• The newly upgraded HKEY-AIDMD 3.0 model library features nearly 300 autoimmune and allergy-related disease models. For multiple major indications, HKeyBio has established four-dimensional (4D) model pools that simulate clinical heterogeneity, providing a mechanism-driven model selection platform for evaluating multi-target combination therapies.
• The HKEY-AIDMD 3.0 omics database integrates spatiotemporal single-cell and spatial omics across various tissues and immune systems from the model library. This significantly improves resolution in identifying the differentiating advantages of multi-target combinations—uncovering subtle distinctions across genes, molecules, cells, tissues, and clinical phenotypes.

 HKeyBio, a global leading CRO specializing in preclinical and translational research for autoimmune and allergic disease drug development, has officially launched the upgraded HKEY-AIDMD 3.0 platform. This platform includes: (1) a four-dimensional model library of nearly 300 autoimmune and allergic disease models, and (2) a comprehensive spatiotemporal single-cell and spatial omics database derived from these models. The platform is designed to significantly enhance prediction accuracy for clinical translation of multi-target combination therapies.

Autoimmune and allergic diseases stem from dysregulated immune networks across three major immunological domains: multiple cellular components, diverse cytokine networks, and interconnected signaling pathways. These conditions involve aberrant activity of immune cell populations such as T cells, B cells, dendritic cells, and granulocytes; dysregulated cytokines including IL-6, IL-4, TNF; and perturbed signaling pathways such as JAK/STAT, NF-κB, BTK, along with mechanisms of immune tolerance. Since single-target drugs may demonstrate limited efficacy in certain patient populations, multi-target combinations can more comprehensively modulate pathological networks and improve therapeutic outcomes. Moreover, due to disease heterogeneity, multi-target therapies can more precisely match patient-specific pathogenic profiles, supporting personalized treatment strategies.

However, multi-target drug development faces major technical and clinical challenges. The number of possible combinations increases exponentially due to the diversity of targets, dosing regimens, and mechanisms of action. With limited resources, prioritizing the most effective and safest combinations is an urgent unmet need. Achieving optimal combinations requires accurate mapping of key pathogenic nodes within disease networks and identifying predictive biomarkers for treatment response.

HKeyBio's newly upgraded HKEY-AIDMD 3.0 provides a practical solution to the "optimal multi-target combination" challenge. Built upon deep mechanistic insights into autoimmune and allergic diseases, HKeyBio has developed four-dimensional model pools across multiple species, strains, and induction strategies to simulate various disease subtypes and endotypes. These model pools enable evaluation of in vivo interactions, feedback mechanisms, and synergy of multi-target combinations. Using systems biology approaches, including gene regulatory networks, protein-protein interaction networks, and pathway topology analysis, HKeyBio identifies key nodal and bottleneck targets in disease networks. Machine learning methods further support predictive modeling of combination outcomes and discovery/validation of biomarkers such as gene signatures, single-cell immune profiles, and cytokine panels.

The HKEY-AIDMD 3.0 platform not only enhances predictive value for multi-target efficacy but also significantly boosts developability and commercial partnering value. By integrating multi-indication 4D model pools with spatiotemporal omics, the platform offers critical support for new drug development in rheumatology, immunology, and allergy. It improves mechanistic accuracy, provides high-resolution multi-dimensional biomarker discovery, and increases reliability in predicting therapeutic responses across multiple pathways.