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Discovery & Development

AI-driven DeepMatcher Drug Candidate Service

The Diagram shows Docker's extension to Syntekabio's AI-powered full drug discovery service solution that support almost all areas of drug discovery & development process from Hit discovery / Lead generation, and ADMET/PK to the pharmacogenomics biomarkers. It is based on Syntekabio’s powerful AI technologies (DeepMatcher®) that provide the best docking Hits/Leads through analysis of deep learning (3D-CNN) and MD simulation on targets.

The Diagram shows Docker's extension to Syntekabio's AI-powered full drug discovery service solution that support almost all areas of drug discovery & development process from Hit discovery / Lead generation, and ADMET/PK to the pharmacogenomics biomarkers. It is based on Syntekabio’s powerful AI technologies (DeepMatcher®) that provide the best docking Hits/Leads through analysis of deep learning (3D-CNN) and MD simulation on targets.
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DDCS : Hit to Preclinical Candidate in 2 YEARS

  • Hit

    Hit

    Hit Screening

    DeepMatcher - Hit

  • Lead

    Lead

    Lead Generation

    DeepMatcher - Lead

  • Candidate

    Candidate

    ADMET/ PK

    DeepMatcher - ADMET/PK

  • Preclinical

    Preclinical

    GLP-Tox

    FDA Registered Facility (CRO)

  • Precision Medicine

    Precision Medicine

    Clinical

    Clinical

    PGx Biomarkers for Drug Labeling

    Immunogenic Neoantigen Prediction

    Cancer/CNS Patient Stratification SNPs

    CYP typing, HLA typing & KIP typing

  • A-Z Package

    Hit-Discovery, Assay Validation, Lead Generation & Preclinical Study

  • Client-Centric

    Minimal Risk *Maximum Customization

  • In-House & Global
    CRO Cooperation

    Discovery & Development

  • Infra-structure

    Fully Customized Packages & Services to Ensure High Success Rate

    Bio-Supercomputer Capacity for Bio-Research, Medicine & Pharmacology

  • Experiences

    15+ Years Experience on Machine-Learning + Structural biology + Supercomputing

    AI & GPT Accelerates Screening Flows and Calculations and increase success rate

    30+ Affiliations & Partnerships with Certified Global CRO Expert Groups

  • Owner-finance

    7.5% Down Payment of Total $cost to Start & Installments for Pay As You Go Model

    Flexible Timeline & Milestone to Match Client’s Finance & Convenience

  • All in one

    From Start-to-Finish A-Z Services = Identify Preclinical Drug Candidate in 2 YEARS & Support IND Preparation

Hit to Preclinical Candidate in 2 YEARS

AI Bio-supercomputer(ABS) center with 10,000 servers (in progress)
CLOUD based ABS serves best-in-solutions for AI drug discovery

>5~8 yrs+>10yrs, 1 approved drug

Drug Discovery

Preclinicial

Clinic Development

1 yr
2 yr
5 yr

Hit Id

Hit to Lead

Lead Opt.

Preclinicial

1 yr
1 yr

Hit

Lead-gen

ADMET/Pk

STB CLOUD + DeepMatcher

Hit

All in 50 Days Form Inial Feasbility
Test to Done Screening

In-vitro assat 100 days, Start to Lead :
Entry Point within 150 Days

Lead-gen

Lead gen.
in 210 days

ADMET/PK

1 Year Period:
form leads to
ADMET Screening

DeepMatcher (Preclinical) Drug Candidate : DDC framework
Auto-Hit Screening

Auto-Hit Screening

  • 10B purchasable Cpnd, screening
  • 1M Physical docking
  • 1K 3D-CNN binding tunning
  • 1K Auto-MD Simulatio
  • In-vitro validation
  • Al-Hits <1μM
  • Finding Grooves (sub-pocket)
  • 20K R-group Substitution
  • Spatial Occupancy Filtering
  • 1K Auto-MD Simulation
  • Iln-vitro/In-vivo validation
  • Al-Leads <10nM
Auto-Lead Generation

Auto-Lead Generation

Auto-ADMET/PK Prediction

Auto-ADMET/
PK Prediction

  • BERT pre- trained Model
  • Multi-tasking ADMET profiling
  • 3D-CNN Toxicity prediction
  • PK prediction
  • In-vitro/In-vivo validation
  • Preclinical candidate

Seeking Ultimate Success

AI-powered auto-HIT/Lead discovery: DDCS, as successful loop platform

  • 1Auto-HIT Discovery

    • Purchasable 10B Chemical Library
    • Physical-3D Docking (1M)
    • 3D-CNN Pose Tunning (1K)
    • Auto-MD Simulation Fine Tunning (1K)

  • 2Auto-Lead Gen.

    • Sub-pocket & Week bond Screening
    • Substitution of 20K R-group to Scaffold
    • Free Energy Perturbation in the Sub-pocket
    • Auto-MD Simulation Fine Tunning (1K)

  • 3Auto-ADMET.PK Scr.

    • Solubility,Intestinal Absorption, Metabolism, PPB, BBB
    • Liver injury, Off target toxicity (NR,HLA adduct, Signaling), PK, etc.
  • Deep Learning : Strength in docking & best pose generation similar to real 3D structure
  • Auto-MD simulation : Strength in binding energy calculations close to experimental values
  • GPT : Streng thin virtual screening by cognitive learning based on big data and extreme hardware
  • Chemical Library
    screening
    Chemical Library screening
  • 3D-CNN Binding Tuning
    3D-CNN Binding Tuning
  • R-group substitution
    R-group substitution
  • Auto-MD Simulation
    Auto-MD Simulation
  • BERT – ADMET/PK screening
    BERT – ADMET/PK screening
  • 3bmGPT - key residue analysis
    3bmGPT - key residue analysis
Service Process
  • Step
  • Items
  • Core Technology
  • TPP
  • Duration
  • Hit Discovery
    AI-Hit discovery
    AI-Hit purchase
    Hit confirm
    DMC-Hit®
    IC50 < 1μM~8 Hits
    ~2m
    ~3m
  • Lead Generation
    AI-LEADgeneration
    Compound synthesis & Lead confirm
    Go-No Go Decision (1st Year)
    DMC-Lead®
    IC50 < 10nM ~4 Leads
    ~7m
  • ADMET/PK(Preclinical Candidate)
    AI-ADMETgeneration
    Compound synthesis
    ADMETvalidation
    PKvalidation in mice (PO)
    Success-Failure Decision (2nd year)
    DMC-ADMET/
    PK predictor®
    Decent ADMET
    /PK Profiles
    ~1 Candidate
    ~12m
Cost Breakdown
  • Unit
  • Hit Discovery
  • Lead Generation
  • ADMET/PK
  • Total
  • Hardware/computation
    (single service only*)
    100 Servers / 3Month
    100 Servers / 3Month
    100 Servers / 3Month
    -
    $150K
    $150K
    $150K
    -
  • Chemical
    Purchase/Synthesis/Assay
    (Validationsize)
    ~200 chemicals
    ~200 chemicals
    ~200 chemicals
    -
    $20K ($100/chemical/
    purchase)
    $300K (10mg/chemical/
    synthesis)
    $200K (~150mg/
    chemical/
    synthesis)
    -
    $20K ($100/chemical/
    purchase)
    $7.5K ($150/chemical)
    $400K (~150mg/
    chemical/
    synthesis)
    -
  • Estimated Cost sum
    $200K
    $457K
    $750K
    Total
    $1.4 Million
  • BigPharma Traditional R&D Cost④
    $1.0M
    $12.5M
    $12.5M
    Total
    $13.5M

Medium.com/EvinceBio, 2017 report

References:
  • Syntekabio’s Hit to PreclinicalCandidate on Cloud Computing, BioPharmaTrend. Vol4.2023
  • How Syntekabio’s Supercomputing Enables AI-driven Drug Discovery, BioPharmaTrend, Vol3. 2023
  • The Power of STB CLOUD in Remote AI Drug Discovery, BioPharmaTrend, Vol2. 2023
  • The State of A.I. Drug Discovery and Its Future:Small Molecules, Vaccines, and Antibodies, BioPharmaTrend, Vol1. 2023

DDC AI-driven DeepMatcher
(preclinical) Drug
Candidate Service

DDCS : HIT to Preclinical Candidate in 2 YEARS

The Diagram shows Docker's extension to Syntekabio's AI-powered full drug discovery service solution that support almost all areas of drug discovery & development process from Hit discovery / Lead generation, and ADMET/PK to the pharmacogenomics biomarkers. It is based on Syntekabio’s powerful AI technologies (DeepMatcher®) that provide the best docking Hits/Leads through analysis of deep learning (3D-CNN)and MD simulation on targets. Docker is a virtualization software.

  • Hit

    Hit

    Hit Screening

    DeepMatcher - Hit

  • Lead

    Lead

    Lead Generation

    DeepMatcher - Lead

  • Candidate

    Candidate

    ADMET/ PK

    DeepMatcher - ADMET/PK

  • Preclinical

    Preclinical

    GLP-Tox

    FDA Registered Facility (CRO)

  • Precision Medicine

    Precision Medicine

    Clinical

    Clinical

    PGx Biomarkers for Drug Labeling

    Immunogenic Neoantigen Prediction

    Cancer/CNS Patient Stratification SNPs

    CYP typing, HLA typing & KIP typing

  • A-Z Package

    Hit-Discovery, Assay Validation, Lead Generation & Preclinical Study

  • Client-Centric

    Minimal Risk * Maximum Customization

  • In-House & Global
    CRO Cooperation

    Discovery & Development

  • Infra-structure

    Fully Customized Packages & Services to Ensure High Success Rate

    Bio-Supercomputer Capacity forBio-Research, Medicine & Pharmacology

  • Experiences

    15+ Years Experience onMachine-Learning + Structural biology + Supercomputing

    AI & GPT Accelerates Screening Flows and Calculations and increase success rate

    30+ Affiliations & Partnerships with Certified Global CRO Expert Groups

  • Owner-finance

    7.5% Down Payment of Total $cost toStart & Installments for Pay As You Go Model

    Flexible Timeline & Milestone to Match Client’s Finance & Convenience

  • All in one

    From Start-to-Finish A-Z Services = Identify Preclinical Drug Candidate in 2YEARS & Support IND Preparation

HIT to Preclinical Candidate in 2 YEARS

Bio-supercomputer AI-data centerwith 10,000 servers (in progress)
CLOUD based ABC servesbest-in-class solutions for AI drug discovery

>5~8 yrs+>10yrs, 1 approved drug

Drug Discovery

Preclinicial

Clinic Development

1 yr
2 yr
5 yr

Hit Id

Hit to Lead

Lead Opt.

Preclinicial

1 yr
1 yr

Hit

Lead-gen

ADMET/Pk

STB CLOUD + DeepMatcher

Hit

All in 50 Days Form Inial Feasbility
Test to Done Screening

In-vitro assat 100 days, Start to Lead :
Entry Point within 150 Days

Lead-gen

Lead gen.
in 210 days

ADMET/PK

1 Year Period:
form leads to
ADMET Screening

DeepMatcher (Preclinical) Drug Candidate : DDC framework
Auto-Hit Screening

Auto-Hit Screening

  • 10B purchasable Cpnd, screening
  • 1M Physical docking
  • 1K 3D-CNN binding tunning
  • 1K Auto-MD Simulatio
  • In-vitro validation
  • Al-Hits <1μM
  • Finding Grooves (sub-pocket)
  • 20K R-group Substitution
  • Spatial Occupancy Filtering
  • 1K Auto-MD Simulation
  • Iln-vitro/In-vivo validation
  • Al-Leads <10nM
Auto-Lead Generation

Auto-Lead Generation

Auto-ADMET/PK Prediction

Auto-ADMET/
PK Prediction

  • BERT pre- trained Model
  • Multi-tasking ADMET profiling
  • 3D-CNN Toxicity prediction
  • PK prediction
  • In-vitro/In-vivo validation
  • Preclinical candidate

Seeking Ultimate Success

AI-POWERED auto-HIT/Lead discovery: DDCS, as successful loop platform

  • 1Auto-HIT Discovery

    • Purchasable 10B Chemical Library
    • Physical-3D Docking (1M)
    • 3D-CNN Pose Tunning (1K)
    • Auto-MD Simulation Fine Tunning (1K)

  • 2Auto-Lead Gen.

    • Sub-pocket & Week bond Screening
    • Substitution of 20K R-group to Scaffold
    • Free Energy Perturbation in the Sub-pocket
    • Auto-MD Simulation Fine Tunning (1K)

  • 3Auto-ADMET.PK Scr.

    • Solubility,Intestinal Absorption, Metabolism, PPB, BBB
    • Liver injury, Off target toxicity (NR,HLA adduct, Signaling), PK, etc.
  • Deep Learning : Strength in docking & best pose generation similar to real 3Dstructure
  • Auto-MD simulation : Strength in binding energy calculations close to experimentalvalues
  • GPT : Strengthin virtual screening by cognitive learning based on big data and extremehardware
  • Chemical Library
    screening
    Chemical Library screening
  • 3D-CNN Binding Tuning
    3D-CNN Binding Tuning
  • R-group substitution
    R-group substitution
  • Auto-MD Simulation
    Auto-MD Simulation
  • BERT – ADMET/PK screening
    BERT – ADMET/PK screening
  • 3bmGPT - key residue analysis
    3bmGPT - key residue analysis
Service Process
  • Step
  • Items
  • Core Technology
  • TPP
  • Duration
  • Hit Discovery
    AI-Hit discovery
    AI-Hit purchase
    Hit confirm
    DMC-Hit®
    IC50 < 1μM~8 Hits
    ~2m
    ~3m
  • Lead Generation
    AI-LEADgeneration
    Compound synthesis & Lead confirm
    Go-No Go Decision (1st Year)
    DMC-Lead®
    IC50 < 10nM ~4 Leads
    ~7m
  • ADMET/PK(Preclinical Candidate)
    AI-ADMETgeneration
    Compound synthesis
    ADMETvalidation
    PKvalidation in mice (PO)
    Success-Failure Decision (2nd year)
    DMC-ADMET/
    PK predictor®
    Decent ADMET
    /PK Profiles
    ~1 Candidate
    ~12m
Cost Breakdown
  • Unit
  • Hit Discovery
  • Lead Generation
  • ADMET/PK
  • Total
  • Hardware/computation
    (single service only*)
    100 Servers / 3Month
    100 Servers / 3Month
    100 Servers / 3Month
    -
    $150K
    $150K
    $150K
    -
  • Chemical
    Purchase/Synthesis/Assay
    (Validationsize)
    ~200 chemicals
    ~200 chemicals
    ~200 chemicals
    -
    $20K ($100/chemical/
    purchase)
    $300K (10mg/chemical/
    synthesis)
    $200K (~150mg/
    chemical/
    synthesis)
    -
    $20K ($100/chemical/
    purchase)
    $7.5K ($150/chemical)
    $400K (~150mg/
    chemical/
    synthesis)
    -
  • Estimated Cost sum
    $200K
    $457K
    $750K
    Total
    $1.4 Million
  • BigPharma Traditional R&D Cost④
    $1.0M
    $12.5M
    $12.5M
    Total
    $13.5M

Medium.com/EvinceBio, 2017 report

References:
  • Syntekabio’s Hit to PreclinicalCandidate on Cloud Computing, BioPharmaTrend. Vol4.2023
  • How Syntekabio’s Supercomputing Enables AI-driven Drug Discovery, BioPharmaTrend, Vol3. 2023
  • The Power of STB CLOUD in Remote AI Drug Discovery, BioPharmaTrend, Vol2. 2023
  • The State of A.I. Drug Discovery and Its Future:Small Molecules, Vaccines, and Antibodies, BioPharmaTrend, Vol1. 2023

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