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DeepMatcher®
Deep-Matcher®
DeepMatcher® is Syntekabio's proprietary AI-based language modeling technology. It rapidly and accurately predicts target proteins for diseases using a large-scale compound library. This innovation drastically improves the accuracy and speed of the drug candidate discovery process.
Beyond the limits of uncertainty,
precision prediction
made by DeepMatcher®
New drug development takes an average of 10 to 15 years and costs billions of dollars, but the final success rate is less than 1%, indicating high uncertainty.
Particularly in the early stage of candidate discovery, immense time and resources are consumed to screen billions of compounds for suitable substances.
DeepMatcher® is an innovative AI platform that interprets the 3D structures of proteins and compounds as a language model, drastically shortening the drug development period and significantly increasing the probability of success.
Syntekabio’s Role
in the Drug Discovery Journey
DeepMatcher® is an AI-powered platform that offers an integrated solution covering two critical stages of drug discovery: hit discovery and lead optimization.
AI-based Matching —
Increasing the accuracy of
new drug development
By combining AI algorithms with large-scale supercomputing, we analyze the interaction between disease target proteins and drug candidates as if understanding a language. This approach significantly enhances both the speed and accuracy of hit discovery.
Overwhelming Efficiency
Supercomputer-based large-scale parallel processing drastically shortens the new drug development period and significantly reduces R&D costs.
Overwhelming Efficiency
Supercomputer-based large-scale parallel processing drastically shortens the new drug development period and significantly reduces R&D costs.
Precise Predictive Accuracy
An AI platform with a language model application surpasses conventional binding prediction methods, precisely analyzing molecular interactions and maximizing the probability of success.
Precise Predictive Accuracy
An AI platform with a language model application surpasses conventional binding prediction methods, precisely analyzing molecular interactions and maximizing the probability of success.
Targeting Difficult Targets
It discovers new drug candidates for targets related to intractable diseases that were difficult to approach with existing technologies.
Targeting Difficult Targets
It discovers new drug candidates for targets related to intractable diseases that were difficult to approach with existing technologies.
Integrated End-to-End Support
Provides a one-stop solution from candidate discovery to optimization and efficacy validation.
Integrated End-to-End Support
Provides a one-stop solution from candidate discovery to optimization and efficacy validation.
AI-based Matching —
Increasing the accuracy of
new drug development
By combining AI algorithms with large-scale supercomputing, we analyze the interaction between disease target proteins and drug candidates as if understanding a language. This approach significantly enhances both the speed and accuracy of hit discovery.
Overwhelming Efficiency
Supercomputer-based large-scale parallel processing drastically shortens the new drug development period and significantly reduces R&D costs.
Precise Predictive Accuracy
An AI platform with a language model application surpasses conventional binding prediction methods, precisely analyzing molecular interactions and maximizing the probability of success.
Targeting Difficult Targets
It discovers new drug candidates for targets related to intractable diseases that were difficult to approach with existing technologies.
Integrated End-to-End Support
Provides a one-stop solution from candidate discovery to optimization and efficacy validation.
DeepMatcher® Service Process
01
Target Protein Input
Preprocesses target protein structural data and converts it into a format compatible with language models.
01
Target Protein Input
Preprocesses target protein structural data and converts it into a format compatible with language models.
01
Target Protein Input
Preprocesses target protein structural data and converts it into a format compatible with language models.
02
Ultra-fast AI Screening (LM-VS™)
Conducts AI language model-based virtual screening (Language Model Virtual Screening) on a database of 10 billion compounds. It selects effective compounds by predicting binding energy for target proteins.
02
Ultra-fast AI Screening (LM-VS™)
Conducts AI language model-based virtual screening (Language Model Virtual Screening) on a database of 10 billion compounds. It selects effective compounds by predicting binding energy for target proteins.
02
Ultra-fast AI Screening (LM-VS™)
Conducts AI language model-based virtual screening (Language Model Virtual Screening) on a database of 10 billion compounds. It selects effective compounds by predicting binding energy for target proteins.
03
Precision Prediction and Optimization (Fine-Tuning)
Performs molecular dynamics simulations (Molecular Dynamic Simuation, MD Simulation) on the selected compounds.
Based on 3D structures, it precisely analyzes the optimal location and binding energy of the drug-protein binding, selecting the top 100 substances with a high probability of success.
03
Precision Prediction and Optimization (Fine-Tuning)
Performs molecular dynamics simulations (Molecular Dynamic Simuation, MD Simulation) on the selected compounds.
Based on 3D structures, it precisely analyzes the optimal location and binding energy of the drug-protein binding, selecting the top 100 substances with a high probability of success.
03
Precision Prediction and Optimization (Fine-Tuning)
Performs molecular dynamics simulations (Molecular Dynamic Simuation, MD Simulation) on the selected compounds.
Based on 3D structures, it precisely analyzes the optimal location and binding energy of the drug-protein binding, selecting the top 100 substances with a high probability of success.
04
AI-based Validation
Predicts the physical properties and ADMET/PK (pharmacokinetic) profile of the lead/candidate substances. It predicts drug absorption, distribution, metabolism, and toxicity to efficiently filter out candidate substances that have a high risk of failure in the clinical stage.
04
AI-based Validation
Predicts the physical properties and ADMET/PK (pharmacokinetic) profile of the lead/candidate substances. It predicts drug absorption, distribution, metabolism, and toxicity to efficiently filter out candidate substances that have a high risk of failure in the clinical stage.
04
AI-based Validation
Predicts the physical properties and ADMET/PK (pharmacokinetic) profile of the lead/candidate substances. It predicts drug absorption, distribution, metabolism, and toxicity to efficiently filter out candidate substances that have a high risk of failure in the clinical stage.
05
Final Candidate Derivation and Connection to Follow-up Research
Delivers the essential new drug development data package
for the final candidate substance. DeepMatcher® is more than
just a data provider; it's an integrated platform that helps you move
to the next successful stage of new drug development.
05
Final Candidate Derivation and Connection to Follow-up Research
Delivers the essential new drug development data package
for the final candidate substance. DeepMatcher® is more than
just a data provider; it's an integrated platform that helps you move
to the next successful stage of new drug development.
05
Final Candidate Derivation and Connection to Follow-up Research
Delivers the essential new drug development data package
for the final candidate substance. DeepMatcher® is more than
just a data provider; it's an integrated platform that helps you move
to the next successful stage of new drug development.
DeepMatcher® Service Process
DeepMatcher® secures a competitive edge with industry-leading accuracy
and processing speed in 'docking,' a technology that predicts how molecules bind using AI.
DeepMatcher® secures a competitive edge with industry-leading accuracy and processing speed in 'docking,' a technology that predicts how molecules bind using AI.
Overwhelming Search Range
By incorporating protein flexibility through a proprietary mold-based flexible docking technology, we expand the search space by up to 100x—enabling the discovery of novel compounds that were previously undetectable.
Overwhelming Search Range
By incorporating protein flexibility through a proprietary mold-based flexible docking technology, we expand the search space by up to 100x—enabling the discovery of novel compounds that were previously undetectable.
Overwhelming Search Range
By incorporating protein flexibility through a proprietary mold-based flexible docking technology, we expand the search space by up to 100x—enabling the discovery of novel compounds that were previously undetectable.
Excellent Predictive Accuracy
Delivers 15–30% higher accuracy compared to conventional algorithms, allowing for precise prediction of high-potential drug candidates.
Excellent Predictive Accuracy
Delivers 15–30% higher accuracy compared to conventional algorithms, allowing for precise prediction of high-potential drug candidates.
Excellent Predictive Accuracy
Delivers 15–30% higher accuracy compared to conventional algorithms, allowing for precise prediction of high-potential drug candidates.
Optimal Efficiency
Integrates the entire process from in silico prediction to efficacy validation through AI, dramatically reducing the time and cost of drug development.
Optimal Efficiency
Integrates the entire process from in silico prediction to efficacy validation through AI, dramatically reducing the time and cost of drug development.
Optimal Efficiency
Integrates the entire process from in silico prediction to efficacy validation through AI, dramatically reducing the time and cost of drug development.
Applications of DeepMatcher®
Intractable Target Proteins
Enables the discovery of new compounds for difficult-to-treat or previously untreatable targets.
Intractable Target Proteins
Enables the discovery of new compounds for difficult-to-treat or previously untreatable targets.
Intractable Target Proteins
Enables the discovery of new compounds for difficult-to-treat or previously untreatable targets.
Repositioning
Supports new indication development for FDA-approved and clinical-stage drugs.
Repositioning
Supports new indication development for FDA-approved and clinical-stage drugs.
Repositioning
Supports new indication development for FDA-approved and clinical-stage drugs.
Targeted Therapies
Proved the possibility of personalized anti-cancer therapy by discovering candidates that selectively act on specific mutations.
Targeted Therapies
Proved the possibility of personalized anti-cancer therapy by discovering candidates that selectively act on specific mutations.
Targeted Therapies
Proved the possibility of personalized anti-cancer therapy by discovering candidates that selectively act on specific mutations.
Novel Modality Development
Applies deep learning to analyze protein–protein interaction patterns, enabling the discovery of novel modalities such as molecular glues and TPD (Targeted Protein Degradation).
Novel Modality Development
Applies deep learning to analyze protein–protein interaction patterns, enabling the discovery of novel modalities such as molecular glues and TPD (Targeted Protein Degradation).
Novel Modality Development
Applies deep learning to analyze protein–protein interaction patterns, enabling the discovery of novel modalities such as molecular glues and TPD (Targeted Protein Degradation).
Experience the new standard
in drug development
with DeepMatcher now.
Experience the new standard
in drug development
with DeepMatcher now.
Global Premier AI
Drug Partner
Innovate with us.
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© Syntekabio Co., Ltd. All rights reserved.
General Inquiries
Investor Relations / Press
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Data Center
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Global Premier AI
Drug Partner
Innovate with us.
Contact Us
Contact Us
© Syntekabio Co., Ltd. All rights reserved.
General Inquiries
Investor Relations / Press
Business Development / Partnerships
Data Center
Family Sites
© Syntekabio Co., Ltd. All rights reserved.