Evidence map›Paper›PMID 41141489›Full record

ReviewFrontiers in nuclear medicine2025

Population pharmacokinetic modeling in radiopharmaceutical therapy: a review.

Deni Hardiansyah, Bisma Barron Patrianesha, Gerhard Glatting

Abstract readReview
In one paragraph

Review in Frontiers in nuclear medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Deni HardiansyahFaculty of Mathematics and Natural Sciences, Medical Physics and Biophysics Division, Physics Department, Universitas Indonesia, Depok, Indonesia.
Bisma Barron PatrianeshaResearch Center for Safety, Metrology, and Nuclear Quality Technology, National Research and Innovation Agency (BRIN), KST B.J. Habibie, Tangerang Selatan, Indonesia.
Gerhard GlattingMedical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Population pharmacokinetic (PopPK) has emerged as a robust framework for characterizing inter-individual variability in the absorbed dose estimates in radiopharmaceutical therapy (RPT). By enabling the analysis of biokinetic data from heterogeneous patient populations, PopPK allows individualized absorbed dose estimates while simultaneously leveraging population-level information. This review presents and evaluates the current applications of PopPK, such as nonlinear mixed-effects modeling (NLMEM) and Bayesian fitting methods in RPT, emphasizing its advantages over traditional individual-based modeling approaches. We summarize key studies that have implemented PopPK for modeling radiopharmaceutical biokinetics, with a focus on time-integrated activity (TIA) estimation, including single-time-point (STP) dosimetry, uncertainty analysis, as well as pharmacodynamic (PD) analysis. The flexibility of PopPK in handling sparse and irregularly sampled data makes it particularly relevant for clinical scenarios where comprehensive imaging schedules are impractical. However, despite its potential, the widespread adoption of PopPK in RPT remains limited due to challenges such as computational complexity and the need for specialized expertise. This review discusses critical aspects of PopPK implementation while emphasizing the importance of interdisciplinary collaboration in translating PopPK methodologies into clinical practice. Future directions include integrating PopPK into adaptive dosimetry frameworks and applying it in STP dosimetry and PD modeling to optimize treatment personalization. By providing a comprehensive overview of PopPK applications in RPT, this review aims to facilitate the integration of advanced modeling techniques into routine clinical workflows, ultimately supporting the development of accurate and precise RPTs.

Indexed as

NLMEMPKPDPOPPKRPTSTP

Identifiers

PMID41141489
PMCPMC12546074

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.