Integrative omics in translational pharmacology: A target‐credibility framework for biomarker‐guided therapy
- 1Department of Orthopedics The Second Affiliated Hospital of Hainan Medical University Haikou Hainan China
- 2Diabetes Research Center, Qatar Biomedical Research Institute Hamad Bin Khalifa University Doha Qatar
- 3Department of Medical Laboratory Sciences Chabahar University of Medical Sciences Chabahar Iran
Abstract
Background Drug discovery remains costly and failure‐prone because molecular associations do not necessarily translate into therapeutically actionable hypotheses. Integrative omics can connect disease biology with target nomination, functional validation, pharmacological assessment, patient stratification and biomarker‐guided therapy. Methods This narrative review was informed by iterative, topic‐guided searches of PubMed, Scopus, Web of Science, ScienceDirect and Google Scholar, updated through September 2026. Searches focused on multi‐omics, target validation, pharmacological assessment, biomarker development and clinical translation. Primary experimental and clinical studies, methodological publications, regulatory guidance and relevant reviews were selected according to their contribution to these topics. No formal risk‐of‐bias assessment or quantitative meta‐analysis was performed. Results The synthesis indicates that genomic and pharmacogenomic evidence supports causal inference and therapeutic directionality; transcriptomic and epigenomic data define dynamic disease states; proteomic and chemoproteomic approaches assess protein function, target engagement and pathway modulation; and metabolomic, lipidomic, single‐cell and spatial approaches provide biochemical, cellular and tissue‐resolved evidence. We propose a multidomain, gate‐based target‐credibility framework that distinguishes causal relevance, biological context, functional validation, tractability, target engagement, pharmacodynamic response, safety, biomarker readiness and clinical implementation. The framework links convergent, unresolved and contradictory evidence to go, refine or stop decisions. Conclusion Integrative omics is most useful when guided by explicit therapeutic questions, intervention‐oriented study designs, independent validation, analytically robust biomarkers and regulatory readiness. The framework is a proposed qualitative decision aid and has not been clinically validated to predict clinical success.
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BibTeX
@article{altahla2026integrative,
title = {{Integrative omics in translational pharmacology: A target‐credibility framework for biomarker‐guided therapy}},
author = {Ruba Altahla and Zhaowei Wang and Shan‐Jie Rong and Chaoyi Li and Nasir Jadgal and Mohammad Javad Mehran and Mansoor Bolideei and Jamal Alshorman},
journal = {Clinical and Translational Discovery},
year = {2026},
month = oct,
doi = {10.1002/ctd2.70223},
url = {https://doi.org/10.1002/ctd2.70223},
note = {CC BY},
}
RIS
TY - JOUR
TI - Integrative omics in translational pharmacology: A target‐credibility framework for biomarker‐guided therapy
AU - Ruba Altahla
AU - Zhaowei Wang
AU - Shan‐Jie Rong
AU - Chaoyi Li
AU - Nasir Jadgal
AU - Mohammad Javad Mehran
AU - Mansoor Bolideei
AU - Jamal Alshorman
PY - 2026
DA - 2026/10/26
JO - Clinical and Translational Discovery
DO - 10.1002/ctd2.70223
UR - https://doi.org/10.1002/ctd2.70223
AB - Background Drug discovery remains costly and failure‐prone because molecular associations do not necessarily translate into therapeutically actionable hypotheses. Integrative omics can connect disease biology with target nomination, functional validation, pharmacological assessment, patient stratification and biomarker‐guided therapy. Methods This narrative review was informed by iterative, topic‐guided searches of PubMed, Scopus, Web of Science, ScienceDirect and Google Scholar, updated through September 2026. Searches focused on multi‐omics, target validation, pharmacological assessment, biomarker development and clinical translation. Primary experimental and clinical studies, methodological publications, regulatory guidance and relevant reviews were selected according to their contribution to these topics. No formal risk‐of‐bias assessment or quantitative meta‐analysis was performed. Results The synthesis indicates that genomic and pharmacogenomic evidence supports causal inference and therapeutic directionality; transcriptomic and epigenomic data define dynamic disease states; proteomic and chemoproteomic approaches assess protein function, target engagement and pathway modulation; and metabolomic, lipidomic, single‐cell and spatial approaches provide biochemical, cellular and tissue‐resolved evidence. We propose a multidomain, gate‐based target‐credibility framework that distinguishes causal relevance, biological context, functional validation, tractability, target engagement, pharmacodynamic response, safety, biomarker readiness and clinical implementation. The framework links convergent, unresolved and contradictory evidence to go, refine or stop decisions. Conclusion Integrative omics is most useful when guided by explicit therapeutic questions, intervention‐oriented study designs, independent validation, analytically robust biomarkers and regulatory readiness. The framework is a proposed qualitative decision aid and has not been clinically validated to predict clinical success.
SN - 2768-0622
ER -