ElevateBio

Powering the creation of cell & gene therapies at a speed the world deserves.

Gene Editing & Discovery

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Drug Target Review recently published a byline article featuring LETI-101, Life Edit’s development candidate for Huntington’s disease (HD). HD is a rare, inherited neurodegenerative disorder affecting approximately 41,000 people in the United States, with another 200,000 at risk. LETI-101 uses Life Edit’s CRISPR technology for allele-selective editing, offering a novel approach to potentially treating this devastating condition. What sets LETI-101 apart is its precision targeting strategy. Rather than directly targeting the disease-causing CAG repeat expansion, LETI-101 targets single nucleotide polymorphisms (SNPs) that allow us to distinguish between mutant and healthy copies of the gene.

“A transformative aspect of our LETI-101 approach is that it’s designed as a one-time treatment that could provide long-lasting benefit without the need for repeated administration,” explains Dr. Amy Pooler, SVP of Research & Development at Life Edit. “Unlike other therapeutic modalities being developed for HD that would require ongoing treatment to maintain efficacy, our gene editing therapy is intended to make a permanent, precise modification to the DNA itself.”

Read the full article “Allele-selective gene editing: a breakthrough in Huntington’s disease treatment” on Drug Target Review.

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In March 2022, Beam Therapeutics and ElevateBio embarked on a groundbreaking partnership to manufacture BEAM-101, an investigational base editing therapy for sickle cell disease. The therapy represents a novel approach to treating this devastating condition by mimicking genetic variants found in individuals with hereditary persistence of fetal hemoglobin. To advance this potentially transformative treatment to clinical trials, Beam turned to ElevateBio’s expertise in cell and gene therapy production, combining rigorous quality standards with the ability to move at unprecedented speed.

The Challenge

Manufacturing gene-edited cell therapies presents unique complexities beyond traditional cell therapy production. Base editing, like all gene editing cell-therapy technologies, requires careful process control to maintain editing efficiency and cellular viability. Traditional manufacturing approaches, optimized for other cell therapies, needed significant adaptation for this novel technology. Additionally, Beam faced urgent timeline pressures – they had identified potential clinical trial participants and needed to accelerate their manufacturing readiness without compromising quality.

“Base editing represents a new frontier in genetic medicine, and its manufacturing demands match that innovation,” says Brian Riley, chief manufacturing officer of Beam. “We needed a partner who could not only handle the technical complexity but move at the speed required to help us reach waiting patients.”

Pioneering Base Editing Technology

Beam’s proprietary base editing technology allows for precise genetic modifications without making double-stranded breaks in the DNA. BEAM-101 leverages this precision to mimic genetic variants seen in individuals with hereditary persistence of fetal hemoglobin – a natural condition that protects against the effects of sickle cell disease. This approach represents a potentially transformative treatment option, offering hope for a one-time therapy that could provide lasting benefit to patients.

Elevate Bio

BaseCamp’s End-to-End Manufacturing Capabilities

ElevateBio BaseCamp is a state-of-the-art process development and cGMP manufacturing facility designed to accelerate the development of cell and gene therapies. BaseCamp provides comprehensive manufacturing solutions, combining advanced technical capabilities with experienced program management to support partners from early development through clinical trials. The facility’s integrated approach to process development and manufacturing enables rapid technology transfer and scaling of complex genetic medicines. This comprehensive platform enables rapid process optimization and seamless technology transfer, crucial capabilities for novel therapeutic modalities like base editing.

The Approach: Innovation at Speed

Beam partnered with ElevateBio’s BaseCamp to define a plan for clinical supply, which ultimately led to an accelerated tech transfer to support BEAM-101’s path to clinical trials.

BaseCamp’s comprehensive strategy combined technical expertise with dedicated program management. The seamless integration of program management and the Manufacturing, Science and Technology (MSAT) group provided end-to-end oversight for technology transfer activities, while parallel manufacturing readiness and analytical method transfer activities compressed traditional timelines. The team leveraged a risk-based approach along with input from the process development group for successful translation of the novel base editing process into GMP manufacturing. This was supported by an accelerated training and qualification program that maintained the highest quality standards.

“We recognized that standard technology transfer approaches would not meet the timeline requirements,” explains Mike Paglia, Chief Technology Officer, ElevateBio BaseCamp. “Our team developed an integrated strategy leveraging our development, manufacturing and quality teams that maintained the highest level of quality while dramatically accelerating the timeline of the technology transfer of the Beam-101 process to ElevateBio BaseCamp.”

Michael Paglia,
Chief Technology Officer, ElevateBio BaseCamp

The results were immediate. Within four weeks, the teams completed their first training run. A second run followed within a month, and engineering runs began shortly after. This unprecedented speed came without sacrificing thoroughness – the teams transferred nine critical assays, completed comprehensive qualification, and maintained rigorous quality standards throughout.

Technology Innovation

The partnership demonstrated the value of close collaboration between therapy developers and manufacturing partners in establishing robust production processes. The team’s experience in transferring and scaling complex cell therapy processes helped create effective workflows and quality control approaches that supported the successful manufacture of BEAM-101.

Results: Breaking New Ground

The partnership achieved several breakthrough milestones in manufacturing excellence. Most notably, the team completed technology transfer two months ahead of schedule – while maintaining exceptional quality standards. The manufacturing process demonstrated consistent editing efficiency and reliable production parameters, establishing a repeatable model for future programs.

Key achievements include:

  1. Completion of comprehensive tech transfer ahead of schedule.
  2. Achieving successful site-to-site comparability to Beam’s in-house manufacturing facility
  3. Proudly supplying patient doses for Beam’s BEACON Phase 1/2 clinical trial evaluating BEAM-101 in adult patients with sickle cell disease

Beyond these immediate results, the collaboration delivered strategic value that extends well beyond BEAM-101. By working with ElevateBio, Beam successfully demonstrated the manufacturing scale-up of its base editing technology – a critical milestone in proving the commercial viability of any novel therapeutic platform. This demonstration provides a blueprint for future development programs across Beam’s pipeline, potentially accelerating the timeline for bringing additional base editing treatments to patients.

“The speed and quality of this collaboration exceeded our expectations,” says Giuseppe Ciaramella, Ph.D., president of Beam. “BaseCamp didn’t just manufacture our therapy – they helped us establish a blueprint for base editing manufacturing.”

Giuseppe Ciaramella, Ph.D.
President, Beam Therapeutics

The successful manufacturing of BEAM-101 represents more than one company’s achievement – it demonstrates the feasibility of rapidly scaling novel genetic medicines. As the field of genetic medicine advances, manufacturing remains a critical determinant of success. The manufacturing platform and processes developed through this collaboration create a pathway for future base editing therapies, potentially accelerating the development of treatments for other genetic diseases.

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The recent convergence of artificial intelligence (AI) and biology has spurred remarkable scientific advances, most notably AlphaFold’s ability to predict 3D structures of proteins from amino acid sequences. These advances have been fueled by the availability of data for training AI models and technology capable of processing data faster than ever before, and they demonstrate the power of AI to revolutionize biological research.

Gene editing technologies, especially CRISPR, are likewise revolutionizing the therapeutic landscape with the promise of curing diseases in a single dose by correcting their underlying genetic drivers. Given the myriad diseases that CRISPR could treat, AI is becoming indispensable for delivering on the promise of gene editing.

Life Edit, ElevateBio’s gene editing business, is uniquely positioned at the interface of computational science and CRISPR biology to do just that. Here, we examine why AI is essential to the future of CRISPR discovery, what challenges AI faces in the CRISPR development, and how Life Edit is addressing those challenges to accelerate CRISPR discovery and enable our partners to develop novel and life-changing genetic medicines.

AI is indispensable for future CRISPR gene therapies

The first wave of CRISPR therapies have focused on a small collection of monogenic diseases, such as sickle cell disease, where the underlying cause is a single SNP in a single gene that can be corrected with ex vivo editing of patients’ cells. Developing CRISPR systems to treat these diseases, without the aid of AI, is relatively straightforward with current experimental approaches. The real challenge lies in expanding CRISPR’s application to the thousands of more complex monogenic disorders, as well as the multitude of polygenic diseases involving multiple gene corrections. Treating all these diseases requires development of many custom CRISPR systems, which would take an extremely long time to achieve with conventional approaches.

A key barrier with conventional approaches is that – for reasons researchers do not fully understand – different CRISPR systems are often needed to edit different disease-associated loci; successful gene editing for each disease thus involves the lengthy process of engineering and optimizing both the nuclease and a guide RNA (gRNA) of a given CRISPR system. There is no quick and rational way to effectively predict and design a CRISPR system with the optimal editing window, potency and specificity for a disease – despite the large quantities of experimental data available in the literature and proprietary databases.

These databases are insufficient for the task because the spaces of possible CRISPR protein sequences (based on 20 amino acid letters) and possible RNA sequences (based on four nucleotide letters) are astronomically huge and cannot be fully explored by experimental means alone. We believe AI is well positioned to tackle this problem using large language models (LLMs). Our belief is encouraged by recent AI advances in small molecule drug discovery, where AI models, trained on high throughput screening data, can perform virtual screening to rapidly narrow the number of hits for experimental validation.

Training AI in the language of therapeutics

While LLMs such as ChatGPT represent a major breakthrough in AI’s ability to use everyday human language, AI models for CRISPR nucleases are not quite as developed. Current AI models trained on natural CRISPR sequences from public databases are capable of predicting CRISPR structures and even generating novel systems. However, upon experimental validation, many do not have sufficient editing activity in mammalian cells, and those that do have sufficient activity sometimes perform at a lower level of efficiency than the current benchmark nuclease, SpyCas9. We believe the gap between function and therapeutic utility might exist because bacteria evolved CRISPR to detect and destroy infecting viruses, not edit and correct human genes, so there is no evolutionary pressure to produce CRISPR systems that are efficient in mammalian cells for treating diseases.

To achieve AI models that have therapeutic utility, we need to train the models with a large amount data from wet-lab experiments that are specifically designed for improving editing activity and specificity in disease-relevant mammalian cells. These data should include sufficient information of systematic search in the CRISPR protein and RNA sequence space that can address potential bottlenecks in gene editing inside mammalian cells, which are probably multifaceted and cell- or disease-dependent. AI models can help us find the right systems for the right targets quickly, without having to understand all of the bottlenecks, and these models should be continuously improved by a feedback loop, in which model predictions are constantly evaluated by experiments. Only with therapeutically relevant AI models for CRISPR we will be able to adequately address the challenges of developing CRISPR systems for the vast majority of monogenic and polygenic diseases.

Life Edit’s solutions for bridging the CRISPR gap

Life Edit is an integral part of ElevateBio’s genetic medicine ecosystem of enabling technologies and end-to-end manufacturing capabilities. We’re also distinct in how we work compared to other gene editing companies. We started with the “top-down” approach of building a diverse array of CRISPR nucleases and base editors suitable for treating a wide range of diseases differentiates us in several ways. Now we are focused more on the “bottom-up” approach of discovering and developing CRISPR systems to treat select diseases for our partners and our own therapeutic development programs.

First, we’re not just working with state-of-the-art computation and AI: we’re pushing their boundaries. We know this, because the questions we’re asking some of the technology sector’s AI leaders are stretching their capabilities into new areas.

Second, we have collected and curated our own proprietary protein database, which constitutes a heterogeneous collection of sequences from isolated organisms and metagenomes. The collection contains proteins from large public collections and numerous published studies, along with proprietary sequences from diverse biomes. These data have been unified, annotated, and structured to promote model development toward protein engineering.

Third, we are generating a large body of experimental data, tailored to the therapeutic needs CRISPR aims to address. We’re using these data to build and train AI models that can predict and generate CRISPR systems, customized to the target disease sequences with high activity and specificity. These AI-generated systems should have significantly higher success rates as gene editing therapies than natural systems and could broaden the disease areas treatable with CRISPR.

Finally, the integration of our computational and experimental labs enables a seamless transition for prediction to experimental validation of the AI-generated CRISPR systems. Our structure allows our computational and experimental teams to work hand in hand, framing questions for our AI models in terms of how the output could be tested experimentally. We want to know: Is the model really gaining us something? Is this something we want to do again? We’re testing whether AI-based recommendations are better than human recommendations – something the field believes should be true but hasn’t yet proven generally.

With our AI CRISPR models, Life Edit can serve not only the needs of our own pipeline, but the whole field of CRISPR gene therapy as well through partnerships. With our models and portfolio of validated CRISPR systems, we are the first stop for a company starting a CRISPR gene therapy program; with our enabling technologies and the end-to-end manufacturing capabilities of ElevateBio’s BaseCamp, we are a “one-stop shop” and ideal partner for developing a CRISPR drug.

We can offer partners and clients many flexible options, not just one, for developing and commercializing their gene editing therapies, thus putting more shots on goal as an industry than any one organization could otherwise pursue independently. We are propelling the entire CRISPR gene editing field into the future, to bring these potentially curative medicines to as many patients as possible.

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In all areas of biotech and pharma, there is a never-ending quest to improve the safety, potency, and effectiveness of drug therapies by harnessing the latest scientific and technological advances. Nowhere is this more evident than in the rapidly growing area of cell and gene therapy (CGT) products. These products are becoming increasingly complex as our knowledge of disease biology expands and CGT platforms evolve, offering insights for developing better CGT products and the technologies needed to make those improvements.

In vivo gene therapies provide a simple example of this evolving complexity. This approach typically begins with an adeno-associated viral (AAV) vector: a gene construct (a designed segment of DNA) is engineered into the vector, and the vector is injected directly into the patient. Each subtype (serotype) of AAV targets a different cell and / or tissue type; specific AAV vectors are therefore selected according to the target cell or tissue in the body in which the gene therapy is intended to go.

However, most AAV serotypes target tissue types beyond the gene therapy’s desired therapeutic target. For these therapies, the next level of complexity involves addressing one or both of two possible solutions: narrowing the target range of the AAV vector both by reducing its targeting for non-desirable tissues and enhancing its targeting for the desired tissue; and engineering the vector’s genetic payload for expression only in the desired cell type, so that it is not expressed in non-target tissues after delivery.

Any of these capabilities can be engineered into the viral vector. This is the present state of complexity for most in vivo gene therapies.

In contrast, the complexities are more layered for ex vivo engineered T cell or other immune cell-based therapies, which are in development for cancer and autoimmune disease. These layers include selection of a disease-specific antigen receptor; delivery of the receptor construct into the cell; other engineering to resist the immunosuppressive tumor microenvironment, to enable long term persistence and potency once transferred back to the patient; and large-scale commercial manufacturing of the cell therapy in a GMP-compliant manner.

Moreover, ongoing research in cancer has revealed the variety of mechanisms tumors use to evade the immune system. These advances point the way of improving cell therapies; but they also highlight the need for more sophisticated tools to make those improvements. The increasing interest in developing allogeneic cell therapies or in vivo engineering of antigen receptors and other components – a concept known as “in vivo cell therapy” – adds yet another layer of complexity.

A company aiming to develop and commercialize a cell therapy must address all layers of complexity to be successful. It’s certainly not easy. It’s also expensive, because most drug developers won’t have unfettered access to the full array of technologies needed to develop the product on its own. This lack of access is especially true for gene editing, a technology essential to addressing the multi-layered complexities of tomorrow’s cell therapies.

Continued advancements in the science of T cell therapies

The earliest iterations of cell therapies for cancer were autologous; that is, they began with T cells derived from the patient. The cells were either tumor-infiltrating lymphocytes (TILs), already presumed to contain some T cells specific for tumor antigens; or they were peripheral blood lymphocytes that could be stimulated with tumor antigens ex vivo to become antigen-specific. In either case, the cells were cultured and expanded to make them modestly active, without any genomic engineering or editing, then administered back to the original patient.

However, for various reasons this approach didn’t work as well as expected. It turns out that the antigen specificities of TILs found in certain tumor types, such as breast and colorectal, are poorly defined; and some TILs populations may include T cells that have immunosuppressive, rather than antitumor, activity.

The evolution of the science, from these early iterations of T cell therapies to the current state of the art, has introduced three fundamental requirements:

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The first is an antigen receptor, such as a chimeric antigen receptor (CAR) or T cell receptor (TCR), enabling the T cell to become highly specific in targeting the tumor.

For a CAR, the identification of receptor candidates is relatively straightforward: the CAR is designed and engineered to target a known tumor antigen, such as CD19 expressed on B cell cancers.

For a TCR, identification of the best receptor candidate is not always so straightforward, because the TCR is selected from the individual patient’s repertoire of T cells and the immune system’s response to cancer (and for that matter, to infection) is usually polyclonal. This means the immune system randomly generates a large set of receptor variants against tumor antigens, but not all of these variants will be tumor-specific. Instead, activation by tumor antigens selects for variants with tumor specificity – a real-time process of natural selection, in the Darwinian sense – and thus determines the repertoire of anti-tumor receptors T cells will have.

How does this polyclonal response complicate the identification of an antigen-specific TCR? The immune system may respond to, say, 10 different antigens expressed by a tumor; then, the immune system may generate 10 sets of 100,000 T cells, one set for each antigen. But among those one million T cells, some may be therapeutically beneficial while others have no effect on the cancer. The challenge lies in isolating what might be a very small number of beneficial T cells, then identifying the receptor they express that confers their antitumor activity.

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The second requirement is engineering the T cells ex vivo to introduce the selected antigen receptor.

The workhorses for delivering antigen receptor constructs such as CARs and TCRs into a cells are lentiviral vectors, not AAV vectors. This is because lentiviruses integrate into the genome of the cell, which enables long-term expression of the receptor construct and transmission of that construct to daughter cells. But lentivirus is not without its drawbacks. It is complex and expensive to manufacture: dose-for-dose, lentivirus and AAV cost about the same, but lentivirus has lower yields per batch. However, recent improvements in manufacturing technologies for lentiviral vectors are overcoming these limitations.

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The third requirement is the need for process development, analytical development and QC, and manufacturing capabilities to produce the engineered T cells under GMP conditions, in batches large enough for human therapeutic applications.

To do this at a commercial scale, a company first has to solve the manufacturing challenges of large-scale biology, which entails defining the critical quality attributes of the product through proper analytical development and QC during manufacturing scale-up. This process is significantly cost- and labor-intensive for a small biotech company to develop for one or two products, especially if they have never done so before.

This is the present level of complexity in cell therapies, but the field isn’t standing still and the landscape continues to evolve.

Tomorrow’s cell therapies depend on gene editing

The evolution of cell therapies brings up new ideas, and with them come new dimensions in functionality to maximize the cells’ effectiveness. To incorporate these functions, cell therapy innovators will need to access new technologies.

For example: it’s long been known that lentiviral vectors insert themselves at random places in the genome. But recent research has shown that insertion of an antigen receptor construct at one specific locus, instead of randomly across the genome, can result in T cells with greater potency. So, improving T cell therapies means employing an alternative to lentivirus for delivering the receptor construct – and that alternative is gene editing.

Next, a great deal is now known about how tumors, especially solid tumors, evade the immune system.

Blood cancers are more responsive to T cell therapies because the cancer cells circulate in the blood where T cells can easily find them. By contrast, solid tumors have many types of defenses – collectively known as the immunosuppressive tumor microenvironment – to keep out T cells. To get a T cell therapy past these outer defenses and into the tumor tissue, the T cell has to be engineered with some form cell trafficking – an address code, so to speak.

Even after the T cell gets past the defenses and infiltrates the tumor, the tumor can deploy countermeasures specifically designed to weaken or destroy the T cells, such as secreting the immune checkpoint protein, PD-L1. To avoid these countermeasures, the T cell needs defenses of its own, such as the deletion of the gene encoding PD-1, the receptor for PD-L1.

Lentiviral vectors cannot be engineered to deliver all of the gene constructs needed to make the foregoing changes to a T cell, precisely where they’re needed in the genome. Instead, the changes have to be made by gene editing of the T cell itself.

Similarly, allogeneic therapies – cells derived from one donor that are engineered to treat many patients – also require technology capable of making multiple edits to the genome.

The CGT space has made significant progress in developing allogeneic therapies derived from hematopoietic stem cells (HSCs), mesenchymal stem cells (MSCs) and induced pluripotent stem cells (iPSCs), with the EMA approving the first allogeneic cell therapy in the EU in late 2022 and FDA approving the first in the U.S. in 2023. To prevent rejection and graft-versus-host disease (GvHD) in the recipient, an allogeneic T cell must be HLA-matched to the recipient. This is a tall order, given that the human genome encodes six HLA genes, each with thirty or more variants (alleles). Alternatively, GvHD risk can be reduced by using gene editing to delete the cell therapy’s TCRαβ receptor that enables T cells to distinguish “self” from “non-self” cells, or to block expression of one or more of the HLA genes.

Another wave of the future is the concept of using iPSCs to produce “universal cell therapies”, in which functional expression of the six HLA genes is prevented via knockout of B2M, a shared subunit necessary for surface expression of these molecules, effectively eliminating the risk of rejection or GvHD. The hurdle here is that clinical-grade iPSC lines – those that comply with both Good Tissue Practices (GTP) and GMP – aren’t easy to obtain or produce.

However, introducing this array of genetic changes into a single T cell with traditional CRISPR-based gene editing systems is problematic, because there is a risk of jumbling the genome and a high cost to accessing the technology.

Gene editing nucleases like Cas9 and its orthologs used in CRISPR make a double-stranded DNA break in a target gene, temporarily resulting in two chromosome segments that are readily reassembled. If the nuclease happens to make more than one double-stranded break, temporarily resulting in four chromosome segments, the odds are still good that the segments will reassemble correctly – but those odds are not 100%. Incorrect reassembly produces chromosomal abnormalities, such as translocations and inversions, that adversely affect cellular processes and can even cause diseases. This risk is associated with every edit to the cell, and so places limits to the numbers of edits per cell that Cas9 and related nucleases can safely make.

Base editing technology gets around the potential reassembly problems posed by Cas9 and orthologous nucleases. A base editing enzyme does not create a double-stranded DNA break; instead, it cuts or “nicks” one strand of DNA, then converts one nucleotide base in the target genetic sequence to another base type. Because it carries no risk of jumbling the genome, base editing allows multiple gene edits per cell – exactly what’s necessary to make T cell therapies as potent and effective as possible.

Finally, the concept of in vivo cell therapy, which involves generating CAR or TCR T cell therapies by gene editing T cells in the patient’s body, adds the latest layer of complexity. In addition to meeting all of the requirements described above, these multi-gene editing constructs must be packaged and delivered specifically to T cells in vivo – for example, by encapsulating the cargo in nanoparticles conjugated to a CD3-targeting antibody. The first in vivo cell therapy products are approaching the clinic; as a class, they may be competitive with allogeneic T cell therapies and the space could evolve quickly. In either case, the next wave of cell therapy’s future is already upon us.

Not an impasse: A solution

To recap, then: A company aiming to create the complex immune cell therapies of tomorrow will need at least five, and possibly six, key components: (1) the antigen receptor; (2) a means of delivering that receptor, preferably with gene editing instead of a lentiviral vector; (3) GMP manufacturing for commercialization; (4) GTP- and GMP-compliant iPSC lines, preferably gene edited to be “universal cells” as starting points for allogeneic cell therapies; (5) base editing technology to engineer multiple features into the cells; and (6) for in vivo cell therapies, a means of delivering the gene editing constructs to T cells in the patient.

If a company doesn’t have access to all five (or six) components – three of which involve gene editing – it won’t be able to make and commercialize an ex vivo (or in vivo) cell therapy product. This situation might appear to leave a company with an innovative cell therapy at an impasse, but this is not quite so.

ElevateBio has technology platforms for all six components: protein, AAV vector, lentiviral vector and cell engineering platforms to identify antigen receptors and deliver them into cells; a large-scale biology approach to GMP manufacturing of CGTs at our BaseCamp facility; a bank of clinical-grade, GTP- and GMP-compliant iPSC lines in development to power regenerative medicine and allogenic cell therapies; the gene editing technology for making multiple changes to cell therapies, including those derived from iPSCs; and a range of delivery vehicles, including lipid nanoparticle (LNPs), for gene editing constructs.

Life Edit Therapeutics adds a highly innovative gene editing platform to our expertise in the discovery and development of new CGTs. Life Edit’s large and diverse array of RNA-guided nucleases (RGNs) and base editors can access virtually any region of the genome and enable the entire spectrum of edits, from small insertions or deletions to rewriting DNA sequences.

By offering this complete suite of CGT technologies to its strategic partners and portfolio companies, ElevateBio aims to develop CGTs at scale in a cost-effective and efficient manner. This is at the core of “ElevateBio’s DNA”; that is to say, ElevateBio has built this into its business model for a large number of partners, thereby significantly reducing the risk and cost of CGT development and commercialization. We believe that if the industry has more gene editing tools we can “democratize” access to these essential technologies required to make the cell therapies of tomorrow – ultimately improving medicines for patients around the globe.

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I recently had the opportunity to join CNBC’s Fast Money after ElevateBio was recognized as a 2024 CNBC Disruptor. In that conversation, I focused on ElevateBio as a “genetic medicines foundry,” a concept I believe captures what we do, how do we it, and the specific intentions with which we designed our business model and built the company from the outset. Through this foundry model we’re advancing programs, companies, and the entire industry with a full spectrum of tools, technologies, and expertise for developing the next generation of genetic medicines.

But what exactly does it mean to be a genetic medicine foundry? And how does it apply to ElevateBio?

An innovative business model for genetic medicines

We founded ElevateBio seven-plus years ago to redefine the way we develop and manufacture therapeutics and usher in a new era of medicine powered by cell and gene therapies, also referred to as genetic medicines. Our model goes beyond the traditional roles of a contract manufacturer or a standard therapeutic biotech company. Instead, we enhance the design and manufacturing of both our internal and partnered investigational therapies by combining platform technologies – including gene editing, cellular engineering, RNA engineering, and viral and non-viral delivery vehicles – scaled manufacturing and analytical and process development expertise. These technologies reside under two complementary components of ElevateBio’s ecosystem: Life Edit and BaseCamp.

Through Life Edit, BaseCamp, and our team of industry-leading experts, ElevateBio supports biopharma partners with end-to-end capabilities to design, develop, and manufacture genetic medicines. We are the first company to build a fully integrated technology stack and end-to-end manufacturing capabilities with what I refer to as a genetic medicine foundry.

ElevateBio as a genetic medicines foundry

Generally speaking, a foundry is a one-stop-shop to create various objects or components for the manufacturing of larger, more complex products.  Two companies from the tech sector illustrate this concept.

Taiwan Semiconductor Manufacturing Company (TSMC), established in 1987 as the world’s first dedicated semiconductor foundry, applies their technology and manufacturing techniques to produce powerful microchips – and still remains a critical supplier today of chips for phones, computers, cars, and servers in our tech-driven world. Nvidia has likewise placed themselves at the center of the artificial intelligence boom, building graphics processing units (GPUs), new software, and AI models for companies to apply in their own sectors.

In a parallel way, ElevateBio applies this same foundry business model to genetic medicines, positioning ourselves as a one-stop shop and indispensable partner for cell and gene therapy companies, dedicated to propelling the entire field of genetic medicine forward.

The benefits of our foundry approach

In essence, we serve as a catalyst for innovation and collaboration. And there are three primary ways in which our foundry model enables us, with our partners, to accelerate genetic medicine development.

The primary benefit is clear: speed of development. Our robust technology stack allows partners to choose the best technology for their product or streamline the design and manufacturing process, significantly reducing the time and resources required to develop new genetic medicines. This acceleration is not only advantageous for our partners but also has far-reaching implications for patients in need of life-saving treatments.

The second is the collaborative innovation we intentionally built into ElevateBio’s structure. Internally, that structure enables collaboration across our R&D, PD, manufacturing groups and other teams of experts on the design of next-generation medicines, with our embedded technology and capabilities at the center. Externally, our teams work closely and directly with our partners to expedite the translation of scientific discoveries into tangible therapies.

The third is the greater therapeutic flexibility our approach to partnerships gives us over a traditional biotech. Through external R&D partnerships and deals, we can advance a pipeline that creates opportunities for downstream revenues. At the same time, our partnerships allow us to advance our platform technologies and de-risk our early-stage programs, giving us the ability to build an internal, wholly owned pipeline of programs where we’ve demonstrated proof of concept and the chance of clinical success has increased.

Our impact on the industry and vision for the future

Multiple industry partners are already benefitting from the integrated technologies made possible through our foundry model.

For example, our process development and manufacturing teams at BaseCamp have partnered with Abata Therapeutics for several years to accelerate the development of their cell therapy program (ABA-101) for multiple sclerosis (MS). The technologies, manufacturing capabilities, and technical expertise of BaseCamp shaved one year off Abata’s initial IND timeline, saving them significant capital on staffing and facility costs required to design and manufacture this promising therapy. Importantly for Abata, the manufacturing process developed for ABA-101 serves as a template to benefit future development programs, including their next program for Type 1 diabetes. This collaboration also represents first time anyone has shown the ability to successfully engineer, expand, and manufacture TCR-engineered Tregs in the numbers required for use as therapeutics.

Similarly, with Kyverna Therapeutics, BaseCamp successfully completed studies to support process development and clinical manufacturing using Ingenui-T, Kyverna’s proprietary three-day manufacturing process for their autologous CAR T-cell therapy program for autoimmune diseases. This achievement is monumental when we consider the tens of thousands of patients affected by autoimmune diseases, and the speed with which Kyverna can turn the patients’ own cells into therapies that targets the underlying pathology of their disease.

Additionally, industry leaders Moderna and Novo Nordisk have turned to the gene editing capabilities of our Life Edit platform to help design potentially curative in vivo gene edited therapies and base editing therapies, respectively.

These are just a few examples of the positive impact ElevateBio is having on our industry partners and the change we’re bringing to the world. For us, “genetic medicine foundry” is more than a title or an abstract concept: it reflects the entire model on which ElevateBio was established and how we’re bringing to life our mission of advancing genetic medicines with our technology and manufacturing capabilities. We believe that being a foundry is a commitment to revolutionizing healthcare through collaboration, innovation, and dedication to improving patient outcomes.

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Life Edit is leveraging a proprietary microbe collection and extensive metagenomic datasets to discover and develop unique gene editing systems for an innovative, next-generation gene editing platform. Our large and diverse collection of proprietary RNA-guided nucleases (RGNs) and base editors provide flexible editing options and further our mission of curing disease by making any edit, anywhere.

In a prior article, Life Edit presented a primer on gene editing technologies, including CRISPR-Cas9, and their potential for treating many human diseases. Here, we’ll dive deeper into the cool technologies we’re developing at Life Edit, what differentiates it from other higher-profile gene editing technologies, and the distinctive company culture that has grown up around our science.

Life Edit’s technology and science

Our technology includes an array of proprietary gene editing systems that have a number of desirable properties.

First, our nucleases are small, which allows for versatility when packaging our systems for therapeutic delivery. For example, our lead systems, along with one or two guide RNAs (gRNAs) and all necessary regulatory elements, fit into single adeno-associated viral (AAV) vectors. Our systems are also amenable to other modes of delivery, like lipid nanoparticles (LNPs), which are less affected by size restrictions.

Second, our nucleases have diverse and complementary protospacer adjacent motif (PAM) requirements that increase the genomic loci we can edit. This matters because the commonly used SpyCas9’s PAM is NGG (any nucleotide followed by two guanines). And, while this PAM requirement does enable editing with Cas9 at many genomic locations, not every region in the genome is located near an NGG and accessible.

One way to illustrate the importance of these features is to consider the genome as a book. In that context, this PAM requirement means you can edit any place in the book that is located near one particular word, e.g., “and,” but nowhere else. While many sites in the book meet this requirement, it’s possible the place you want to edit is not close to “and.” Critically, many loci in the genome that are known to be associated with debilitating genetic diseases and disorders are not near the NGG PAM required for Cas9 editing. Thus, there’s a need for new tools that can unlock editing at these important locations in the genome.

Life Edit is building a collection of nucleases with A-, C-, G- or T-rich PAMs that will allow us to edit across a wide range of genomic loci. Sticking with the above book analogy, rather than being locked to edits near “and,” we have tools that can edit near a number of small words throughout the book, including “and,” “in,” “of,” “the,” “to” and so on. This will open every locus in the genome to editing, because virtually every place in the “book” we want to edit will be located near a small word that one or more of our nucleases can work with.

Moreover, the PAM diversity of our RGNs is of particular importance when utilizing precise editing tools, such as our proprietary collection of base editors. With this type of editing, pioneered by David Liu’s lab, a specialized enzyme called a deaminase is fused to an RGN in which the nuclease (scissor) activity is limited to cutting only one strand of DNA while allowing the deaminase to modify the uncut strand. The deaminase removes an amine group on specific DNA bases for which there are two classes of base editors: cytosine (C) base editors and adenine (A) base editors. Once the amine group is removed from C or A by the respective deaminase, the natural repair machinery of the cell facilitates the change of the deaminated base to a new base: cytosine base editors change C to G, and adenine base editors change A to T. If we go back to the analogy of editing a book, then base editors allow us to change specific letters in words, such as changing “and” to “any.” Important to the base editing system, the fused deaminase can only function within a narrow window of bases away from the PAM, and because of that limited mobility, having RGNs with PAM-diversity is incredibly advantageous. Also advantageous is the ability to engineer our deaminases and PAM-diverse RGNs separately to reduce the off-targeting propensity of each, then “mix and match” them to produce base editors with the best possible selectivity for the target loci. These features contribute to the strength and differentiation of our platform at Life Edit and drew the attention of partners like Moderna and Novo Nordisk.

Third, our systems have high fidelity and have shown little to no off-target editing to date.

We apply our scientific know-how to engineer these proprietary gene editing systems in various ways to optimize their editing efficiency and application as gene editing therapeutics. One improvement involves shortening the gRNA while retaining editing efficiency in order to facilitate GMP manufacturing.

Additional improvements include modifying the gRNA’s nucleotide sequence to increase its stability and making chemical modifications to the gRNA that further increase its stability and prevent it from getting digested by ribonucleases (RNases).

The importance of versatility

All of the foregoing translates into a versatile gene editing platform. We have many options to offer partners, based on the region of the genome they want to edit, the edit (or even multiple edits) they want to make, and the delivery system they want to use.

The versatility Life Edit offers is also important because there are still some things that aren’t fully understood by the gene editing field. For example, two genomic loci with identical PAMs may be edited by the same nuclease with differing efficiencies; editing efficiencies can also be very different when one genomic locus has two PAMs very close to each other. It is unknown why this happens, but we are interrogating different theories we have.

We can help partners navigate this obstacle because we have optimized the efficiencies of other nucleases with a variety of PAMs. If a partner isn’t getting good editing efficiency at the site of interest with SpyCas9, which requires an NGG PAM, we could offer them a system that uses another nuclease with a different PAM that edits the same gene with better efficiency.

Furthermore, we have demonstrated the multiplexing capability of our base editors – that is, their ability to edit multiple genes in one cell. As an example, using cell-based analysis, we have demonstrated that our base editing systems are able to edit three therapeutically relevant genes at once, with efficiencies comparable to those achieved when editing the same three genes individually.

These options could influence how a client thinks about making a new medicine and even change its approach to solving a therapeutic problem. Life Edit’s versatility allows partners to step outside the technological limits of Cas9, escaping its “mental box” and imagining new possibilities.

Our unmatched gene editing science and culture

Life Edit has a breadth of science and technologies that we can apply to each new system we investigate. We learn and combine different kinds of engineering approaches available in the field, including shortening gRNAs, swapping nucleotides in or out of them, and stabilizing them with chemical modifications. The engineering capabilities we have built set us apart from other companies that have had to carve out different, and more narrowly focused, gene editing approaches for IP purposes. It makes us unique among our peers in the gene therapy field. We have also built out – and will continue to expand – our capabilities in computational biology and high throughput robotics that enable us to engineer proteins, solve structures, and generate more experimental data faster.

Unlike most in the CRISPR field who are focused on optimizing the Cas9 system, we are developing platforms and techniques that can be used across systems. Each system we find is completely new, just like Cas9 was at one time; we get to figure out how it works, how to optimize it, and how to apply it to new technologies, such as base editing. We need a broad toolbelt to do all of this.

There are generally no universal rules; each system we find is unique and may have slightly or significantly differentiated properties as compared to previously known systems. We have to think of each system distinctly and become experts in it. That is a big part of why we think our science is so cool and intriguing, and that’s what brought us both to the company.

Whether it’s the science influencing the company culture or vice versa, Life Edit’s culture has a distinct “coolness” that differentiates the company and drives us. We work hard to protect and maintain that culture, even with our exponential growth, and we’re eager to share it with each new employee who joins the company.

Much more to discover and develop

We and other scientists at Life Edit have presented our research and technologies at national and international conferences. These presentations have highlighted the discovery of new nucleases and identification of their respective PAMs; the ability of these new systems to make knock-in and knock-out edits, including multiplex edits; and the high editing efficiencies achieved by chemically modifying the gRNAs. Furthermore, we’ve also presented exciting preclinical data demonstrating that our gene editing systems can enable allele-specific editing of the mutant huntingtin (mutHTT) gene in mouse disease models, leading to clinically meaningful reductions in striatal mutHTT protein.

Life Edit continues to develop the systems we’ve already found and to explore new gene editing systems from our proprietary collection of microbes. Future technological expansions could include new systems for epigenomic editing, other classes of nucleases, and base pair-specific editing. We’re pioneering discoveries in all of these areas and more, and we’re connecting our discoveries to the development of real and curative gene therapies for patients.

by

CRISPR gene editing offers the potential to permanently treat genetic diseases with just a single dose of medicine. For this reason, CRISPR technology has received widespread attention from life scientists, biopharma companies, and the public in the nine years since its first reported use in editing human DNA. This concept of “one and done” has revolutionized not only how we think about treating disease; it has also revolutionized how therapies for many diseases are now being discovered and developed.

DNA is the blueprint of life. Genes are individual segments of DNA that contain the instructions for making the proteins and other molecules the cells in our bodies need to grow, survive and function. The complete set of genes in our bodies is called the genome.

Many genetic diseases are caused by inherited mutations in a single gene that render the corresponding protein non-functional or otherwise defective. Depending on the gene and its role in the human body, a person who inherits a mutant copy of the gene from one parent or both parents will develop the disease.

On a general level, many people grasp the potential of CRISPR-based gene editing to treat genetic diseases: it targets the mutated segment of DNA within the disease-related gene to “correct” it. But many people, including those in the general public, are keen to know more: how CRISPR works, which diseases it can and can’t treat, and what its future opportunities and challenges are.

We’ll take a look at all of these topics in this “primer”, which is the first article in a series about the gene editing landscape. In later articles, I’ll discuss how Life Edit’s gene editing technology fits into that landscape, and how our team is developing that technology into the medicines of tomorrow.

Before gene editing

CRISPR’s recent media attention may create the impression that gene editing is a brand-new idea, but it is not. The concept of treating a genetic disease by counteracting the underlying problem in the genome has a history that began with gene therapy, long before gene editing came along.

Traditional gene therapy medicines remedy the lack of functional protein by treating the patient with a normal copy of the gene. This is achieved by packaging the gene into a delivery vehicle, typically an adeno-associated viral (AAV) vector, which enters the cells most involved in the disease and then delivers the gene inside them. The normal gene remains in those cells for some period of time, treating the disease by expressing a functional version of the protein.

While it may seem straightforward, gene therapy faces several challenges.

Many genes are too large to fit into AAV vectors. Some diseases, such as muscular dystrophy, might be treatable with a truncated gene that produces a shortened, but still functional, form of the protein. But many other genetic diseases require delivery of a full-length gene for the therapy to be effective.

Additionally, because the therapeutic gene is not incorporated into the patient’s genome, its effects, while possibly long-lasting, have not yet proven to be permanent. Yet redosing with the gene therapy may not be possible, because the first dose can induce an immune response to the AAV vector that would prohibit a second dose of the therapy from effectively reaching the target cells.

Gene editing therapy aims to overcome the limitations of gene therapy by making a permanent change in the patient’s genome, so that only one dose is required to treat the disease. Depending on the genetic problem driving the disease, gene editing has the potential to remove, add, or alter DNA, which offers greater flexibility than gene therapy (which can only add) and the possibility of delivering treatments for diseases where gene therapy isn’t an option.

One example is spinocerebellar ataxia 1 (SCA1) where a mutant version of the ataxin 1 gene (ATXN1) contains an abnormally high number of repeated sections (called CAG repeats) in the DNA code and produces a mutant ATXN1 protein that damages several types of neurons. This problem can’t be addressed by adding a normal copy of ATXN1 with gene therapy, but may be improved by removing the excess CAG repeats with gene editing.

How gene editing works: Fingers, TALENs and nucleases

All gene editing technologies require two essential components: an enzyme capable of cutting DNA (a nuclease); and a method that directs the enzyme to the target sequence in the genome. As with gene therapy, these components are typically packaged into AAV vectors and delivered to the cells most involved in the disease. Once inside the cells, the nuclease finds the target DNA sequence, binds to it, and cuts both strands of DNA. Next, natural mechanisms found in all cells repair the DNA break, leaving behind the edited gene.

Three types of gene editing technology arose before CRISPR. One type utilizes a class of artificial enzymes called zinc finger nucleases (ZFNs), which were discovered in the 1980s and moved into therapeutic development in the early 2000s , with several products now in clinical trials. A second type is based on a class of naturally occurring enzymes called meganucleases (also known as homing endonucleases), which were discovered in the 1990s; they have since been tested in non-human primates ,  and the first meganuclease-based gene therapy entered clinical testing in 2019 . A third type also uses a class of engineered enzymes called transcription activator-like effector nucleases (TALENs); these were first described in the scientific literature in 2010  and quickly moved into clinical testing as well .

A strength of both ZFNs and TALENs is that they can edit any site in the genome. But one drawback is that these nucleases must be guided by proteins that specifically target the site. Designing and engineering such proteins involves a great deal of upstream R&D and yields a protein that can target only one place in the genome. Meganucleases have similar drawbacks: each naturally occurring enzyme targets a single genomic site. However, because the likelihood of finding a natural meganuclease specific for a given site is quite low, meganucleases for therapeutic applications are typically engineered, which also requires upstream R&D.

The advent of CRISPR in 2012 transformed the gene editing landscape by streamlining the method to direct the nuclease to a target sequence in the genome. Instead of being directed to the target sequence by a protein, CRISPR is directed by a guide RNA molecule. These guide molecules can be easily designed and generated for each target and paired with the same nuclease protein instead of relying on engineering new ZFN or TALEN proteins or a meganuclease for every target.

The best-known CRISPR system uses an RNA-guided nuclease (RGN) called CRISPR-associated protein 9 (Cas9), which is derived from Staphylococcus pyogenes bacteria (SpCas9). Instead of requiring a guide protein, Cas9 relies on a short RNA molecule called a guide RNA (gRNA), whose sequence is complementary to the target site in the genome. The gRNA must be designed specifically to target that site, but it’s much easier to develop a gRNA than to engineer a guide protein.

This type of guide molecule gives CRISPR a modular aspect: the same RGN can be targeted to different sites in the genome simply by swapping one gRNA for another.

That said, a single RGN can’t target everywhere in the genome; it can only bind DNA segments that are located close to a short nucleotide sequence called a protospacer adjacent motif (PAM).

The therapeutic potential of CRISPR

The ease of design and genomic range of CRISPR raises many interesting questions: What can it do therapeutically? What diseases could it treat and how are target genes chosen? How many copies of the gene must be edited to achieve a permanent fix – all of them?

As I mentioned above, genetic diseases caused by a mutation in a single gene, such as SCA1, are starting points for gene editing. CRISPR-based therapies would cut out the small segment of the gene where the mutation occurs.

Medical doctors and researchers continue to investigate the genes that cause diseases and mapping the specific mutations involved, in order to figure out which part of the gene to fix. But CRISPR can also target non-mutant genes that play roles in disease. A good example is the PCSK9 gene in hypercholesterolemia.

The PCSK9 protein controls the number of low-density lipoprotein (LDL) receptors on cell surfaces that regulate blood cholesterol levels. Studies have shown that people with naturally occurring loss-of-function mutations in the PCSK9 gene are otherwise healthy and have higher levels of LDL receptors, with resulting lower blood cholesterol levels. As a way to treat and reduce high cholesterol, CRISPR gene editing can be targeted to cut the PCSK9 gene to create a loss-of-function mutation. This underscores the importance of ongoing investigations into basic human biology to identify potential genetic targets that could be edited to treat diseases.

Notably, gene editing doesn’t need to correct every copy of the gene in a patient’s body to be effective. Rather, only the cell types and tissues where that gene plays a major functional role need to be targeted, such as muscle cells for ATXN1 and liver cells for PCSK9.

That brings us to another point: gene editing machinery is just one part of the equation; delivering the gene editing machinery to the target cells is the other part.

Engineered AAV vectors are currently the delivery workhorses for gene editing because AAV has many subtypes (serotypes), each of which targets a different tissue type, making them good choices for delivering many gene editing therapies. However, because wild-type (naturally occurring) AAVs can infect humans, many people have some level of pre-existing immunity to AAVs that could compromise the efficacy of a gene therapy delivered with an AAV vector. Additionally, while CRISPR packages are generally smaller than the full-length genes used in gene therapy, not all CRISPR packages will fit into AAV vectors. Because AAVs have these potential limitations, other delivery vehicles, such as lipid nanoparticles (LNPs), are under investigation to expand the toolbox of delivery options.

What’s next: Questions, challenges and avenues of exploration

In addition to new delivery methods, there are several aspects of gene editing we need to investigate in order to fully tap its potential.

A major concern is its ability to make off-target edits – that is, to alter one or more sites in the genome apart from the intended target. The technology’s success will depend on understanding where those off-target edits could occur and the ramifications they could have. For example, is the off-target gene critical to cell survival? Will editing the off-target gene lead to another disease, such as cancer? Of course, it will also be critical to design gene editing systems that have little or no potential to make off-target edits.

There are also questions about how “permanent” a given edit is. For example, because SpCas9 is derived from bacteria that infect humans, patients may have pre-existing immunity to the nuclease. Similarly, patients may also have pre-existing immunity to the AAV vectors, as noted above. If AAV remains in the individual’s system expressing SpCas9 for too long, the vector and/or the nuclease might be recognized and eliminated by the immune system before the gene editing process is complete, or edited cells that have prolonged AAV and/or SpCas9 expression may be cleared by the immune response.

But there are exciting new areas to explore as well. An expansion of potential genome targets for CRISPR editing is possible with the discovery of new nucleases that have different PAM requirements. Also, new editing strategies such as altering a single nucleotide in the genome for correction of disease-causing point mutations, is enabled with development of new gene editing technologies, such as base editors.

Life Edit is delving into all aspects of gene editing, from new nucleases and base editors, to delivery methods and off-target edit detection assays. In my next article, we’ll take a closer look at Life Edit’s technology, its unique potential, and why I am excited to be working on it.

  1. https://www.sciencedirect.com/science/article/pii/S0022283615006063
  2. https://www.nature.com/articles/nbt.4182
  3. https://www.sciencedirect.com/science/article/abs/pii/S1525001621000873
  4. https://www.nature.com/articles/d41573-020-00096-y
  5. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2942870/
  6. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3547402/#BX1
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