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Drug Discovery Service

Welcome to CD ComputaBio, your partner in revolutionizing drug discovery through cutting-edge artificial intelligence technologies. Our advanced AI-driven solutions empower pharmaceutical companies, biotech firms, and research institutions to accelerate the drug development process, saving time and resources while maximizing success rates. With a commitment to excellence and innovation, we offer comprehensive AI-aided drug discovery services that are tailored to meet your specific needs.

AI-Powered Technologies in Drug Discovery

In the realm of drug discovery, harnessing the power of artificial intelligence has become a game-changer. AI algorithms, machine learning models, and predictive analytics have significantly enhanced the efficiency and effectiveness of drug development pipelines. By leveraging massive datasets and employing sophisticated algorithms, AI can unlock valuable insights, predict compound activities, optimize lead candidate selection, and streamline the entire drug discovery process.

Our Services

Fig 1. DDR analysis

Drug-Drug Relationship Analysis

Drug-drug relationship (DDR) analysis is an important aspect of pharmacovigilance, clinical research, and personalized medicine. We focus on modeling how different drugs interact with each other in solution. These interactions may alter the effectiveness and safety of the agents involved.

Fig 2. Drugs repurposing

Repurposing Existing Drugs

Relying on CD ComputaBio's AI-powered platform, with the help of natural language processing and deep learning abilities, our experts' team can extract knowledge and put forward new hypotheses from the scattered and disordered mass information.

Fig 3. Drug-disease interaction analysis

Drug-Disease Relationship Analysis

We have developed different methods for identifying candidate indications of existing drugs considering types of interactions between biomolecules based on known drug-disease associations.

Fig 4. Target identification of drug discovery

Target Identification

With the rapid development of AI and machine learning technologies, unstructured information from omics, text and image analytics, public databases, systems biology can be integrated. Our expert team can help clients extracting knowledge from a multitude of resources and thus enabling science-based decisions.

Network-based Methodologies for DTI Prediction in silico

Fig 5. Network-based methodologies

Our Capabilities

  • Hit Identification
    At CD ComputaBio, we leverage the power of computational approaches to streamline hit identification, reducing the need for resource-intensive experimental screenings while enhancing the quality of identified hits.
  • Hit-to-lead
    With a relentless commitment to innovation and excellence, we offer a comprehensive suite of services that leverage computational approaches to accelerate drug development processes.
  • Lead Optimization
    At CD ComputaBio, we specialize in providing cutting-edge computer-aided lead optimization services to accelerate drug discovery and development processes.

Our Advantages

Structure-based drug discovery

By utilizing state-of-the-art computational techniques, we analyze the high-resolution 3D structures of target proteins and complexes. Our advanced AI tools assist in accurately predicting the binding sites, essential for the identification of potential drug candidates.

Our Advantages

Ligand-based drug discovery

Our ligand-based drug design is designed to integrate seamlessly with your existing workflows. Whether you're a biotech startup or a large pharmaceutical company, our platform provides flexible and scalable solutions that cater to your unique research and development needs.

At CD ComputaBio, we understand that every drug discovery project is distinct, with its own set of challenges and goals. That's why we offer customized AI-aided solutions tailored to the specific needs of our clients. Whether you require target identification, lead optimization, ADMET profiling, or combination therapy design, our team of experts is here to collaborate with you and deliver personalized strategies that drive success. If you are interested in our services or have any questions, please feel free to contact us.

Reference:

  • Jiang M, Niu C, Cao J, et al. In silico-prediction of protein–protein interactions network about MAPKs and PP2Cs reveals a novel docking site variants in Brachypodium distachyon[J]. Scientific reports, 2018, 8(1): 15083.

Services

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