0:20
Sebastian, that was a great talk. I really appreciate that. Let's continue on that note and see what we have here. I'll certainly talk about transposase. It was a good introduction, but I think we want to start by giving the context of why we're here and the interesting science going on.
0:55
Over the last decade, the top ten drugs in 2010 were all small molecules. Now, in 2020, the industry has shifted from chemistry to biology. This change fundamentally affects all the CMC, manufacturing, and processes we have built up. Chemistry manufacturing is very different from biology. Manufacturing biologics is complicated, its slow and expensive. From identifying your molecule to manufacturing it, it takes a long time and there are regulatory uncertainties. With biology we don’t have the tools yet to make it as predictive as chemistry.
1:56
The drugs that have come to the forefront in recent years are amazing and efficient, but the manufacturing pipeline needs to keep up. Biology is complicated, not just single steps like organic chemistry. It takes a long time to go from identifying a molecule to manufacturing it. It's expensive, with regulatory uncertainties.
2:50
We don't have the tools to make biology as predictive and consistent as chemistry. That's why we're here, to discuss how we brought transposon technology to make the production pipeline more efficient. This is in the context of digitizing and standardizing processes to make drugs more affordable and available to patients.
3:36
This is the third or fourth talk on transposons. Regarding our Leap-In platform, we initially started with CRISPR 5 -10 years ago, but found it to be a knockout platform rather than a knock-in one, with many legal issues. We realized that transposons and the Leap-In platform provided consistent multi-copy integration for fast protein production. These integrations are genetically stable and lead to high yields.
5:06
Transposons have evolved for 4 billion years to be stable. Once integrated, they never leave, creating a homogeneous population. This platform allows for predictable engineering on the genome. It has been approved by regulatory bodies in Europe, the US, and China.
5:53
Atum's platform started with gene optimization and codon optimization i.e. the gene GPS which allows you to identify different variables that control expression as a functional and translational velocity and how you can manipulate that. We showed that there was no correlation between commonality of a codon and expression yield. But we found that manipulating codon bias can control expression by orders of magnitude. This involves digitizing sequence information and using machine learning tools to optimize variables affecting expression.
7:10
We've done a lot of work on vector optimizations, using digital information to control expression. This includes elements like UTRs, promoters, and ribosome binding sites. We apply machine learning tools to biology, treating DNA as digital information. We the same with vectors and protein engineering.
8:02
Transposons work through a cut-and-paste mechanism (carried out by the transposase enzyme), integrating into open chromatin. This leads to multiple copies (typically up to 50) and high yields. These are all single copy integrations and you get multiple insertions. Compared to random integration, transposase provide clean, consistent cassettes across the genome.
10:02
With transposons, the majority of clones are good expressors, unlike random integration which produces many poor expressors. With transposons your population is very homogenous and consistent. This consistency is crucial for regulatory approval and efficient production.
11:18
During the COVID-19 pandemic, there was pressure from customers and regulatory bodies to speed up the production of biologics. The Leap-in Transposase platform allowed for rapid GMP manufacturing of COVID-19 monoclonals, reducing the timeline from over a year to 4.5 months. This is because you can sample directly from the pool and make it into clinical material. With the Leap-In platform we took 2,000 litres in 3 months from transfection to first in human, this shaved off years from the typical timeframe for producing antibodies.
12:51
This platform has been used for rapid implementation, allowing for clinical material production in a fraction of the usual time. It has been widely accepted, with 24 IND filings and active licensees across the globe.
14:08
The Leap-in platform is well-established for antibodies and is now being used for bispecifics, trispecifics, and other complex molecules. It allows for precise control of genetic elements, leading to efficient production. In terms of taking pools to market, for tox materials the majority agree with taking pool material to tox but only one third of the survey takers said that they expected to take pool material to clinical material.
16:03
With transpososns you can control the design of your genetic space more specifically. We can set up multiple pools in parallel, testing different elements of different ORFs to find the best-performing ones. This speeds up the development process and ensures high yields.
17:01
We can play around with the parameters and look at codon choice, mRNA structure and poly-A-signals etc. We capture data from each project to look at relationship between different variables , using it to improve our machine learning algorithms. This helps us understand the correlation and causality of different variables affecting expression.
18:25
For example, a customer (Hengenix) achieved 6 grams per litre with a bispecific molecule, with 97% correct assembly. This robust market adoption shows the platform's effectiveness.
19:09
We've also worked on using the Leap-In Transposase platform for gene reduction technologies, knocking out specific pathways to improve production. This allows for rapid testing of different host cell lines including a miCHO-GS, miFuc and miLPN cell lines The miFuc is host cell agnostic and vector based. miLPN is used for custom projects. miCHO-GS is K1 derived and GS deficient
21:20
We've used transposons to knock out fucosylation pathways, improving ADCC signaling. This demonstrates the platform's versatility and effectiveness. We observe rapid integration of fucosylation. We have a custom project with a cytokine therapeutic, exploring the inhibitory pathways to knockout.
23:14
This is the current cell line that produces this particular cytokine. After putting it into a couple of different leap in constructs with different promoters and different systems, we upped that by an order of magnitude and then coming in with a second transposon. Now that knocks out different regulatory features.
23:36
So gives you that capacity of really being able to manipulate this on multiple different levels using multiple different orthogonal transposons.
23:47
In cell therapy, we've used transposons to carry large genetic payloads, enabling high consistent expression. This is crucial for manipulating genetic information in cell lines.
24:55
Our collaborators at the University of Minnesota used Leap-in to improve AAV manufacturing, showing the platform's potential in gene therapy.
25:27
With multiple orthogonal transposons, we can manipulate genomes on a new level, enabling complex genetic engineering.
26:01
We'll discuss more about orthogonal systems in an upcoming webinar. Thank you for your time. Science is fun, and we look forward to your questions.
