Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Bayesian nonparametric inference on the dose level with specified response rate.

S Mukhopadhyay1

  • 1Merck Research Laboratories, Rahway, New Jersey, USA. saurabh_mukhopadhyay@merck.com

Biometrics
|April 28, 2000
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Alignment in yrast structure and negative-parity sideband in the proton-rich nucleus [Formula: see text]Sm.

Scientific reports·2026
Same author

Skin barrier-related genes in childhood atopic dermatitis, asthma, and allergy: A systematic review and meta-analysis.

Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology·2026
Same author

ADRB2 genotype-guided treatment for childhood asthma: Cost analysis of the PUFFIN and PACT trials.

Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology·2025
Same author

Ameloblastic fibroma and BRAF V600E immunohistochemistry staining pattern: case report and review of a rare entity.

International journal of oral and maxillofacial surgery·2025
Same author

Wavelet transform of autoradiographs: Analysis of MOX fuel heterogeneity.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine·2024
Same author

Measurement of energy and directional distribution of neutron ambient dose equivalent for the <sup>7</sup>Li(p,n)<sup>7</sup>Be reaction.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine·2023
Same journal

Acknowledgment of Referees 2025.

Biometrics·2026
Same journal

Fast penalized generalized estimating equations for large longitudinal functional datasets.

Biometrics·2026
Same journal

Causally-interpretable random-effects meta-analysis.

Biometrics·2026
Same journal

Statistical inference for mean function of partially observed functional time series.

Biometrics·2026
Same journal

Subgroup identification via Interaction Tree and Mixed Model for Repeated Measures with application to Alzheimer's disease.

Biometrics·2026
Same journal

Finite mixtures of linear quantile regressions with concomitant variables: a solution to endogeneity in longitudinal data modeling.

Biometrics·2026
See all related articles

This study introduces a new nonparametric Bayesian inference method for dose-finding studies, enabling accurate estimation of toxicity and efficacy dose levels. The approach utilizes Dirichlet process priors for improved percentile inference and potency curve estimation.

Area of Science:

  • Statistics
  • Biostatistics
  • Pharmacometrics

Background:

  • Nonparametric Bayesian models offer flexibility but lack methods for percentile inference in dose-finding.
  • Dose-finding studies require precise inference on dose levels linked to specific toxicity or efficacy rates.
  • Existing methods struggle with nonparametric Bayesian inference on percentiles crucial for these studies.

Purpose of the Study:

  • To develop and present a novel nonparametric Bayesian inference methodology for dose-finding studies.
  • To address the limitations in inferring percentiles within Bayesian frameworks for dose-finding.
  • To enable accurate estimation of unknown dose levels corresponding to prespecified rates.

Main Methods:

  • Derivation of theoretical results for nonparametric Bayesian inference on percentiles using Dirichlet process priors.

Related Experiment Videos

  • Development of numerical implementation strategies for the proposed theoretical framework.
  • Application of the method to estimate the entire potency curve.

    • Main Results:

    • Successful derivation of nonparametric Bayesian inference for unknown dose levels.
    • Efficient estimation of the complete potency curve is achieved.
    • The methodology is validated through a practical experimental data example.

    Conclusions:

    • The proposed nonparametric Bayesian approach effectively handles percentile inference in dose-finding studies.
    • This methodology provides a robust framework for estimating dose-response relationships and potency.
    • The approach offers a valuable tool for pharmaceutical research and clinical trial design.