Evidence map›Paper›PMID 42216189›Full record

ArticleJournal of translational medicine2026

Aspiration to architecture: multi-omics, AI, digital twins, and blockchain for P4 medicine.

Alex E Mohr, Anil Bajnath, Gail King, Thomas E Ichim, Paniz Jasbi

Abstract read
In one paragraph

Article in Journal of translational 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

5 authors.

Alex E MohrSystems Precision Engineering and Advanced Research (SPEAR), Theriome Inc, Phoenix, AZ, USA.
Anil BajnathThe American Board of Precision Medicine, Wilmington, USA.
Gail KingSystems Precision Engineering and Advanced Research (SPEAR), Theriome Inc, Phoenix, AZ, USA.
Thomas E IchimImmorta Bio Inc., Miami, FL, USA.
Paniz JasbiSystems Precision Engineering and Advanced Research (SPEAR), Theriome Inc, Phoenix, AZ, USA. jasbi@therio.me.ORCID 0000-0002-2129-3098

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Two decades after its formalization, P4 medicine (predictive, preventive, personalized, participatory) remains more framework than practice. Most implementations stall at single-omics prediction and fail to close the loop across all four dimensions. In this Perspective, we argue that the P4 framework becomes actionable only when each pillar is anchored to a specific, implementable digital technology: multi-omics for prediction, artificial intelligence for prevention, digital twinning for personalization, and blockchain for participation. We propose a tiered multi-omics classification (Tier 1: genomics, measured once; Tier 2: epigenomics/proteomics, periodic; Tier 3: metabolomics/wearables, frequent) and present preliminary metabolomic aging data from 2,072 individuals identifying nine metabolites with linear age associations. We offer a computational definition of personalization requiring baseline state estimation, trajectory prediction, and counterfactual intervention simulation via stochastic digital twin engines. For the participatory pillar, we describe a blockchain architecture enabling patient-controlled data sovereignty and a health data marketplace. These four technologies form a reinforcing flywheel, where longitudinal patient participation enriches upstream data layers. We discuss validation challenges, regulatory gaps, equity concerns, and privacy risks that must be addressed before clinical deployment.

Indexed as

Artificial IntelligenceBlockchainMultiomicsPrecision MedicineDigital HealthGenomicsHumans

Identifiers

PMID42216189
PMCPMC13422370

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.