Infinite Intelligence
Pharma

Insight & Innovation for Drug Dicovery

深思明辨,百药可成

About us

Infinite Intelligence Pharma, officially launched in 2019, uses artificial intelligence technique to accelerate drug discovery process. Our drug discovery R&D platform PharmMind, which integrates human expertise, state-of-art AI algorithms and cutting-edge drug design methods are designed to addresses key problems in early stage of drug discovery.

PharmaMind

PharmaMind uses advanced artificial intelligence drug discovery (AIDD) and computer-aided drug design technology (CADD) to promote the drug discovery process. The system is driven by big data, AIDD and CADD technology. Besides accuracy and speed, interpretability is also a key consideration to assist experts in understanding problems and making decisions.

Tech & Product

IIP分子探索3D

MolExplorer3D

IIP分子优化3D

MolOptimizer3D

IIP分子搜索

MolSearcher

IIP分子评估

MolEvaluator

IIP分子探索3D
MolExplorer3D

  • Stimulate your inspiration by effectively explore compound scaffolds that can potentially bind to specific targets.

  • Based on the target structure, use deep learning technology to generate molecules with good drug-like properties and high potential binding ability.

IIP分子探索3D
MolOptimizer3D

  • Optimize the structure of hit/lead based on binding affinity, druggability and synthesis feasiability.

  • Improve biological activity as well as harmacokinetic properties.

  • Reduce toxicity to obtain safe and effective drug candidates for subsequent development.

IIP分子探索3D
MolOptimizer3D

  • Optimize the structure of hit/lead based on binding affinity, druggability and synthesis feasiability.

  • Improve biological activity as well as harmacokinetic properties.

  • Reduce toxicity to obtain safe and effective drug candidates for subsequent development.

IIP分子搜索
MolSearcher

  • Search other potential active small molecules based on reference ligands.

  • Use multi-dimensional similarity index based on deep learning to expand the search of chemistry space.

IIP分子评估
MolEvaluator

  • Use a variety of models that integrate artificial intelligence and computer-aided drug design to evaluate the multi-dimensional properties of a compound.

  • Physical and chemical properties.

  • ADMET properties,Druggability.

  • Synthesis feasiability.

  • Docking scoring and pharmacophore matching scoring, etc.

IIP分子评估
MolEvaluator

  • Use a variety of models that integrate artificial intelligence and computer-aided drug design to evaluate the multi-dimensional properties of a compound

  • Physical and chemical properties

  • ADMET properties,Druggability

  • Synthesis feasiability

  • Docking scoring and pharmacophore matching scoring, etc.

IIP虚拟筛选
MolDOCKingVS

  • Your content goes here. Edit or remove this text inline or in the module Content settings. You can also style every aspect of this content in the module Design settings and even apply custom CSS to this text in the module Advanced settings.

IIP多靶标药物设计
MolMulti-Target

  • Single-target drugs are often less effective in controlling complex diseases with multiple pathogenic factors, such as diabetes, inflammation, cancer, and central nervous system disorders. Biological network analysis generally provides multiple-target control solutions, and single-target solutions are rare. Combination therapy or multi-target therapy is necessary to effectively treat these diseases.

  • We design multi-target drugs using de(斜体)novo (斜体)structure-based methods in a rational and “highly integrated”manner.

  • We also design multi-target drugs using AI generation models consensus on multiple targets.

IIP逆合成分析
MolSynthesize

  • The synthesis process of new molecules either by generation or modification is not easy.  Therefore, solving the synthesis problems of the designed molecules is the key step for actual verification.

  • Reverse synthesis analysis based on fast heuristic enhanced tree search algorithm helps synthesizers arrange the order of experiments and obtain compounds faster.

  • Evaluating the synthesis feasiability and potential synthesis methods of compounds.

IIP互动分子设计
MolInteractive

  • The incorporation of human expertise and artifical intelligence via well-designed interactive molecular design process is an ideal way to improve the success rate of design, which makes the design process stable and controllable.

IIP分子数据挖掘
MolDataMiner

  • Use combined advanced deep learning technology (natural language processing technology, image recognition technology, graph neural network technology, etc.) to build a knowledge graph.

IIP蛋白质结构功能设计与改造
ProDesign

  • We design protein structures and sequences to meet the protein functional need from the industry.
  • Enzyme engineering is also specialty of IIP, designing optimized engineered enzyme through dynamics simulations and computations helps the developments in healthcare and pharmaceutical industry.

IIP靶向无序蛋白质的药物设计
DrugIDP

  • Many human diseases are closely related to intrinsically disordered proteins, which are currently recognized as a new class of potential drug targets.
  • IIP specializes in rational drug molecular design targeting intrinsically disordered proteins based on their ensemble structures.

Team

Dr. Jianfeng Pei

Chief Scientist

Dr. Youjun Xu

Chief of AIDD

Dr. Weilin Zhang

Chief of CADD

Mr. Jinchuan Xiao

Chief of IT Engeering

Dr. Tianlong Hao

Chief of Medicical Chemistry

Dr. Guozhen Wu

Chief of Biological Science

Dr. Chaojun Gong

Chief of Suzhou R&D

Ms. Hua Yang

Chief of Operating Dept