Protein/Antibody Development

Protein/Antibody drug discovery and development is the process of identifying new therapeutic antibodies to combat different diseases. These antibody therapeutics can become in a number of different formats, such as full length antibodies, bispecific antibodies, antibody fragments, and more. Conventional approaches for the discovery and pre-clinical development take two to three years, CD ComputaBio’s technologies, based on artificial intelligence (AI), machine learning (ML), allow shrinking this time to a few weeks.

Figure 1 Protein/Antibody Drug Development Overview

Therapeutic Antibodies Discovery Process

Target Identification and Validation
Molecular targets are generally receptors or antigens expressed on the outside of a cell. Biochemical methods, genetic interactions, and computational inference are common methods used to identify specific target, revealing the antibody-antigen binding mechanism.
Antibody Lead Generation
In the phase of antibody lead generation, validated molecular targets are used as antigens to initiate an immune response in a host animal to generate therapeutic antibody candidates.
Antibody Lead Optimization
Antibody-based drug candidate is modified to increase their effectiveness, affinity, and to diminish immunogenicity. In this stage, rodent monoclonal antibodies are converted to their humanized forms.
Antibody Lead and Functionality Analysis
This is an important part of the discovery stage of therapeutic antibody discovery and development. Antibody lead and functionality analysis include in vitro and in vivo testing to further evaluate potential drug candidates. It’s necessary to check their feasibility and efficiency.
Antibody Production and Preclinical Development
This is the final stage of preclinical development, where antibody-based drug candidate selection and recombinant expression are conducted.
Preclinical Research
The safety of the lead is checked before clinical trials in this phase. Then the new therapeutic antibody drug is manufactured for clinical testing.
Clinical Phase
Assess the safety and efficacy of the drug and how it compares to the current treatment options, until finally tested through clinical trials and approved for distribution to patients.

Technical Services Driven by Artificial Intelligence

Artificial intelligence is capable of reducing high costs in drug research and development as it finds solutions faster and with precision. CD ComputaBio implements AI-driven solutions for the development of therapeutic antibodies, as bio-drugs are used in an increasing number of pathologies, including oncology. CD ComputaBio’s objective is to propose a software suite that creates a formal approach of antibody development, reducing the risks of failure and the duration of pre-clinical steps, as well as strengthening intellectual protection.