AI-based One-stop Antibody Discovery Platform

As a world-leading service provider of antibody development and engineering, Creative Biolabs has combined artificial intelligence, big data, and machine learning to generate a novel artificial intelligence (AI)-powered computational antibody drug discovery platform to predict antibody-antigen binding and provide antibody drug candidates. This platform has been considered as an attractive strategy for producing human antibodies with high specificity and affinity.

AI-based One-stop Antibody Discovery Platform

Step 1 - AI-algorithm Development

Creative Biolabs gathers published antibody usage data from journals, partners, patents to generate a large, customized proprietary data set, based on which, we create an algorithm capable of computationally generating, screening, and optimizing hundreds of millions of therapeutic antibodies. Our monthly-updated machine learning algorithm is able to rapidly screen for therapeutic antibodies with a high probability of success.

AI-based One-stop Antibody Discovery Platform

Step 2 - Antibody Candidates Generation

Our AI-algorithm allows prediction of antibody-antigen binding based solely on the primary structure of the proteins, and harness developments in cell-free protein synthesis technology that enable the high-throughput generation of a large, customized proprietary antibody cluster. The submitted antibody sequences maximize the antibodies’ therapeutic potential while minimizing safety and manufacturing risks.

AI-based One-stop Antibody Discovery Platform

Step 3 - Antibody Sequence Optimize

Through our AI platform, we can quickly and efficiently optimize the existing antibodies via computational algorithm, such as affinity, solubility, cross-reactivity, manufacturability, immunogenicity, specificity, stability.

AI-based One-stop Antibody Discovery Platform

Step 4 - Antibody Production

Creative Biolabs offers antibody development and production services with different antibody formats (Fab, scFv) and flexible strategies (hybridoma, phage display, B lymphocytes sorting). In addition, AI technology can help us discover diverse and rare antibodies.
AI-based One-stop Antibody Discovery Platform

Step 5 - Antibody Characterization

At Creative Biolabs, antibodies can be completely characterized using a variety of techniques for the reproducible and safe production, including but not limited to:
  • Affinity measurement
  • Peptide mapping
  • Disulfide bond mapping
  • Stability evaluation
  • Paratope mapping
  • Epitope mapping
AI-based One-stop Antibody Discovery Platform

Step 6 - Antibody Validation

Creative Biolabs provides comprehensive antibody functional assays to in-depth validate your antibody candidates. The therapeutic effects of mAbs and their derivates (e.g., antibody drug conjugates (ADCs), and Fc-fusion proteins) can be mediated by different mechanisms, including but not limited to:
  • Direct blocking of ligand-receptor interaction
  • Agonist activity on a receptor to trigger downstream signaling
  • Antibody-dependent cellular cytotoxicity (ADCC)
  • Antibody-dependent cellular phagocytosis (ADCP)
  • Complement-dependent cytotoxicity (CDC)
  • Direct cell killing by induction of apoptosis
  • Inhibition of enzyme activity

Why Choose AI?

  • AI can typically generate 10 times more antibody sequence clusters than a laboratory-based approach alone.
  • AI expands the diversity that leads to the discovery of new binding modalities and potentially new therapeutic modes-of-action.
  • AI creates optimized antibody sequences to increase the success rate.
  • AI helps CROs to become more competitive by increasing the hits, diversity, and delivery speed.

Implementing deep learning to predict antibody target specificity. Fig.1 Implementing deep learning to predict antibody target specificity. (Mason, 2019)

To help our clients develop a safe and effective human antibody, Creative Biolabs is continuously exploring novel AI technologies and phage display libraries for antibody development solutions. We are committed to helping our clients to shorten the antibody development timeline in a cost-effective manner. If you are interested in our services, please do not hesitate to contact us for more details.


  1. Mason, D. M.; et al. Deep learning enables therapeutic antibody optimization in mammalian cells by deciphering high-dimensional protein sequence space. bioRxiv. 2019, 6(2).
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