Evidence map›Paper›PMID 39008243›Full record

SynthesisClinical pharmacokinetics2024

Can we Predict Drug Excretion into Saliva? A Systematic Review and Analysis of Physicochemical Properties.

Thi A Nguyen, Ricky H Chen, Bryson A Hawkins, David E Hibbs, Hannah Y Kim, Nial J Wheate, Paul W Groundwater, Sophie L Stocker, Jan-Willem C Alffenaar

Abstract readSystematic Review
In one paragraph

Synthesis in Clinical pharmacokinetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Interpol review of forensic toxicology, 2023-2025.Forensic science international. Synergy · 2026
    Review
  3. Article
  4. Article
  5. Review
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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

9 authors.

Thi A NguyenSydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Pharmacy Building (A15), Sydney, NSW, 2006, Australia. thi.a.nguyen@sydney.edu.au.ORCID 0000-0002-8508-8990
Ricky H ChenSydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Pharmacy Building (A15), Sydney, NSW, 2006, Australia.
Bryson A HawkinsSydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Pharmacy Building (A15), Sydney, NSW, 2006, Australia.
David E HibbsSydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Pharmacy Building (A15), Sydney, NSW, 2006, Australia.
Hannah Y KimSydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Pharmacy Building (A15), Sydney, NSW, 2006, Australia.
Nial J WheateSchool of Natural Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, NSW, Australia.
Paul W GroundwaterSydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Pharmacy Building (A15), Sydney, NSW, 2006, Australia.
Sophie L Stocker *Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Pharmacy Building (A15), Sydney, NSW, 2006, Australia.
Jan-Willem C Alffenaar *Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Pharmacy Building (A15), Sydney, NSW, 2006, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesSaliva is a patient-friendly matrix for therapeutic drug monitoring (TDM) but is infrequently used in routine care. This is due to the uncertainty of saliva-based TDM results to inform dosing. This study aimed to retrieve data on saliva-plasma concentration and subsequently determine the physicochemical properties that influence the excretion of drugs into saliva to increase the foundational knowledge underpinning saliva-based TDM.

methodsMedline, Web of Science and Embase (1974-2023) were searched for human clinical studies, which determined drug pharmacokinetics in both saliva and plasma. Studies with at least ten subjects and five paired saliva-plasma concentrations per subject were included. For each study, the ratio of the area under the concentration-time curve between saliva and plasma was determined to assess excretion into saliva. Physicochemical properties of each drug (e.g. pKa, lipophilicity, molecular weight, polar surface area, rotatable bonds and fraction of drug unbound to plasma proteins) were obtained from PubChem and Drugbank. Drugs were categorised by their ionisability, after which saliva-to-plasma ratios were predicted with adjustment for protein binding and physiological pH via the Henderson-Hasselbalch equation. Spearman correlation analyses were performed for each drug category to identify factors predicting saliva excretion (α = 5%). Study quality was assessed by the risk of bias in non-randomised studies of interventions tool.

resultsOverall, 42 studies including 40 drugs (anti-psychotics, anti-microbials, immunosuppressants, anti-thrombotic, anti-cancer and cardiac drugs) were included. The median saliva-to-plasma ratios were similar for drugs in the amphoteric (0.59), basic (0.43) and acidic (0.41) groups and lowest for drugs in the neutral group (0.21). Higher excretion of acidic drugs (n = 5) into saliva was associated with lower ionisation and protein binding (correlation between predicted versus observed saliva-to-plasma ratios: R

conclusionsMany commonly used drugs are excreted into saliva, which can be partly predicted by a drug's ionisation state, protein binding, lipophilicity, hydrogen bond donor count and polar surface area. The contribution of drug transporters and physiological factors to the excretion needs to be evaluated. Continued research on drugs potentially suitable for saliva-based TDM will aid in adopting this person-centred TDM approach to improve patient outcomes.

Indexed as

SalivaDrug MonitoringHumansPharmaceutical PreparationsProtein BindingPharmaceutical Preparations

Identifiers

PMID39008243
PMCPMC11343830

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.