Antibody Selection Using Structural Parameters for mAb Stability
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Solution Overview
Problem
Existing methods struggle to predict and optimize the viscosity, clearance rate, and stability of monoclonal antibodies (mAbs) for stable, low-viscosity formulations suitable for subcutaneous delivery, which is crucial for at-home use and long plasma half-life, especially for chronic conditions like rheumatoid arthritis.
Innovation Solution
Utilizing sequence-based structural parameters and molecular dynamics simulations to predict and differentiate mAbs' properties such as viscosity, clearance rate, and stability, enabling efficient selection and manufacturing of mAbs with desirable attributes through computational tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If high concentrations of mAb are used in liquid formulation for subcutaneous delivery, then the volume required for drug delivery is reduced, but the viscosity increases making the solution difficult to manufacture and administer
Solution Approach 1:
The patent applies parameter changes by modifying the physical and chemical properties of the mAb molecule itself to achieve lower viscosity at high concentrations. Specifically, the invention identifies and modifies structural parameters of the mAb (such as charge distribution, hydrophobicity, and molecular shape) to optimize solution viscosity while maintaining high concentration formulation, enabling efficient subcutaneous delivery
2Duration of action of stationary object
If mAb is formulated for stable shelf-life, then the chemical and physical degradation is minimized, but the plasma half-life and clearance rate may be affected
Solution Approach 1:
The patent applies preliminary action by predicting and optimizing mAb properties before clinical development using computational methods. The invention uses in silico models to predict plasma half-life and clearance rate based on mAb structural characteristics, allowing researchers to select candidates with optimal pharmacokinetic properties before manufacturing and clinical testing, thereby ensuring both stable shelf-life and appropriate plasma half-life
Solution Approach 2:
The patent replaces traditional empirical trial-and-error methods with computational prediction models. The invention uses computer-based simulations and algorithms to predict mAb stability and pharmacokinetic properties, substituting wet-lab experimentation with in silico modeling to identify optimal candidates with desired shelf-life and plasma half-life characteristics
3Measurement precision
If traditional empirical methods are used to evaluate mAb properties, then the assessment is based on actual measurements, but the time and resources required for evaluation are excessive
Solution Approach 1:
The patent applies copying by creating virtual replicas of mAb molecules and their behavior through computational models. The invention uses in silico simulations to copy and predict the physical and chemical properties of mAbs, allowing researchers to evaluate multiple candidates rapidly without conducting extensive wet-lab experiments for each candidate, thus reducing evaluation time while maintaining prediction accuracy
Data Source
AI summary
Apparatus, systems, computer-readable media, articles of manufacture and methods for selecting an antibody. Apparatus, systems, computer-readable media, articles of manufacture and methods for producing the selected antibody. The selecting may include determining one or more physiochemical characteristics of the antibody. The determining may be based on antibody structural parameters.