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  1. Article ; Online: Thoughts on plagiarism and the case against Claudine Gay.

    Bonate, Peter L

    Journal of pharmacokinetics and pharmacodynamics

    2024  Volume 51, Issue 1, Page(s) 1–4

    MeSH term(s) Humans ; Plagiarism ; Sexual and Gender Minorities
    Language English
    Publishing date 2024-02-15
    Publishing country United States
    Document type Editorial
    ZDB-ID 2041601-5
    ISSN 1573-8744 ; 1567-567X
    ISSN (online) 1573-8744
    ISSN 1567-567X
    DOI 10.1007/s10928-024-09904-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Changes in Associate Editors at the Journal of Pharmacokinetics and Pharmacodynamics.

    Bonate, Peter L

    Journal of pharmacokinetics and pharmacodynamics

    2023  Volume 50, Issue 1, Page(s) 3

    Language English
    Publishing date 2023-01-25
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2041601-5
    ISSN 1573-8744 ; 1567-567X
    ISSN (online) 1573-8744
    ISSN 1567-567X
    DOI 10.1007/s10928-023-09843-1
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  3. Article ; Online: The role of quantitative systems pharmacology in pharmacometrics and the scope of the journal.

    Bonate, Peter L

    Journal of pharmacokinetics and pharmacodynamics

    2023  Volume 50, Issue 1, Page(s) 1–2

    MeSH term(s) Network Pharmacology ; Pharmacology, Clinical ; Models, Biological ; Pharmacology
    Language English
    Publishing date 2023-01-31
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2041601-5
    ISSN 1573-8744 ; 1567-567X
    ISSN (online) 1573-8744
    ISSN 1567-567X
    DOI 10.1007/s10928-023-09844-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Editor's note on the themed issue: integration of machine learning and quantitative systems pharmacology.

    Bonate, Peter L

    Journal of pharmacokinetics and pharmacodynamics

    2022  Volume 49, Issue 1, Page(s) 1–3

    MeSH term(s) Machine Learning ; Network Pharmacology
    Language English
    Publishing date 2022-01-18
    Publishing country United States
    Document type Editorial
    ZDB-ID 2041601-5
    ISSN 1573-8744 ; 1567-567X
    ISSN (online) 1573-8744
    ISSN 1567-567X
    DOI 10.1007/s10928-022-09803-1
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  5. Book: Pharmacokinetic pharmacodynamic modeling and simulation

    Bonate, Peter L.

    (Biomedicine)

    2011  

    Title variant Pharmacokinetic-pharmacodynamic modeling and simulation
    Author's details Peter L. Bonate
    Series title Biomedicine
    Keywords Pharmacology ; Pharmakokinetik ; Mathematisches Modell ; Pharmakodynamik
    Subject Klinische Pharmakokinetik ; Toxikokinetik
    Language English
    Size XIX, 618 S. : Ill., graph. Darst.
    Edition 2. ed.
    Publisher Springer
    Publishing place New York u.a.
    Publishing country United States
    Document type Book
    HBZ-ID HT016907823
    ISBN 978-1-4419-9484-4 ; 9781441994851 ; 1-4419-9484-X ; 1441994858
    Database Catalogue ZB MED Medicine, Health

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    Shelf markLoan statusLocation
    2011 A 2751 order for loan Magazin

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  6. Article ; Online: Correction to: QTc interval analysis-an ever-evolving endeavor.

    Bonate, Peter L

    Journal of pharmacokinetics and pharmacodynamics

    2021  Volume 48, Issue 3, Page(s) 445

    Language English
    Publishing date 2021-04-22
    Publishing country United States
    Document type Published Erratum
    ZDB-ID 2041601-5
    ISSN 1573-8744 ; 1567-567X
    ISSN (online) 1573-8744
    ISSN 1567-567X
    DOI 10.1007/s10928-021-09756-x
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  7. Article ; Online: QTc interval analysis-an ever-evolving endeavor.

    Bonate, Peter L

    Journal of pharmacokinetics and pharmacodynamics

    2021  Volume 48, Issue 2, Page(s) 183–186

    MeSH term(s) Dose-Response Relationship, Drug ; Drug Approval ; Drug Recalls ; Electrocardiography/drug effects ; Humans ; Long QT Syndrome/chemically induced ; Long QT Syndrome/diagnosis ; Models, Biological ; Software ; Terfenadine/adverse effects ; Terfenadine/pharmacokinetics
    Chemical Substances Terfenadine (7BA5G9Y06Q)
    Language English
    Publishing date 2021-04-07
    Publishing country United States
    Document type Editorial
    ZDB-ID 2041601-5
    ISSN 1573-8744 ; 1567-567X
    ISSN (online) 1573-8744
    ISSN 1567-567X
    DOI 10.1007/s10928-021-09754-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Pharmacokinetic comparability between two populations using nonlinear mixed effect models: a Monte Carlo study.

    Sahasrabudhe, Siddhee A / Bonate, Peter L

    Journal of pharmacokinetics and pharmacodynamics

    2023  Volume 50, Issue 3, Page(s) 189–201

    Abstract: Are two populations the same or are they different' is a question that is often faced in clinical pharmacology trials e.g., a pharmacokinetic trial studying a particular drug in racially different groups. To address this question, concentration-time ... ...

    Abstract 'Are two populations the same or are they different' is a question that is often faced in clinical pharmacology trials e.g., a pharmacokinetic trial studying a particular drug in racially different groups. To address this question, concentration-time data were simulated from a reference and test population, where in the latter the clearance, sample size, and sampling design were systematically varied. It was of interest to determine whether the estimates of clearance from the two groups were the same or different. Two approaches were used to estimate the empirical Bayes estimates (EBEs) for clearance. One approach developed a population pharmacokinetic model for the reference population and the EBEs for the reference population were estimated from this model. The parameters of the reference population were fixed to their maximum likelihood estimates. The model was then applied to the test population dataset to estimate the EBEs of the test population using the MAXEVAL = 0 option in NONMEM. A second approach, the theta approach, combined the reference and test datasets into a single dataset and used population as a covariate in the model; the EBEs were estimated from this combined model. The power and type I error rate of each approach were calculated for each treatment combination using a variety of statistical tests to determine whether there was a difference in the distribution of the EBEs in the reference population compared to the test population. Our results suggest that either MAXEVAL or theta approaches can be used with informative sampling designs. In addition to reasonable power and type I error, both approaches gave almost identical results under a dense sampling design. To statistically compare the distribution of EBEs of pharmacokinetic parameters from a reference group to that of a test group, a T-test and DTS eCDF test are equally useful.
    MeSH term(s) Bayes Theorem ; Kinetics ; Likelihood Functions ; Monte Carlo Method ; Sample Size ; Models, Biological
    Language English
    Publishing date 2023-01-28
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2041601-5
    ISSN 1573-8744 ; 1567-567X
    ISSN (online) 1573-8744
    ISSN 1567-567X
    DOI 10.1007/s10928-023-09842-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: On the shoulders of giants….

    Bonate, Peter L

    Journal of pharmacokinetics and pharmacodynamics

    2020  Volume 47, Issue 1, Page(s) 1

    MeSH term(s) History, 21st Century ; Humans ; Pharmacokinetics ; Publications/history
    Language English
    Publishing date 2020-01-20
    Publishing country United States
    Document type Editorial ; Historical Article
    ZDB-ID 2041601-5
    ISSN 1573-8744 ; 1567-567X
    ISSN (online) 1573-8744
    ISSN 1567-567X
    DOI 10.1007/s10928-020-09674-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Musings on the current state of COVID-19 modeling and reporting.

    Bonate, Peter L

    Journal of pharmacokinetics and pharmacodynamics

    2020  Volume 47, Issue 3, Page(s) 183–185

    MeSH term(s) Betacoronavirus ; COVID-19 ; Coronavirus Infections/epidemiology ; Humans ; Models, Statistical ; Pandemics ; Pneumonia, Viral/epidemiology ; SARS-CoV-2
    Keywords covid19
    Language English
    Publishing date 2020-05-28
    Publishing country United States
    Document type Editorial
    ZDB-ID 2041601-5
    ISSN 1573-8744 ; 1567-567X
    ISSN (online) 1573-8744
    ISSN 1567-567X
    DOI 10.1007/s10928-020-09692-2
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