase II/III clinical trials of antimicrobial agents is dose selection. The choice is often based on preclinical data from pharmacokinetic (PK) studies with animals and healthy volunteers but is rarely linked directly to the target organisms except by the MIC, an in vitro measure of antimicrobial activity with many limitations. It is the thesis of this paper that rational dose-selection decisions can be made on the basis of the pharmacodynamics (PDs) of the test agent predicted by a mathematical model which uses four data sets: (i) the distribution of MICs for clinical isolates, (ii) the distribution of the values of the PK parameters for the test drug in the population, (iii) the PD target(s) developed from animal models of infection, and (iv) the protein binding characteristics of the test drug. In performing this study with the new anti-infective agent evernimicin, we collected a large number (n = 4,543) of recent clinical isolates of gram-positive pathogens (Streptococcus pneumoniae,Enterococcus faecalis and Enterococcus faecium, and Staphylococcus aureus) and determined the MICs using E-test methods (AB Biodisk, Stockholm, Sweden) for susceptibility to evernimicin. Population PK data were collected from healthy volunteers (n = 40) and patients with hypoalbuminemia (n = 12), and the data were analyzed by using NPEM III. PD targets were developed with a neutropenic murine thigh infection model with three target pathogens: S. pneumoniae (n = 5), E. faecalis(n = 2), and S. aureus (n= 4). Drug exposure or the ratio of the area under the concentration-time curve/MIC (AUC/MIC) was found to be the best predictor of microbiological efficacy. There were three possible microbiological results: stasis of the initial inoculum at 24 h (107 CFU), log killing (pathogen dependent, ranging from 1 to 3 log10), or 90% maximal killing effect (90%Emax). The levels of protein binding in humans and mice were similar. The PK and PD of 6 and 9 mg of evernimicin per kg of body weight were compared; the population values for the model parameters and population covariance matrix were used to generate five Monte Carlo simulations with 200 subjects each. The fractional probability of attaining the three PD targets was calculated for each dose and for each of the three pathogens. All differences in the fractional probability of attaining the target AUC/MIC in this PD model were significant. For S. pneumoniae, the probability of attaining all three PD targets was high for both doses. For S. aureus and enterococci, there were increasing differences between the 6- and 9-mg/kg evernimicin doses for reaching the 2 log killing (S. aureus), 1 log killing (enterococci), or 90%Emax AUC/MIC targets. This same approach may also be used to set preliminary in vitro MIC breakpoints. Classifications Services AAC Citing Articles Google Scholar PubMed Related Content Social Bookmarking CiteULike Delicious Digg Facebook Google+ Mendeley Reddit StumbleUpon Twitter current issue AAC About AAC Subscribers Authors Reviewers Advertisers Inquiries from the Press Permissions & Commercial Reprints ASM Journals Public Access Policy AAC RSS Feeds 1752 N Street N.W. • Washington DC 20036 202.737.3600 • 202.942.9355 fax • journals@asmusa.org Print ISSN: 0066-4804 Online ISSN: 1098-6596 Copyright © 2014 by the American Society for Microbiology. For an alternate route to AAC .asm.org, visit: AAC |
| Author | C. Hardalo W. A. Craig R. Hare S. L. Preston C. Banfield D. Andes G. L. Drusano O. Vesga |
| AuthorAffiliation | Division of Clinical Pharmacology, Albany Medical College, Albany, New York 1 ; Schering Plough Research Institute, Kenilworth, New Jersey 2 ; and Division of Clinical Pharmacology, University of Wisconsin, Madison, Wisconsin 3 |
| AuthorAffiliation_xml | – name: Division of Clinical Pharmacology, Albany Medical College, Albany, New York 1 ; Schering Plough Research Institute, Kenilworth, New Jersey 2 ; and Division of Clinical Pharmacology, University of Wisconsin, Madison, Wisconsin 3 |
| Author_xml | – sequence: 1 givenname: G. L surname: DRUSANO fullname: DRUSANO, G. L organization: Division of Clinical Pharmacology, Albany Medical College, Albany, New York, United States – sequence: 2 givenname: S. L surname: PRESTON fullname: PRESTON, S. L organization: Division of Clinical Pharmacology, Albany Medical College, Albany, New York, United States – sequence: 3 givenname: C surname: HARDALO fullname: HARDALO, C organization: Schering Plough Research Institute, Kenilworth, New Jersey, United Kingdom – sequence: 4 givenname: R surname: HARE fullname: HARE, R organization: Schering Plough Research Institute, Kenilworth, New Jersey, United Kingdom – sequence: 5 givenname: C surname: BANFIELD fullname: BANFIELD, C organization: Schering Plough Research Institute, Kenilworth, New Jersey, United Kingdom – sequence: 6 givenname: D surname: ANDES fullname: ANDES, D organization: Division of Clinical Pharmacology, University of Wisconsin, Madison, Wisconsin, United States – sequence: 7 givenname: O surname: VESGA fullname: VESGA, O organization: Division of Clinical Pharmacology, University of Wisconsin, Madison, Wisconsin, United States – sequence: 8 givenname: W. A surname: CRAIG fullname: CRAIG, W. A organization: Division of Clinical Pharmacology, University of Wisconsin, Madison, Wisconsin, United States |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=915423$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/11120938$$D View this record in MEDLINE/PubMed |
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| Copyright | 2001 INIST-CNRS Copyright © 2001 American Society for Microbiology Copyright © 2001, American Society for Microbiology 2001 |
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| Keywords | Human Monte Carlo method Intravenous administration Oligosaccharide Rodentia Preclinical trial Normal In vitro Biological activity In vivo Vertebrata Antibiotic Mammalia Simulation Mouse Animal Minimum inhibitory concentration Antiinfectious Antibacterial agent Mathematical model Pharmacokinetics |
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| Notes | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 Corresponding author. Mailing address: Division of Clinical Pharmacology, Departments of Medicine and Pharmacology, Albany Medical College, 47 New Scotland Ave., Albany, NY 12208. Phone: (518) 262-6330. Fax: (518) 262-6333. E-mail: GLDRUSANO@AOL.COM. |
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| PublicationTitle | Antimicrobial Agents and Chemotherapy |
| PublicationTitleAbbrev | Antimicrob. Agents Chemother |
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| PublicationYear | 2001 |
| Publisher | American Society for Microbiology |
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Chemother., in press. – volume: 178 start-page: 360 year: 1998 end-page: 367 ident: B5 article-title: Factors influencing the emergence of resistance to indinavir: role of virologic, immunologic, and pharmacologic variables. publication-title: J. Infect. Dis. contributor: fullname: Holder, D. J. – volume: 45 start-page: 141 year: 1991 end-page: 157 ident: B15 article-title: Nonparametric EM algorithms for estimating prior distributions. publication-title: Appl. Math. Comput. contributor: fullname: Schumitzky, A. – volume: 35 start-page: 1413 year: 1991 end-page: 1422 ident: B7 article-title: Correlation between in vitro and in vivo activity of antimicrobial agents against gram-negative bacilli in a murine infection model. publication-title: Antimicrob. Agents Chemother. contributor: fullname: Craig, W. 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Reddit... One of the most challenging issues in the design of phase II/III clinical trials of antimicrobial agents is dose selection. The choice is often based on... |
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| SubjectTerms | Aminoglycosides Animals Anti-Bacterial Agents Anti-Bacterial Agents - administration & dosage Anti-Bacterial Agents - pharmacokinetics Anti-Bacterial Agents - pharmacology Antibacterial agents Antibiotics. Antiinfectious agents. Antiparasitic agents Area Under Curve Bacterial Infections - chemically induced Bacterial Infections - microbiology Biological and medical sciences Clinical Trials, Phase II as Topic Clinical Trials, Phase III as Topic Enterococcus faecalis Enterococcus faecium Evernimicin Experimental Therapeutics Gram-Positive Bacteria - drug effects Medical sciences Methicillin Resistance Mice Microbial Sensitivity Tests Monte Carlo Method Oligosaccharides - pharmacology Pharmacology. Drug treatments Protein Binding Staphylococcus aureus Staphylococcus aureus - drug effects Streptococcus pneumoniae |
| Title | Use of Preclinical Data for Selection of a Phase II/III Dose for Evernimicin and Identification of a Preclinical MIC Breakpoint |
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