Computational Biology Accelerating Cell and Gene Therapy Development with Kent Wakeford Form Bio

Empowered Patient Podcast

Kent Wakeford, Co-CEO and Co-Founder of Form Bio, a company that provides computational solutions to scientists who are focused on cell and gene therapy to accelerate drug discovery and development, reduce costs, and ultimately make treatments more affordable for patients. Form Bio's in silico platform utilizes computational biology tools, bioinformatics, machine learning, and AI to process large amounts of open source data to provide insights to scientists to help them solve critical challenges. They are committed to supporting the rare and ultra-rare disease community and offer their tools to patient advocacy groups for free.

Kent explains, "There are a lot of bumps. The production, scaling up, and cost of gene therapies are major obstacles to their widespread success. As we’ve seen in small molecule, target identification is one of the key challenges, and there’s been a lot of breakthroughs in AI, and computational analysis that have helped scientists find those targets."

"In cell and gene therapy, it’s different. It’s a little bit easier to find the gene of interest that you want to try and work on. Still, it is harder to design and ultimately develop the gene therapy that can scale, have limited immunotoxic impact, and provide the therapeutic outcome at the right place and strength in the body."

"Training a platform is one of the most critical areas for an AI or a computational company. Our team of incredible AI scientists from some of the greatest academic labs went out and pulled together all the available data in the open-source market. And to be honest, there’s a lot, but it’s not that helpful when you’re trying to get very specific scientific outcomes."

"And so, we partnered with a number of leading academic institutions where we commissioned and paid for scientific research that produced data that we can then train models on. We looked at specific genes of interest for major therapeutic areas and then looked at all the regulatory elements to understand the different interactions. We can understand if you were to change one element of this, what happens to the rest of the therapeutic? What happens to expression, what happens to tropism, what happens to the packaging and manufacturability of that drug?"

#FormBio #AI #ML #ComputationalBiology #DrugDiscovery #ClinicalTrials #DrugDevelopment #CellTherapy #GeneTherapy #RareDiseases

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