Detailed analysis of manufactured drug product, including proportion of full viral genomes to non-therapeutic packaged species.
Assess the quality of bioreactor runs, identify unknowns
Determine proportion of full, partial and empty capsids from bioreactor samples
Analyze sequence variants and alignment to reference sequences
FORMsightAI solves your replication & packaging challenges to mitigate manufacturing risk.
Rapidly evaluate hundreds of millions of construct combinations in silico, comparing the safety, yield and expression of multiple candidates with different regulatory elements.
Compare combinations of promoters, ITRs, introns, backbones, RepCap, polyA elements and more
Rank constructs for triple transfection, CpG islands, GC content, transcription and translation, and manufacturability
Design for improved safety, efficacy and manufacturability and evaluate the impact of substituting regulatory elements
Multi-candidate comparison enables you to integrate large scale in silico modeling into your existing R&D process to hone in on the drug candidate most likely to succeed in the lab.
Formation of CpG islands is a reported trigger mechanism for immune response to many therapies. Form helps you identify CpG islands and score associated risks of potential immunotoxicity such as empty and partial capsids.
Score potential immunotoxicity risks associated with CpG islands, empty and partially filled capsids and other viral genomic patterns.
Analyze GC content and determine sites for CpG formation
Leverage powerful AI/ML models to predict propensity of full, empty and partial capsids
FORMsightAI enables your time to identify possible immunotoxicity effects and likelihood when making key changes to therapeutic construct design.
For a comprehensive and holistic optimization of construct for safety, efficacy and manufacturability engage with Form Bio to use our AI/ML expert services to optimize the CDS region.
Optimize CDS region of your construct for lowest truncation propensity and highest manufacturability
Optimize construct for gene expression and immunogenicity
Create derivative IP with our generative LLM AI models for identifying optimal versions of your starting construct.
By using FORMsightAI’s sophisticated models trained on vast public and private datasets, therapeutic developers can dramatically reduce the time and cost of drug development.
by avoiding costly bioreactor runs on suboptimal construct designs
by minimizing design inefficiencies that prolong manufacturing trial-and-error
by predicting and optimizing capsid fill proportion with therapeutic drug product to streamline production scaling
by filing fresh patents on optimized construct derivatives generated with FORMsightAI
As a Form Bio customer, we are thrilled with the uniquely valuable AI-driven insights they’ve contributed to our research and development efforts. By working closely with this world class team and cutting edge technology, we can clearly see that applying innovative AI solutions to pre-clinical cell and gene therapy development offers exciting potential for CGT companies’ economics, market timing and ability to impact human health.
Deficiencies in replication and packaging of genomes into assembled capsids cause manufacturing efficiency and therapeutic yield to plunge.
These inefficiencies account for millions of dollars in capital and months/years of manufacturing trial and error per pipeline candidate.
Solving for replication and packaging issues in construct design addresses a multi-billion dollar problem for the cell and gene therapy industry.
Running a therapeutic construct through a bioreactor can be highly unpredictable. This guessing game can cost CGTs millions in manufacturing costs and months or years in time-to-market.
Gene therapy companies, more than ever, can’t afford to waste time and capital on manufacturing scale up trial and error.
Failure to optimize therapeutic design for manufacturing can result in lower yields and higher costs-per-dose, making therapies less accessible for patients and squeezing margins for CGT companies.
In 2021, 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 and FDA draft guidance, CTGTAC singled out the importance of screening AAV-based gene therapies for empty and partially filled.