Converging Multi-Modal Intelligence: From Medical Imaging and Genomics to Causal Drug Discovery

Dear Colleagues,

The biomedical sciences are undergoing a radical transformation driven by the increasing availability and integration of multimodal data. These data modalities—ranging from medical imaging (e.g., MRI, CT, PET), genomics and transcriptomics to electronic health records (EHRs), pathology slides and even real-world evidence from wearable devices—hold immense potential for advancing both biological understanding and clinical applications.

The convergence of such heterogeneous data streams has paved the way for multimodal intelligence: a paradigm in which artificial intelligence (AI), machine learning (ML) and systems biology collaborate to extract deep, causally meaningful insights across biological and clinical contexts. By jointly analyzing these high-dimensional data sources, researchers can infer hidden mechanisms of disease, model disease progression and identify causal relationships that were previously obscured in single-modality approaches.

Particularly exciting is the opportunity to leverage this convergence for causal drug discovery and precision therapeutics. AI-powered models can now simulate patient-specific biological systems, predict responses to drug interventions and identify novel therapeutic targets through explainable and data-driven causal reasoning. This revolution is enabling the transition from observational correlation to causal inference and actionable insight, which is fundamental to the next generation of drug development pipelines.

What This Special Issue Covers

This Special Issue aims to bring together interdisciplinary research at the intersection of multimodal data integration, causal inference and computational drug discovery. We welcome submissions presenting:

• Novel algorithms or models for integrating multimodal data (e.g., imaging + omics, EHR + pathology)
• Causal modeling techniques applied to disease mechanism discovery or drug target prioritization
• Explainable AI systems for clinical diagnostics and therapeutic recommendations
• Applications of foundation models, digital twins or graph-based learning in biomedicine
• Large-scale pipelines for translating omics and imaging data into therapeutic hypotheses
• Clinical case studies or translational pipelines demonstrating real-world impact

Who Should Submit?

This Special Issue is ideal for researchers working in:

• Computational biology and bioinformatics
• Medical imaging and radiogenomics
• AI/ML in healthcare and drug development
• Systems pharmacology
• Precision medicine and translational research
• Biomedical knowledge representation (e.g., knowledge graphs, causal networks)

We encourage contributions from academia, industry and clinical research institutions, particularly those demonstrating cross-disciplinary impact and translational relevance.

Dr. Yingying Zhu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.