One-stop drug design

High-performance

Research Platform for Mechanism of Target Proteins

MoMed Biotech  focuses on research and development by adapting Nobel Chemistry Prize-winning computational biology technologies to the study of ultra-large-scale biomolecular systems. The platform conducts research on the interactions between small-molecule drugs and DNA/proteins, which not only helps elaborate the mechanism of drug action at the molecular level, but also holds significant importance for the in vitro screening of anti-cancer and antiviral drugs. Meanwhile, it provides theoretical guidance and valuable information for designing more effective anti-cancer, antiviral and other drugs, offering the highest-performance research service platform.

High-innovation

Artificial Intelligence Platform for Mining New Disease Pathways

Traditional drug development faces bottlenecks such as long cycles, high costs, and high failure rates. "Drug repositioning," which explores new indications for approved drugs, can significantly shorten the R&D cycle and reduce risks. MoMed Biotech has established a platform for mining new disease pathways based on multidisciplinary knowledge integration and graph neural networks. By using AI technology to integrate massive biomedical data, the platform constructs a knowledge graph of drugs-targets-diseases, and identifies potential new indications for marketed or clinical-stage drugs. This approach can drastically shorten the drug R&D cycle and mitigate risks.

High-scale

Target Protein Kinetics Database

MoMed Biotech enables full-cycle dynamic capture of drug target proteins through their steady state → transition state → functional state, breaking through the limitations of traditional static structural biology analysis. Currently, the company has completed mechanistic studies on multiple key drug target proteins, accurately capturing kinetic information such as transition state structures and energy barriers during the proteins’ operational processes. Based on this information, MoMed Biotech has constructed a large-scale Target Protein Kinetics Database that integrates dry (in-silico) and wet-lab experimental data, with wet-lab results validated to ensure accuracy. This database facilitates the training of artificial intelligence-driven drug design models. By integrating multiple compound databases, it provides the most comprehensive compound resources for drug screening. Research on target protein mechanisms is ongoing, and the database is continuously expanding.

High-intelligence

Artificial Intelligence Small Molecule Drug Design Platform

Small-molecule compounds remain the dominant type of approved drugs, characterized by low cost, high bioavailability, and favorable pharmacokinetic properties. Based on its unique mechanistic research platform and combined with advanced artificial intelligence algorithms.

MoMed Biotech has established a small-molecule drug design platform that covers the full spectrum of design tasks, including virtual screening, structure-based drug design, fragment-based drug design, AI de novo drug design, and AI-driven molecular optimization.

High-Level

AI-Based Macromolecular Drug Design Platform

Macromolecular drugs encompass various types such as antibodies, polypeptides, and antibody-drug conjugates (ADCs). They can address the challenge of "difficult-to-drug" targets that small-molecule drugs cannot solve, offering advantages of higher affinity and better selectivity.

Leveraging unique computational biology technologies combined with advanced artificial intelligence models, MoMed Biotech can complete a series of macromolecular drug design tasks, including polypeptide design, protein structure modeling, antibody sequence design, and antibody humanization optimization, providing comprehensive services.

High-efficiency

Multi-pipeline drug R&D platform

MoMed Biotech's drug discovery platform efficiently and innovatively supports parallel development across multiple pipelines. With the best R&D technology, the most stringent quality standards, the most professional service and the use of advanced technical means and strict quality management system.

we provide first-class, professional and efficient multi-pipeline drug research and development solutions, and constantly optimize the process and improve efficiency in the process to ensure the maximization of R&D results and achieve a win-win situation.

High-precision

Artificial Intelligence Platform for Predicting ADMET Properties of Drugs

In drug research and development, the evaluation of a molecule's absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties is a critical factor determining the success or failure of candidate compounds. Traditional methods for ADMET evaluation rely on animal experiments and in vitro testing, which are time-consuming and costly.  To address this, Chenzhu Technology has established a cutting-edge AI-driven drug property prediction platform. By leveraging the Directed Message Passing Neural Network (D-MPNN), the platform automatically learns molecular topological features, overcoming the limitations of traditional QSAR models that depend on expert experience. This innovation enables rapid and accurate evaluation of compound ADMET properties, providing key decision-making support throughout the entire drug research and development lifecycle.