Form Bio Resources

Accelerating AAV Vector Development with AI

In this webinar we'll unveil the latest breakthroughs in AI modeling for evaluating and optimizing vector designs to reduce discovery timelines from years to weeks! Discover how Resilience and Form Bio teamed up to apply cutting-edge in silico techniques, accelerating the vector design process, while producing a safer and more manufacturable vector.

2024-09-25

Recent Advancements in AAV Production Process for Gene Therapy Manufacturing

Jill Roughan, PhD

August 6, 2024

2024-08-06

Explore the AAV production process for gene therapy manufacturing, as well as the techniques and efficiency improvements to enhance AAV payload purity.

AAV Candidate Testing & Selection—A New Solution for Accelerating Vector Design

In silico techniques for generating and screening libraries prior to in vitro testing provides actionable insights, guiding researchers towards candidates with the highest PoS.

2024-08-02

AI/ML Optimization Reduces AAV Discovery Timeline from Years to Days

AI/ML optimization can reduce AAV discovery timelines from years to days, identifying an optimal vector design quickly and resulting in 91% full capsids.

Optimization of the CDS Using an AI/ML Model Outperforms an Open-Source Codon Optimization Tool by Improving Enzymatic Activity by 20%

AI/ML optimization of the coding sequence (CDS) can outperform open-source codon optimization tools by increasing mRNA expression by 24% and increasing enzymatic activity by 20%.

Reducing the Risk of Immunogenicity Using an AI/ML Model

AI/ML models can reduce the immunogenicity risk of %CpG islands through sequence optimization, while maintaining a consistent %GC content.

AI/ML Optimization of Coding Sequences Reduces Genome Truncations in AAV Vectors

AI/ML optimization of the coding sequence (CDS) of a gene-of-interest (GOI) can de-risk AAV manufacturing by reducing partially filled AAV capsids.

AI/ML is Able to Reliably and Reproducibly predict AAV Genome Truncation

AI simulation can reliably and reproducibly predict AAV genome truncation to help increase production lot yield and lower manufacturing costs.

Improving AAV Manufacturability with AI/ML Simulation to Reduce Genome Truncations

Improve AAV manufacturability with AI/ML in silico techniques to identify the best performing vector design for lead candidates.