MedAI: Explore Therapeutic Antibody Discovery and Development for Disease Treatment

Bio-drugs are more extensively used in disease treatment, especially in the past decade. On December 22, 2020, MedAI, an expert of AI-assisted R&D research company, announces that it now provides AI-driven solutions for the development of therapeutic antibodies, which could be used for the treatment of pathologies such as oncology.

The introduction and application of AI would greatly help scientists and researchers find solutions in a faster and more precise way, and at the same time help reduce the R&D costs.

“The objective of MedAI is to propose a software suite that can create a formal approach of antibody development,” commented the representative speaker from MedAI. “We believe with AI system, the risks of failure will be decreased, the duration of pre-clinical steps will be shortened, and the intellectual protection will also be strengthened.”

In short, the protein or antibody drug discovery and development is the process of identifying new therapeutic antibodies to combat different diseases. These therapeutic antibodies can be full length antibodies, bispecific antibodies, antibody fragments, or others. Conventional approaches would take two to three years to finish the antibody discovery and pre-clinical development process, while MedAI can accomplish it in a few weeks owing to its technologies based on artificial intelligence (AI) and machine learning (ML).

Generally, the therapeutic antibodies discovery process entails the following steps:

Therapeutic Antibodies Discovery Process

Target Identification and Validation

Antibody Lead Generation

Antibody Lead Optimization

Antibody Lead and Functionality Analysis

Antibody Production and Preclinical Development

Preclinical Research

Clinical Phase

The featured technical services driven by Artificial Intelligence at MedAI:

Affinity Maturation

High affinity and selectivity are critical issues for antibody therapeutic capacity. It is critical to be able to understand how certain amino acid substitutions will change the binding energy (affinity maturation). Various different mutagenesis strategies have proven useful to enhance the affinity of candidate therapeutic antibodies.

Immunogenicity Assessment

Immunogenicity testing assays provide a way to measure the potential immune responses of biologics and biosimilars. Also, MedAI’s AI platform has a range of proteins to screen and to determine which are more likely to progress through the development process.

Antibody De Novo Design

De novo design of antibodies binding specific epitopes could greatly accelerate discovery of therapeutics as compared to conventional immunization or synthetic library selection strategies. MedAI’s AI-driven platform utilizes molecular simulation technologies to provide antibody De novo design.

For more information about therapeutic antibodies discovery and development at MedAI, please visit

About MedAI

Fully aware of the difficulties and challenges faced by the research and healthcare industry in drug discovery, MedAI has newly developed an AI-powered drug discovery platform, which can greatly facilitate scientists and researchers’ work, and help them more efficiently and wisely make choices in drug discovery and development attempts. Ever since its founding, MedAI has been known for its expertise in applying AI into drug discovery, personalized healthcare and various other medical applications.

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