AIWhy is drug development so popular? BecauseTAThree Major Pain Points of Traditional R&D:

1. Target Identification: Precise Locking

   
   

   From "Finding a Needle in a Haystack" to "Precision Locking". The main targets of antibody drugs are cell surface receptors, soluble proteins, tumor antigens, etc. Traditional target discovery relies on gene knockout./Overexpression experiments and literature mining are prone to omissions.AIBy integrating multi-dimensional data such as genomics and proteomics, a knowledge graph can be constructed to quickly explore the associations between genes and diseases.

   
   

   Based on Graph Neural Network (GNN) Constructing intracellular protein interaction networks, identifying disease-related core regulatory targets, and discovering novel immune checkpoint proteins.Machine learning can integrate structural features, immunogenicity, tissue specificity, and other data of target proteins to construct a druggability scoring model, screening for targets with high affinity, low immunogenicity, and easy druggability while eliminating high-risk candidate targets.BenevolentAIThe company used these theories to design new targets for autoimmune diseases.IRAK4A fully human antibody, Phase II clinical trials have shown that it can improve symptoms in patients with rheumatoid arthritis, and the development cycle is shorter than the traditional model.60%。

   
   

2. Improve Efficiency, Shorten Cycle

   
   

   Phase Ⅱ clinical trials are known as the "valley of death" for innovative drugs. In the traditional model, about90%Candidate drugs will falter at this stage.AIThe intervention is changing this phenomenon, according to statisticsAIThe drug designed has a high level of80-90%The success rate significantly reduces the risk of later-stage development.Insilico Medicine'sRentosertib（ISM001-055) From target discovery to nominating preclinical candidate compounds, it only took18Months, costing about260Million USD. The time cost efficiency is greatly shortened compared to traditional methods, which can be called a "dimensionality reduction attack."

   
   

3. Optimization of Experimental Design

   
   

   During the clinical trial phase,AIAble to accurately screen patients and predict test results.AIOptimize trial protocols by analyzing real-world data to shorten enrollment time.AIIt can also analyze existing drug databases and clinical data, uncover new indications for existing drugs, and achieve efficient research and development. Therefore,AIR&D has established an "intelligent" design and validation closed-loop from data to drugs.Thereby systematically reducing the uncertainty in research and development, transforming "experience-driven" trial and error into "data-driven" rational design.

Drug development is a multi-stage, interdisciplinary, and high-risk systematic project, including several key stages such as target identification, drug discovery, preclinical research, clinical trials, regulatory approval, and post-marketing surveillance.AIAlthough the discovery of driver-based lead molecules has overcome the drawbacks of antibody discovery such as animal immunity and display libraries, and shortened the cycle of antibody discovery and screening, developing them into therapeutic drugs remains a long and challenging journey.

AIThe designed molecules need to undergo rigorous "wet lab" validation.AIExcels in "chemistry" issues, capable of designing nearly perfect target-binding molecules, increasing the success rate of the drug discovery phase to9%-18%。But it is still difficult to solve "biological" problems, such as: can this lead molecule really cause disease? Will it trigger unpredictable side effects? Therefore, functional verification and developability assessment are key steps.Establish "AIDesign (Dry)+The closed-loop R&D model of "high-throughput experimental validation (wet)" has become an industry consensus.

RT.

03

Solution:

Sino Biological High-Throughput Antibody Production and Analysis Platform

FacingAIThe urgent need for functional validation and developability assessment in antibody development,Sino Biological Launches SpecializedAIA one-stop high-throughput antibody production and analysis platform customized for drug research and development. The platform significantly shortens the process from "dry to wet" integration.AIDesign the transformation cycle from sequence to candidate drug molecules.

Sino Biological Integrates Two High-Throughput Platforms: Mammalian Cell and Cell-Free Expression, Enabling Antibody Purification Directly from Sequences in Just...5Days delivery.Matching20More than 10 advanced developability assessment tools, which can completeAIEfficient transformation of design sequences into candidate drug molecules significantly shortens the development cycle and accelerates the innovation process of biopharmaceutical enterprises.

1. Mammalian Transient Expression Platform: Efficient, High-Quality, High-Throughput

   
   

   Core Advantages: Relying on a fully automated plasmid construction platform to quickly, accurately, and efficiently complete gene synthesis and vector construction, combined with optimizationHEK293/CHOTransient expression system,AchieveFrom gene synthesis to antibody expression and purification as fast as10Day Delivery。

   
   

   Capacity and Diversity: Monthly production capacity exceeds10,000An antibody, supportIgG、scFv、Fab、VHH, bispecific antibodies and other antibody formats to meet the needs of large-scale screening.

   
   

   Quality Assurance: Relying on18Years of technical沉淀 and a well-established quality control system ensure the high activity and quality of the antibodies.

   
   

2. Cell-Free Protein Expression Platform (CFPS): Ultra-fast, flexible, highly scalable

   
   

   Disruptive Speed: ExogenousDNA/mRNAAs a template, the synthesis was completed in an in vitro enzyme system.3Hours to complete the expression,1Days to obtain purified antibodies, the fastest from sequence to purified sample only takes5Day.

   
   

   High-throughput Capability: Single Project Support2000+Antibody production capacity, and plasmid compatibilityDNAAnd LinearDNAInput.

   
   

   Excellent Performance: The antibody binding activity is comparable to that expressed in mammalian cells, with extended capabilities for producing difficult-to-express antibodies and antibodies containing non-natural amino acid sequences.

   

   
   

   Measured by its binding ability in a functional ELISA. Immobilized IL6R at 0.5 μg/ml (100 μL/well) can bind anti-IL6R VHH expressed by CFPS system and HEK293 Cell respectively.

   
   

3. Comprehensive Developability Assessment

   
   

   Multi-dimensional Testing: Supporting Provision20More Than 100 Ready-to-Use Physicochemical Detection Solutions (e.g.,ELISA、SPR、BLI, etc.), and evaluate the physicochemical properties, structural integrity, and biological functions of antibodies from multiple dimensions.

   
   

   Closed-loop Support: ForAIDriven next-generation antibody discovery provides full-chain technical support from design, production to validation, accelerating the innovation process of biopharmaceutical enterprises.

Conclusion

AIReshaping the underlying logic of drug development, transforming the past "relying on experience and luck" trial-and-error model into a "data-driven and logical" precision R&D approach. In this technological revolution, Sino Biological leverages its high-throughput antibody production and developability assessment platform to establish...AIDesign and clinical validation of the "last mile" to help enterprises reduce R&D risks, improve innovation efficiency, and jointly write a new chapter in human health.

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