Evidence map›Paper›PMID 42812224›Full record

ArticleFrontiers in medicine2026

LAFOV PET as an enabling platform for pharmacokinetics-informed digital twins.

Bastian Rittmeyer, Matthew Strugari, Sophia Dietrich, Carla González-Avilés, Luis Martí-Bonmatí, Irene Torres Espallardo

Abstract read
In one paragraph

Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Bastian RittmeyerDepartment of Biology, Chemistry, and Pharmacy, Freie Universität Berlin, Berlin, Germany.
Matthew StrugariBiomedical Imaging Research Group (GIBI230), Instituto de Investigación Sanitaria La Fe (IIS La Fe), Valencia, Spain.
Sophia DietrichBiomedical Imaging Research Group (GIBI230), Instituto de Investigación Sanitaria La Fe (IIS La Fe), Valencia, Spain.
Carla González-AvilésBiomedical Imaging Research Group (GIBI230), Instituto de Investigación Sanitaria La Fe (IIS La Fe), Valencia, Spain.
Luis Martí-BonmatíBiomedical Imaging Research Group (GIBI230), Instituto de Investigación Sanitaria La Fe (IIS La Fe), Valencia, Spain.
Irene Torres EspallardoBiomedical Imaging Research Group (GIBI230), Instituto de Investigación Sanitaria La Fe (IIS La Fe), Valencia, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital twins (DTs) have emerged as a promising framework for precision medicine and are a key part of current initiatives to digitalize and innovate the healthcare sector. Medical DTs have shown potential to support more effective and efficient patient care, reduce healthcare costs, and enable novel approaches in drug development. Currently, DTs are primarily informed by structural imaging modalities, genetic information, clinical history, and lifestyle factors. These anatomy-driven twins can capture, for example, tumor burden and morphology in cancer, but lack the pharmacological dimension that ultimately shapes response and toxicity. Long axial field-of-view (LAFOV) PET systems now provide a platform capable of measuring dynamic tracer distribution across all major organs within a single examination, thereby enabling pharmacokinetic (PK) studies that could fill the current gap in DT concepts. The extended axial field of view and the resulting high sensitivity enable comprehensive characterization of patient-specific organ kinetics, potentially advancing DTs for preventive and personalized medicine. In this Perspective article, we discuss how LAFOV PET could complement population-based PK modeling and facilitate the development of PK-informed DTs. We explore its potential implications for selected clinical applications and aspects of drug development. Additionally, we discuss current limitations and outline steps required to translate PK-informed DTs into decision-grade tools for clinical use.

Indexed as

digital twinsLAFOV PETmolecular imagingpharmacokineticsphysiologically based pharmacokinetic modeling

Identifiers

PMID42812224
PMCPMC13619403

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Registered trials

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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.