全球新藥開發中的In Silico預測技術企業介紹

Examples of Companies Using In Silico Prediction for New Drug Development

Below are some international companies actively using in silico prediction technologies in drug development:

Exscientia is based in Oxford, UK, and focuses on leveraging AI and machine learning for drug design and development, with multiple drugs already in clinical trials.

Insilico Medicine is headquartered in Hong Kong and accelerates drug discovery with deep learning and molecular modeling, focusing on cancer and neurodegenerative diseases.

Absci is located in Vancouver, Washington, USA, and uses AI to search billions of potential drug designs, aiming to reduce development costs and accelerate time-to-market.

Generate Biomedicines in Cambridge, Massachusetts, USA, specializes in AI-driven protein drug design, particularly for gene therapy and vaccine development.

Deep Genomics is headquartered in Toronto, Canada, applying AI to genomics to develop drugs for rare diseases.

These companies utilize in silico prediction technologies, using computational modeling and simulations to accelerate the drug discovery and development process.

Detailed Overview of Companies Using In Silico Prediction Technology

Exscientia: AI-Driven Drug Design

Exscientia, based in Oxford, UK, is one of the global leaders in AI-driven drug development. Their platform combines AI with machine learning for efficient drug design, focusing on accelerating the early stages of drug discovery. Exscientia has successfully designed multiple drugs now in clinical trials, including therapies for cancer and immune diseases, establishing itself as a key player in AI drug development.

Insilico Medicine: Genomics and Molecular Modeling Platforms

Headquartered in Hong Kong, Insilico Medicine uses deep learning and molecular modeling technologies for drug development, especially in cancer, fibrosis, and neurodegenerative diseases. Their core AI platforms include "PandaOmics" and "Chemistry42":

• PandaOmics: This AI-driven platform aids in target discovery for diseases by integrating genomics and bioinformatics. It leverages data sources across genomics, transcriptomics, proteomics, and clinical data, identifying disease-relevant targets to speed up drug discovery.

• Chemistry42: This molecular design platform uses generative AI to create and optimize candidate molecules. By simulating properties like solubility and toxicity, it enables rapid design of safe and effective compounds, widely applied in cancer, neuroscience, and infectious disease research.

Absci: AI-Enhanced Biopharmaceutical Screening

Absci, based in Vancouver, Washington, USA, focuses on biopharmaceuticals by using AI to screen and design proteins. Their platform analyzes billions of molecular design combinations to identify the best candidate drugs, greatly reducing the time and costs involved in biopharmaceutical development. Particularly suited for protein-based drugs, Absci’s technology enables rapid identification of potent protein formulas for applications in oncology and immunotherapy.

Generate Biomedicines: Generative AI for Protein Design

Located in Cambridge, Massachusetts, Generate Biomedicines is a biotech company focused on protein design using generative AI. Their platform can generate protein sequences based on therapeutic requirements and predict their effects, facilitating the rapid development of drug candidates for gene therapy, antibody drugs, and vaccines. Generate Biomedicines has established a significant presence in AI-driven protein therapeutics, advancing drug development in cancer, infectious diseases, and metabolic disorders.

Deep Genomics: AI-Driven Genomics in Drug Development

Toronto-based Deep Genomics applies AI to genomics for identifying gene therapy drugs targeted at rare diseases. Their AI platform analyzes vast amounts of genomic data to identify gene mutations linked to diseases, and then designs targeted small molecule drugs. Deep Genomics has a particular focus on RNA-related diseases and has advanced into preclinical trials, with plans to expand into neurological and metabolic disease treatment.

By combining AI with computational modeling, these companies accelerate drug discovery, shaping the future of biotechnology and pharmaceutical industries.

Detailed Description of Insilico Medicine’s Platforms: PandaOmics and Chemistry42

Insilico Medicine’s "PandaOmics" and "Chemistry42" are the core platforms specifically designed for drug discovery. Below is a detailed description of each platform:

PandaOmics: Genomics-Based Target Discovery Platform

"PandaOmics" is an AI-driven platform for target discovery, integrating genomics and bioinformatics to accelerate the identification of promising drug discovery targets.

• Multi-Omics Data Integration: PandaOmics leverages a wide range of data, including genomics, transcriptomics, proteomics, chemical response, and clinical information, providing a multi-perspective analysis of disease mechanisms.

• Disease-Target Matching: This platform screens for targets linked to specific diseases by identifying genes associated with the disease and predicting their mechanisms.

• Risk Prediction and Filtering: With a robust risk prediction feature, PandaOmics assesses the druggability and potential risks of each target, helping researchers select the most viable options.

• Applications: PandaOmics is ideal for discovering targets in cancer, neurodegenerative diseases, and metabolic disorders. The platform narrows research to the most promising targets, expediting new drug discovery.

Chemistry42: Molecular Design and Synthesis Simulation Platform

"Chemistry42" is an AI platform supporting compound design and simulation, using generative AI and molecular modeling to create candidate compounds.

• Generative AI Modeling: Chemistry42 employs generative neural networks to create and optimize molecules at the atomic level, rapidly generating compounds with specific pharmacological traits. This approach significantly shortens the timeline from initial molecule design to selecting viable drug candidates.

• Molecular Property Optimization: This platform optimizes molecules for properties like solubility, bioavailability, and toxicity, ensuring candidates meet the highest standards for efficacy and safety.

• Virtual Screening and Simulation: Chemistry42 conducts virtual screening and simulation, allowing researchers to efficiently filter and predict the metabolic and interaction behavior of compounds.

• Applications: Widely used for new molecule design and optimization of existing compounds, Chemistry42 is applied in cancer treatment, anti-infective drugs, and neuroscience.

Summary

Together, PandaOmics and Chemistry42 form a complementary suite of tools, connecting target discovery with candidate drug design in a cohesive drug development workflow. Insilico Medicine leverages this integrated AI technology to accelerate the drug discovery cycle, providing a more precise and efficient solution than traditional methods.

Does Insilico Medicine Use GSEA Technology?

Insilico Medicine’s PandaOmics platform incorporates Gene Set Enrichment Analysis (GSEA) technology to provide deeper insights during target discovery by analyzing gene expression data. The GSEA applications within PandaOmics include:

• Identifying Disease-Associated Genes: PandaOmics uses GSEA to evaluate gene sets associated with specific disease processes under various experimental conditions or samples, helping to identify potential therapeutic targets.

• Pathway Analysis: By integrating GSEA results with pathway analysis, PandaOmics identifies disease-relevant signaling pathways, assisting researchers in understanding disease mechanisms.

• Multi-Layer Data Integration: GSEA plays a critical role in integrating multi-omics data in PandaOmics, combining transcriptomics and proteomics to verify gene enrichment status and pinpoint critical biological pathways and potential drug targets.

Conversely, Chemistry42 does not directly employ GSEA technology, as it focuses primarily on molecule design and optimization through generative AI and molecular modeling, rather than relying on gene expression data.

Insilico Medicine’s Business Model Overview

Insilico Medicine Official Website
Insilico Medicine’s business model is built around proprietary AI platforms, offering an end-to-end drug discovery solution from target identification to compound design.

Core Aspects of the Business Model

• Target Discovery: Using AI to analyze multi-layer biological data, Insilico Medicine identifies targets associated with various diseases.

• Drug Design: Leveraging generative AI and molecular modeling, the company designs compounds with specific pharmacological properties.

• Integrated Platform: By providing a comprehensive platform from disease target identification to candidate drug design, Insilico Medicine accelerates the drug development timeline.

Through this AI-driven approach, Insilico Medicine aims to enhance drug discovery efficiency and success rates, driving innovation within the pharmaceutical industry.