Evidence map›Paper›PMID 42042549›Full record

ReviewJournal of personalized medicine2026

New Personalized Medicine Model for Medication Management.

Kannayiram Alagiakrishnan, Tyler Halverson, Desiree Virginia Fermin Olivares, Cheryl A Sadowski

Abstract readReview
In one paragraph

Review in Journal of personalized medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 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

4 authors.

Kannayiram AlagiakrishnanDivision of Geriatric Medicine, University of Alberta, 11350-83 Ave, Edmonton, AB T6G 2P4, Canada.ORCID 0000-0003-1444-2451
Tyler HalversonChild and Adolescent Mental Health Services, Trillium Health Partners-Credit Valley Hospital, Mississauga, ON L5M 2N1, Canada.ORCID 0000-0001-5841-7659
Desiree Virginia Fermin OlivaresCollege of Pharmacy, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0009-0008-7128-8220
Cheryl A SadowskiFaculty of Pharmacy & Pharmaceutical Sciences, University of Alberta, Edmonton, AB T6G 2H1, Canada.ORCID 0000-0002-4526-7054

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When using traditional approaches, such as pharmacokinetics and pharmacodynamics, the entire cellular or molecular response to drugs in the body cannot be fully ascertained or established. The oral medication process involves pharmacokinetics, followed by oral microbiomics and then gut microbiomics and pharmacodynamics. Recently, there has been increasing interest in the role of genetics (pharmacogenetics and pharmacogenomics) in both humans and microbiomes, as well as omics alterations (e.g., epigenetic, transcriptomic, proteomic, and metabolomic alterations as a consequence of drug exposure), which can help to ascertain the cellular responses to medications. Both the efficacy and toxicity of a drug are influenced by these factors. To assess these at an individual level, an integrative Personalized Medicine Model may be needed to help with medication management. Two example application cases for SSRIs and statins demonstrate the clinical usefulness of such a model, which can guide clinicians during drug selection and dosing to reduce reliance on trial-and-error, thus potentially improving patient outcomes and safety. Integrating this framework into practical clinical workflows requires the capture, analysis, and translation of multi-omics data in order to realize decision support protocols and actionable drug recommendations. This review also discusses IT requirements and different stakeholder roles. Although the proposed model can guide the treatment of diseases at the individual patient level, further research is still needed before it can be implemented as part of drug development research, clinical care, and healthcare delivery systems.

Indexed as

computational biologymicrobiomepharmacodynamicspharmacogeneticspharmacokineticspharmacomicrobiomicspharmacomulti-omics

Identifiers

PMID42042549
PMCPMC13117434

What Socratic 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 Socratic graph.