Drug Design

The future of personalized, precision medicine.

Nucleic Acid and Small Molecular Drug Design

Graphen's four-stage drug development and optimization model untilizes AI to create precise and effective drugs and treatments targeting particular disease.

Stage 1: Pre-Development Study conducts druggable candidate finding by Poly-Omics Data with Clinical Label and Druggable Candidate Constructure.

Stage 2+3: Candidate Processing and Small Molecular Designer stage utilizes: Database of Small Molecular Drug for Reproposing Searching by Affinity Score (Kd/Ki), Database of Small Molecular Drug for New Drug Generating by Affinity Score + QED (drug likeness) + PLogP (solubility), Optimization of Small Molecular Candidates by Affinity Score + QED (drug likeness) + PLogP (solubility), and Safety Issue of Small Molecular Candidates by ADME Prediction and Small Molecular Candidates Side Effect Prediction.

Stage 4:The Antibody Drug Designer Includes: Epitope Finding for Druggable Targets, CDRs Substitution for Antibody Humanization and Optimization, Antibody Affinity Prediction, Develabilities of Antibody Structure


Vaccine Design and Optimization

Pre-Development Study

  • Vaccine Energy Prediction by Antibody - virus protein Co-structure.
  • Virus Variants Immune Escape Prediction.

  • Vaccine Design and Optimization

  • Optimization of Vaccine Immunol Epitopes Areas
  • Design Vaccine Candidate Structure
  • Refine the Affinity of Vaccine Candidate with Antibody Structures

  • Graphen's vaccine design and optimization model analyzes vaccine protein immunogenicity and the ability of immune escape from antibody or immune cell. It's desgined to be highly effective and takes into the consideration of virus mutation.


    Medical Domain Knowledge

    One advantage of Graphen's Drug Design lays in it's extensive medical domain knowledge.

    Graphen uses its next-gen Graph Database which includes cmplex medical researches and data on diseases. The Drug Design solution uses Ardi's Graph Computing to gain deep understanding of these diseases and therefore is able to predict and propose effective treatments.


    Patient-Centered Drug Development

    Graphen is able to unravel gene mutation and pathways linked to rare diseases. It combines gnomic, proteomic, and environmental analysis in conjunction with personal electronic medical record to design and develop effective drugs for targeted rare diseases.

    Graphen's personalized rare disease drug development is built upon deep domain knowledge and understanding of individual gene mutatnion. The system designs targeted, personalized, effective drugs for the treatment of rare diseases.


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