FORM BIO FOR VECTOR DESIGN

Explore Your AAV Vector Design Space

Broaden your vector design horizons using intuitive tools that harness AI/ML models trained on AAV vector nucleotide sequences.

Design for Safety

Numerous studies have shown immunogenicity of empty capsids in humans (ref 1 & 2). Researchers have several avenues to reduce the innate immunogenicity of vector plasmids. Form Bio facilitates in silico vector design iterations to enhance drug safety by minimizing empty and partial capsids, predicting CpG islands, assessing truncation propensity and evaluating secondary and tertiary structures—thus mitigating adaptive immune responses.

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FDA Draft Guidance on AAV-Based Gene Therapy Safety

In 2020, the FDA’s Cellular, Tissue, and Gene Therapies Advisory Committee (CTGTAC) shared a report and draft guidance* on safety issues for AAV-based gene therapies. In its report the FDA singled out the importance of screening AAV-based gene therapies for empty capsids.

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Design for Efficacy

Selection of promoters and other regulatory elements is crucial in the development of successful gene therapy candidates.

These selections can significantly impact transduction into target tissues, as well as transcription and translation processes. Form Bio streamlines this process through in silico construct prediction, offering clearer insights into vector design performance within in vitro models and facilitating the progression of the most promising designs to mouse models.

Design for Manufacturability

Many drug companies use crude methods for harvesting rAAV, resulting in a typical capsid fill rate of 5-30% for the therapeutic transgene. This practice leads to reduced viral vector yield and elevated cost of goods (COGS), necessitating extra purification steps to remove empty and partially filled capsids (ref 3).

Form Bio empowers cell and gene therapy process development scientists to simulate the impact of simultaneously altering multiple process parameters and predict cell titer and other critical quality attributes in silico before investing a single dollar in bioreactor runs. This approach has resulted in both cost and time savings by minimizing trial-and-error during process development.

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Design for Expression

Protein expression is never a guarantee and often makes the difference between therapeutics that work and those that don’t. Form enables you to carefully analyze mRNA for transcription and translation efficiency—making it possible to predict therapeutic protein production. This includes helping you understand the impact of regulatory, or other non-coding elements, swapping of mRNA expression and identifying sequence motifs that can affect expression.

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in AAV Research

Reference 1

Molecular Therapy, 2014: “Empty virions in AAV8 vector preparations reduce transduction efficiency and may cause total viral particle dose-limiting side effects”

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Reference 2

FDA+ASGCT Summit, January 2013: 

“Immune Response to AAV vectors”

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Reference 3

FDA CBER Session: “Advanced Manufacturing and Analytical Technologies (AMAT) for Regenerative Medicine Therapies (RMT) Workshop, 2023”

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Key Vector Design Questions
Form Bio Can Help Answer

What is the truncation propensity 
of my candidate construct?

Will my construct generate CpG islands?

What are the most likely sites of 
truncation on my construct sequence?

Why isn’t my vector plasmid 
expressing as expected?

Which promoter and other regulatory
elements should be selected?

Which sites  on the construct give rise 
to 2° and 3° structures, CpG islands?

What questions are you interested in answering?

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Key Benefits for Vector Design Teams

Evaluate up to billions of vector designs in silico, exceeding wet lab feasibility

Pre-optimize vector designs 
to enhance manufacturability

Mitigate immunogenicity 
and minimize toxicity risks

Evaluate different regulatory 
elements for improved efficacy

Accelerate development timelines, reduce costs and 
establish new IP

FORMsightAI models are continuously validated against wet lab data with CDMO and academic partners

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Product Characterization

Fully understand constructs with automated AAV characterization reporting

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Biomanfuacturing Simulation

Predict manufacturing results relating to truncations and other issues

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Comparative Analysis

Compare an array of
constructs with different design characteristics to find the most promising versions

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Generative Optimization

Enhance constructs to generate de novo designs with the best predicted yield, efficacy and safety characteristics

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Get Your Therapeutic Candidate to Market Faster

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