Evidence map›Paper›PMID 41514518›Full record

ReviewCancers2025

Pharmacokinetic and Pharmacodynamic Modeling of Antibody-Drug Conjugates.

Patrick M Glassman

Abstract readReview
In one paragraph

Review in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. From Payload-First Toward Dual-Mechanism Antibody-Drug Conjugates.Advanced materials (Deerfield Beach, Fla.) · 2026
    Article
  2. Review
  3. Review
  4. Review
  5. Review
  6. 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

1 author.

Patrick M GlassmanDepartment of Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, PA 19140, USA.ORCID 0000-0003-3786-0437

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibody-drug conjugates (ADCs) have risen in prominence over the past 15 years, with numerous regulatory approvals in oncology. A complicating factor in the development of ADCs is the presence of numerous analytes with unique pharmacologic properties. Following administration, ADCs are present in the body as the intact ADC, unconjugated antibody, and liberated payload. Due to heterogeneity in conjugation and in vivo deconjugation rates, the drug-to-antibody ratio (DAR) changes with time. Each of these molecular species has unique pharmacokinetic (PK) and pharmacodynamic (PD) properties that should be understood and characterized. One approach that is frequently applied is the development of in silico mathematical models to characterize and predict the PK/PD of ADCs. In this review, we summarize key mechanisms controlling the PK/PD of ADCs. This provides context for a detailed discussion of the array of PK/PD models that have been applied for ADCs, ranging from empirical compartmental models all the way through system-level models, such as physiologically based pharmacokinetics (PBPK) and cell-level PK/PD models. We provide a critical discussion of the strengths, weaknesses, and utility of each of these model structures.

Indexed as

antibody-drug conjugatespharmacodynamicspharmacokineticsPK/PD modeling

Identifiers

PMID41514518
PMCPMC12785113

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.