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Updated: Feb 26, 2026

In Silico Clinical Trials for Cardiovascular Disease
Published on: May 27, 2022
From polygenic risk to digital twins: the future of personalised cardiovascular medicine
Ibrahim Antoun1,2, Alkassem Alkhayer3, Ahmed Abdelrazik1
1Department of Cardiology, University Hospitals of Leicester NHS Trust, Glenfield Hospital, Leicester, United Kingdom.
Insights
Precision cardiology offers personalized cardiovascular disease (CVD) care by integrating genomics, multi-omics, and AI. This approach aims to improve risk prediction, diagnosis, and treatment strategies for better patient outcomes.
Area of Science:
- Cardiovascular Medicine
- Genomics
- Computational Biology
Background:
- Cardiovascular disease (CVD) is a leading global health burden.
- Current generalized approaches inadequately address individual variability in CVD risk, progression, and treatment response.
- Precision cardiology leverages advanced technologies for individualized patient care.
Purpose of the Study:
- To review advances in precision cardiology across genomic, omics, digital, and therapeutic domains.
- To discuss translational gaps and implementation challenges in personalized cardiovascular medicine.
- To highlight the potential of precision cardiology to redefine CVD prevention, diagnosis, and treatment.
Main Methods:
- Review of current literature on genomic, multi-omics, and computational approaches in cardiovascular medicine.
- Analysis of advances in polygenic risk scores, pharmacogenomics, and AI/machine learning applications.
- Synthesis of emerging technologies like gene editing and digital twins.
Main Results:
- Polygenic risk scores enhance population-level cardiovascular risk stratification.
- Multi-omics platforms provide deeper insights into CVD pathophysiology and biomarkers.
- Pharmacogenomics guides personalized cardiovascular drug selection and dosing.
- AI and machine learning improve predictive modeling using diverse data sources.
- Emerging technologies promise further advancements in personalized cardiovascular care.
Conclusions:
- Precision cardiology holds significant potential to shift from reactive to proactive, patient-specific cardiovascular care.
- Implementation challenges include regulatory, data integration, cost, and equity concerns.
- Multidisciplinary collaboration, robust validation, and equitable infrastructure are crucial for clinical translation.
Abstract:
Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide. Traditional risk assessment and treatment approaches often follow generalised strategies that inadequately capture individual variability in disease susceptibility, progression, and therapeutic response. Precision cardiology seeks to overcome these limitations by leveraging genomic, molecular, and computational innovations to enable more individualised care. Advances in polygenic risk scores have improved our ability to stratify cardiovascular risk at a population level, though challenges remain in ensuring clinical utility across diverse populations. Integrating multi-omics platforms, including transcriptomics, proteomics, and metabolomics, offers a more comprehensive understanding of CVD pathophysiology and potential diagnostic or prognostic biomarkers. Pharmacogenomic insights increasingly guide the selection and dosing of cardiovascular therapies such as statins and antiplatelets, supporting the shift toward personalised pharmacologic strategies. Applying artificial intelligence and machine learning to cardiovascular imaging, electronic health records, and wearable data enables more accurate, scalable predictive models. Emerging technologies, including CRISPR-based gene editing, single-cell sequencing, and digital twin modelling, further expand the frontiers of personalised cardiovascular medicine. However, real-world implementation remains limited by regulatory uncertainty, data integration challenges, cost, and concerns about equity and access. This review synthesises advances across genomic, omics, digital, and therapeutic domains in cardiovascular precision medicine, discusses key translational gaps, and highlights ethical and implementation challenges. We emphasise the need for multidisciplinary collaboration, robust validation frameworks, and equitable infrastructure to ensure these innovations lead to meaningful clinical impact. Personalised cardiology is poised to redefine prevention, diagnosis, and treatment paradigms as the field matures, moving from reactive care to proactive, patient-specific strategies.
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