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Center for AI-Based Precision Control of Hematologic Malignancies

Pioneering the Future of Hematologic Cancer Precision Medicine through AI–Bio Convergence

KEYWORDKeyword

AI for Science Multimodal AI Drug Discovery SynBio Digital Health

OBJECTIVE Objective

Establishing a Full-Cycle Hematologic Cancer Precision Medicine Platform
that Connects AI-Based Disease Interpretation with Biological Mechanism Validation.
The goal of the Research Unit is to precisely define the disease progression processes of
hematologic malignancies by integrating AI-based data analysis, gene network interpretation,
biological mechanism validation, therapeutic target discovery, and preclinical evaluation into a unified research workflow.
To achieve this goal, the Unit will leverage large-scale patient multi-omics and
clinical datasets to identify core disease-associated signals and gene regulatory networks underlying hematologic cancers.
AI modeling will then be used to develop patient stratification models capable of predicting diagnosis,
prognosis, relapse risk, and therapeutic response.
In parallel, candidate targets derived from these analyses will be functionally validated in cellular systems,
patient-derived models, and animal models, thereby establishing a target-driven therapeutic foundation
that can be translated into practical treatment strategies.
Ultimately, the Research Unit aims to establish an integrated precision medicine research framework
for hematologic cancers by organically connecting gene network analysis, AI modeling, experimental validation,
and preclinical evaluation, thereby linking diagnosis, prediction, and therapy within a single translational platform.

INTRODUCTION Director's Message

Greetings.
I am Hongtae Kim, Director of the Center for AI-Based Precision Control of Hematologic Malignancies Unit.

The AI-Based Hematologic Cancer Precision Medicine Research Unit was established to
elucidate the complex gene regulatory networks and disease progression principles underlying
hematologic malignancies, and to build a next-generation precision medicine platform in which diagnosis,
prediction, and therapy are seamlessly integrated.

Hematologic cancers are among the most challenging diseases to treat, characterized
by substantial molecular heterogeneity among patients, frequent relapse, and therapeutic resistance.
Therefore, conventional single-target approaches are often insufficient to fully explain
the complexity of these diseases or the diverse treatment responses observed across patients.
Recent advances in artificial intelligence, multi-omics, single-cell analysis,
and advanced disease modeling technologies now provide a transformative opportunity
to understand and predict hematologic cancers with unprecedented precision.

Our Research Unit aims to establish an integrated convergence research framework
that brings together AI-based data analysis, gene network interpretation,
biological mechanism studies, therapeutic target discovery, innovative drug
and cell therapy development, and preclinical validation.
Through this approach, we seek to precisely interpret the temporal evolution
and inter-patient heterogeneity of hematologic cancers and translate these insights
into mechanism-based diagnostic technologies and personalized therapeutic strategies.

In particular, our Research Unit places a strong emphasis on a creative and
independent postdoctoral researcher-centered research environment.
We will support young investigators from diverse disciplines—including AI, omics,
cell biology, hematologic cancer biology, therapeutic development, and preclinical research—to work collaboratively,
identify new scientific questions, and generate world-class research outcomes.

The AI-Based Hematologic Cancer Precision Medicine Research Unit is committed
to providing new diagnostic and therapeutic opportunities for patients with hematologic cancers
and to contributing to Korea’s leadership in global AI–Bio precision medicine.
We will also foster the next generation of convergence research leaders and
build a sustainable research ecosystem capable of driving future innovations in biomedicine.

Thank you.

Hongtae Kim, Ph.D. Director, Center for AI-Based Precision Control of Hematologic Malignancies

IMPACT Impact

The AI-Based Hematologic Cancer Precision Medicine Research Unit aims to< establish a full-cycle research platform that integrates AI-powered multi-omics analysis with biological mechanism studies to elucidate the fundamental principles underlying the initiation, progression, relapse, and therapeutic resistance of hematologic cancers. By connecting these discoveries to precision diagnosis, prognostic prediction, and targeted therapeutic strategies, the Unit seeks to accelerate the translation of scientific insights into clinical and industrial innovations.

by systematically defining the complex gene regulatory networks and disease-driving axes of hematologic malignancies, the Research Unit will uncover previously unexplained biological mechanisms of relapse and therapeutic resistance and facilitate the discovery of novel therapeutic targets.

the development of AI-based patient stratification models and ultra-sensitive diagnostic panels will provide a foundation for more precise prediction of disease status, prognosis, relapse risk, and therapeutic response in individual patients. This will contribute to the implementation of personalized treatment strategies and help reduce unnecessary therapeutic burden.

by developing novel targeted therapies and next-generation cell therapy strategies, the Research Unit will propose new therapeutic options for refractory hematologic cancers and strengthen the competitiveness of Korea’s biomedical and healthcare industries in drug discovery, therapeutic development, and technology commercialization.

the establishment of a preclinical validation system using patient-derived models and animal models will accelerate the translation of basic research discoveries into clinically applicable therapeutic technologies.

by creating a postdoctoral researcher-centered AI–Bio convergence research environment, the Unit will train next-generation precision medicine researchers who can integrate data analysis, biological mechanism studies, therapeutic development, and preclinical validation. Through these efforts, the Research Unit is expected to contribute to strengthening national healthcare capabilities and enhancing future competitiveness in the biohealth sector.

TALENT Ideal Talent

by creating a postdoctoral researcher-centered AI–Bio convergence research environment, the Unit will train next-generation precision medicine researchers who can integrate data analysis, biological mechanism studies, therapeutic development, and preclinical validation. Through these efforts, the Research Unit is expected to contribute to strengthening national healthcare capabilities and enhancing future competitiveness in the biohealth sector.

1. AI and Data Analysis Competency
The ability to understand large-scale patient multi-omics and clinical datasets, and to apply AI-based analytical approaches to identify disease-specific signals, gene regulatory networks, prognostic predictors, and therapeutic response biomarkers.

2. Biological Mechanism Research Competency
The ability to functionally validate candidate targets and disease networks identified through AI-based analysis using cellular systems, patient-derived models, and animal models, and to elucidate the mechanisms underlying the initiation, progression, relapse, and therapeutic resistance of hematologic cancers.

3. Convergence Research and Collaboration Competency
The ability to collaborate across disciplines with experts in AI, omics, cell biology, hematologic cancer biology, clinical research, drug development, cell therapy, and preclinical studies to solve complex biomedical problems.

4. Problem-Solving and Innovation Competency
The ability to redefine unresolved challenges in hematologic cancer precision medicine and to connect creative research strategies to diagnostic, predictive, and therapeutic technologies.

5. Global Research Competency
The ability to generate internationally competitive research outcomes and grow as an independent researcher within global research networks through strong research planning, scientific writing, presentation skills, and leadership.

FACULTY Faculty