Clinical OMICS for Drug Discovery and Personalized Medicine

Background

Modern clinical medicine requires high-throughput molecular profiling to understand disease heterogeneity, therapeutic resistance, and patient-specific responses. While genomics has established foundational diagnostic frameworks, execution in biological systems is governed by functional molecules like proteins and metabolites. Advanced mass spectrometry, clinical proteomics, and multi-omics have emerged as essential technologies for identifying functional biomarkers and druggable protein targets. However, translating multi-omics data from research labs to routine clinical decision-making remains challenging and require stronger collaborative bridges between bench scientists and practicing physicians. This symposium will bring together medical practitioners, clinical researchers, bioinformaticians, and proteomics/ multi-omics scientists onto a unified platform to address pressing diagnostic and therapeutic challenges. The symposium, which serves as a specialized session of the 5th International Conference on Modern Medicine and Global Health (ICMMGH 2027), will focus on clinical medicine and drug.

Goal/Rationale

Translational Bridge-Building: Interaction and discussion of clinicians (oncology, cardiology, infectious diseases) with omics scientists to map clinical needs to multi- omics workflows.

Hands-on Clinical Proteomics Sessions: Laboratory demonstrations covering clinical applications for sample preparation, high-resolution 4D-proteomics & mass spectrometry, clinical metabolomics, and data analysis.

Target Discovery & Drug Repurposing: Interactive discussion focused on functional proteoforms to identify novel drug targets, validation techniques for therapeutics, and tailor personalized treatment protocols.

Roadmap Formulation: Brainstorming to create collaborative networks and draft action plans for clinician-led multi-omics studies leading towards “Omics for Clinics”.

Scope

The symposium presentations and discussions would cover:

1. Clinical mass spectrometry, 4D-Omics and target discovery in oncology, and metabolic disorders.
2. Biomarker validation and standardized sample processing for clinical trials.
3. Integration of bio-AI, machine learning, and multi-omics data for precision diagnostics.
4. Translational challenges in converting proteomic discoveries into bedside therapeutic interventions.