Chimeric antigen receptor (CAR) T-cell therapy has inspired newfound hope for patients with unresponsive cancer and created widespread scientific enthusiasm spanning oncology to autoimmune disease. At the time of this writing, there are only six FDA-approved CAR T-cell therapies, primarily for oncology indications. Even though the FDA granted orphan drug designation for a CAR T-cell therapeutic for use in lupus earlier this year, there is still much work to be done to bring more drugs to market. The path to furthering these treatments requires mouse models, which can be used for proof-of-concept studies, understanding mechanisms of action, optimizing protein designs, predicting clinical outcomes, and even investigating toxicity and side effects.

Focus on potential

Like most new oncology therapies, CAR T-cell therapy still requires additional scientific investigation and refinement in the preclinical stages. Allogeneic CAR T-cell therapies—using human donor cells—could accelerate timelines and broaden distribution, but they face unique challenges, including graft-versus-host disease and cytokine release syndrome. Modeling these responses and treating any negative side effects in murine models will aid in developing more translatable treatments.

The most translatable platform: mice

Before using CAR T-cell therapies in patients, it’s essential to determine efficacy in animal models that capture disease complexities. Cell-based ex vivo assays alone are unable to recapitulate the intricacies of animal immune systems. FDA guidance issued in January 2024 emphasized the use of animal models in CAR T-cell therapy, noting, “Animal models can be useful in demonstrating proof-of-concept data for CAR T-cell functionality.” The guidance also noted, “If a relevant surrogate product is available, syngeneic tumor animal models can provide information regarding the interaction of the surrogate CAR T-cells with an intact host immune system and potential on-target/off-tumor toxicities.” As the immuno-oncology industry evolves, so must the preclinical animal models that fuel these early stages of drug development. Taconic Biosciences recognizes the importance of breaking down licensing barriers and making available the most translationally relevant preclinical models for CAR T-cell therapy development. The IL-2 NOG mouse, a super-immunodeficient mouse that expresses the human IL-2 cytokine, is one example of a complex animal model that has been successfully employed to model CAR T-cell immunotherapy in HER2+ breast cancer and is available off the shelf.¹ In one recent study using hIL-2 NOG mice, researchers were able to demonstrate significant CAR T-mediated antitumor efficacy in mice transplanted with PDX melanoma cell lines. Additionally, Taconic’s immunodeficient NOG-EXL mice, which express human GM-CSF and IL-3 cytokines, were used to assess CAR T-cell therapy in non-small cell lung cancer.² In addition to the hIL-2 NOG and NOG-EXL models, which are maintained in live colonies for easy access, Taconic has the most experienced model generation team in the industry that partners with researchers to create custom models tailored to their specific CAR T-cell therapy investigations.

Creating advanced CAR T-cell therapies requires extensive preclinical studies. However, by using animal models that approximate human disease, scientists are able to reduce the number of animals needed to elucidate how therapeutic candidates act upon disease in preclinical stages. Taconic’s commitment to the 3R’s principle—Replace, Reduce, and Refine—promotes the ethical use of animals in scientific research and exceeds U.S. FDA and international animal use guidelines. Streamlining the preclinical-to-clinical oncology pipeline necessitates effective tools capable of capturing the intricacies of disease response to treatment in humans. Super immunodeficient and genetically engineered models are uniquely valuable tools for oncology and autoimmune researchers seeking to develop novel therapeutics.

References

1. Cao B, Liu M, Wang L, et al. Remodelling of tumour microenvironment by microwave ablation potentiates immunotherapy of AXL-specific CAR T-cells against non-small cell lung cancer. Nat Commun. 2022;13(1):6203. Published 2022 Oct 19. doi:10.1038/s41467-022-33968-5
2. Forsberg EM, Lindberg MF, Jespersen H, Alsén S, Olofsson Bagge R, Donia M, Svane IM, Nilsson O, Ny L, Nilsson LM, Nilsson JA. HER2 CAR-T cells eradicate uveal melanoma and T cell therapy-resistant human melanoma in interleukin-2 (IL-2) transgenic NOD/SCID IL-2 receptor knockout mice. Cancer Res. 2019 Jan 8. pii: canres.3158.2018

Explore the hIL-2 NOG, NOG-EXL, and other super immunodeficient models for CAR T-cell therapy work, visit: taconic.com/gen.

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Unleashing potential with CRISPR technology

In the dynamic landscape of biological research, CRISPR technology has revolutionized our approach to genetic disorders and the future of personalized medicine. Of these advances, cell and gene therapy is front and center as an example of where CRISPR has been forging inroads into these novel therapeutic possibilities.

Established as a pioneer in genome engineering, EditCo Bio spun out from the CRISPR heavy weight, Synthego, in March of 2024 with a mission to redefine how CRISPR tools are used. Leveraging data from over 500,000 edits, EditCo’s automated gene editing design and application platform has handled a variety of complex genomic challenges, offering streamlined solutions from optimized gene knockout kits or custom-edited cells to high-throughput projects and advanced data analysis.

High-throughput screening in iPSCs for cell therapies

This novel gene editing platform has opened the door to a wide range of challenging projects and partnerships with companies whose research is moving the world of cell and gene therapy forward quickly. An example highlighting how EditCo Bio’s CRISPR platform has solved gene editing challenges is through a recent partnership with bit.bio, a synthetic biology company with a platform to program human induced pluripotent stem cells (iPSCs) into a wide range of cell types for discovery research and cell therapy.

Combining EditCo’s ability to perform high-throughput edits in many medically relevant cell types, including human iPSCs, with full automation integration, and bit.bio’s expertise in leveraging iPSCs for cell therapies, the team performed a high-throughput screen of hundreds of guides across 25 genomic safe harbor (GSH) sites. Additionally, EditCo’s ability to analyze many biological and technical replicates with the use of an integrated robotic workcell for next-generation sequencing (NGS) allowed the generation of a highly reproducible dataset by sequencing more than 4,600 NGS libraries with a success rate ranging from 88% to 98%.

Through meticulous optimization of editing conditions, careful validation through NGS, and automated high-throughput capacity, the project showcased the precision and flexibility made possible through EditCo’s gene editing platform. This allowed for rapid identification of hot spots for high knock-in editing levels with the most effective guides in genomic regions not typically targeted for gene editing. Ultimately, this research has the aim of maximizing safety and efficacy of CRISPR-Cas editing across the 25 genomic loci.

Addressing Alzheimer’s disease with advanced CRISPR applications

Beyond large-scale editing optimization, EditCo’s genome editing process has been important for providing a unique solution for CRISPR screening in clonal cells. In collaboration with the National Institute of Health (NIH), the Inducible Pluripotent Stem Cell Neurodegeneration Initiative (iNDI) project by EditCo Bio targeted 22 genes, generating 12 variants per gene, which resulted in 264 CRISPR iPSC clones all in less than five months.

This massive screening of 8,108 clones and the execution of 6,138 sequencing reactions highlighted the platform’s capability to handle large-scale, high-throughput operations efficiently. This project is particularly crucial for advancing understanding and treatments of complex diseases like Alzheimer’s, showcasing EditCo’s pivotal role in cutting-edge genetic research.

Shaping the future of healthcare

By marrying the precision of CRISPR with the expertise and innovation within EditCo Bio, significant progress continues to be made to elucidate and mitigate risks associated with genetic diseases. Opening up new avenues for enhancing human health is proving that EditCo’s technology will continue to be a powerful solution within the field of cell and gene therapy and healthcare overall. And, as CRISPR technology continues to evolve, EditCo Bio plans to remain at the forefront, committed to partnering with researchers and leading the charge toward transformative health solutions.

References
1. Published with permission from bit.bio
2. Figure created with BioRender.com

To learn more visit editco.bio

Contact us partner@editco.bio

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Most biopharma companies depend on a contract development and manufacturing organization (CDMO) for some steps—often all steps—in the production of material for clinical trials and manufacturing therapies. In late 2023, however, Gil Roth, president of the Pharma & Biopharma Outsourcing Association, wrote: “The last several years have been tumultuous for the CDMO sector.”¹ Nonetheless, this sector continues to play a vital role in supplying customers with new and long-standing treatments, and many biopharma companies need to partner with an experienced and reliable CDMO.

Charles River Laboratories—founded in 1947 and headquartered in Wilmington, MA, just west of Boston—is a veteran contact research organization (CRO) and CDMO that supports clients from drug discovery and development through commercialization. In addition to conducting more than 1,000 studies in cell and gene therapies, including supporting the development of 20 of those approved by the FDA, the company constantly develops new tools and technologies to accelerate, improve, and scale the development of drug therapies.

Tools for Testing

The development and manufacturing of cell or gene therapies requires safety and efficacy testing. The latest in its portfolio, Charles River developed reference materials for
adeno-associated viruses (AAV) and lentiviral vectors (LVV), including six AAV stereotypes and five LVV products.

As Elizabeth Misleh, associate director, gene therapy research solutions, Charles River, says, “Our AAV reference materials boast superior empty/full capsid ratios and high vector concentrations, while our LVV reference material comes in various combinations of promoter and reporter genes.”

These reference materials can be used from early discovery through manufacturing as controls for assay development and validation. “Some of the assays include, but are not limited to, infectivity testing, transduction efficiency, biodistribution studies, and standard in-process testing,” Misleh explains.

Transferring Viral Vectors

Building on established viral vector production platforms—nAAVigation and Lentivation, which streamline AAV- and LVV-based programs, respectively—Charles River launched a new framework for technology transfer of viral vectors at BIO 2024. “It’s a methodical approach to transfer products from one facility into ours in the most expedited way,” says Ramin Baghirzade, PhD, senior director, global head commercial, gene therapy CDMO services, Charles River.

With more than 20 years’ experience with tech transfers from drug manufacturers and other CDMOs, this program includes fast-track and modular frameworks. “Within the fast-track framework, we’re taking a product as is and transferring it, because the process is robust and no changes are required before taking it to GMP,” Baghirzade says. “With the modular approach, our partners can customize the technology transfer by selecting modules, such as plasmid supply and process development, to suit their program.” Either way, technology transfer of viral vectors facilitates program continuity and de-risks supply chains.

Cell Therapy Flex Platform

In May, Charles River reinforced its commitment to cell and gene therapy developers in launching its Flex Platform for CAR T and TCR T cells. The Flex Platform is “an off-the-shelf solution for people who need to make these cell therapies,” says Alex Sargent, PhD, director of process development, Charles River. “It’s designed to be a modular approach, and it allows for maximum flexibility so it suits a wide variety of processes.”

In addition to being flexible, this platform includes other key attributes: automation, artificial intelligence (AI), and GMP operations. “These fully automated solutions are AI-enabled and functionally closed technologies that deliver a process adapted for GMP operations,” Sargent says. “The Flex Platform can significantly shorten development times and get cell therapy products into clinical production faster.”

Along with the Flex Platform, Charles River’s tools for viral vectors, including reference materials and technology transfer, accelerate the development of new gene-modified cell therapies, which is one of the fastest growing segments across all cell- and gene-based treatments.

Reference
1. Roth, G. The road ahead for CDMOs in 2024. Contract Pharma. 2023.

Advance Your CGT bit.ly/3yFijVa

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Patients rely on diagnostic tests to monitor their health efficiently and effectively. There is a lot of background work that takes place to reliably produce the components of these indispensable products. GEN recently spoke with Shana Khoury, President of Scripps Laboratories, to learn more about the in vitro Diagnostic Industry (IVD) and the challenges that suppliers face.

GEN: What are the major areas of focus for your business / laboratory?

Khoury: We manufacture antigens and antibodies as well as buffers and reagents for the IVD market. Diagnostics are the first line of defense in healthcare to help direct treatment. Patients need to have a diagnosis, such as from a blood test, before they can be treated. Our products are key components in the test kits used at centralized testing facilities, hospitals, medical offices, clinics, and other laboratory settings that specialize in diagnostic testing. Although we do not manufacture infectious disease–specific products, during the height of the COVID pandemic, we ramped up production to meet the increased demand for our reagents that are used in some of the most widely distributed COVID home tests. Aside from infectious disease testing, developing reagents for point-of-care devices and the home test market for pregnancy, fertility, and ovulation monitoring are big areas of focus for us.

GEN: What are the main challenges affecting your industry?

Khoury: Our major challenges are the scarcity of resources and raw materials. Human tissues that are donated to science have diminished in quantity and quality over the last several years. Glands and organs have never been abundant; supply has always fluctuated. Over the last few decades, we made it a priority to stockpile excess supply when available. The recent COVID pandemic brought our supply chains to a screeching halt. It is still incredibly difficult to get these raw materials, regardless of the energy and resources spent trying to obtain them. Our stockpiles allowed us to continue manufacturing at maximum capacity throughout the pandemic. We began developing a mirror recombinant catalog to mitigate the impact of future tissue scarcity and to continue to supply our customers with the products they need to meet their manufacturing schedules.

Additional challenges have also presented themselves which have required us to get creative and adapt with the changing times. As a result, we find ourselves utilizing our domestic resources more and sourcing locally when possible.

GEN: What is Scripps doing to combat the challenges?

Khoury: The supply of native tissues is not coming back. We foresaw this scarcity and have been replacing our native catalog with recombinants that are reliable, available, and cost-efficient. As technology has advanced, we have been able to shift our focus and produce recombinants that are comparable to their native counterparts. We are proud of our results. Maintaining a consistent, reliable supply of these products is absolutely critical to our IVD customers. It is imperative for us to always meet our manufacturing deadlines, so our customers’ schedules stay on track.

GEN: What would you say to customers who are reluctant to switch from native to recombinants?

Khoury: There is no other option. There is no foreseeable solution to the diminishing supply and quality issues we have been seeing over the last few decades. It is a good time to start validating recombinants and replace native-sourced proteins wherever possible. Our recombinants are different from those produced a decade ago; they perform better in IVD assays. We never release a recombinant product until we get the same, comparable results as with our native proteins. It has taken time, but customers are becoming more receptive. They realize that the short-term inconvenience of validating a recombinant gives them long-term guaranteed supply, stability, and security.

GEN: Discuss the importance of a quality system and its role in your business/industry?

Khoury: Our quality management system holds us accountable and evolves with our needs. It also helps us continually improve. It encompasses every function in our business, including manufacturing processes, training, and communications. We are ISO certified and we welcome customers to visit us to see how seriously we take quality. Our quality system ensures that we repeatedly produce products the same way and with the same performance, so we meet all expectations. If we need to make a modification, for example, due to a discontinued reagent, we inform our customers far in advance. Then we do everything possible to ensure the products we produce perform comparably or better than their predecessors.

Visit our website to see how you can benefit from Scripps Laboratories’ world-class recombinants.

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Imagine being able to map every cell within a tumor, understanding not just which ones are present, but also their precise locations and how they communicate. This is the promise of spatial biology—a cutting-edge approach to cancer research and precision medicine. By examining cells in their natural context, spatial biology helps researchers gain biological insights into tumor structure, cellular composition, proximity, and morphology, which could lead to faster tumor detection, more accurate diagnoses, and personalized treatment strategies.

A study by Arutha Kulasinghe, PhD, Scientific Director of the Queensland Spatial Biology Center at the University of Queensland, showcased the power of this technology by demonstrating how spatial biology enables cellular phenotyping and functional annotation of every cell in the tumor microenvironment (Figure 1).

Insights revealed at the bench are now being translated into the delivery of precision oncology at an entirely new level in clinical settings. This progress provides deeper insights into the current landscape and shapes the next generation of cancer research.

• “We know where the cells are and what they are doing. Using spatial biology, we can identify subsets of cells and their nuances. This will tell us which are key players in driving resistance or sensitivity to therapy.” —Arutha Kulasinghe, PhD, University of Queensland

A catalyst for spatial biology

An enormous amount of spatial data is being generated and combined with other “omics” data, bringing new clarity to the complexity of cancer. However, deriving actionable insights from these large datasets remains a challenge due to a lack of accessible computational tools. Expanding the use of AI in spatial biology can help pathologists and oncologists identify patterns within the tumor microenvironment, leading to more precise diagnostics, personalized treatment strategies, and a better understanding of how patients respond to treatments.

Spatial biology 2.0 elevates research

Despite its potential, spatial biology still faces hurdles. Current spatial biology multiplex imaging platforms are limited by slow processing speeds, complex workflows that limit throughput, and large data storage requirements. While AI can help overcome some of these challenges, limitations remain.

To address these challenges, Akoya Biosciences has developed Spatial Biology 2.0—end-to-end solutions including PhenoCycler®-Fusion 2.0 and PhenoImager® HT 2.0, designed to generate more data, faster, at any scale. From unlocking breakthroughs from individual samples and generating spatial atlases on a human scale to understanding tumor heterogeneity, and identifying cellular neighborhoods, these solutions are poised to transform our understanding of human biology and disease.

Spatial Biology 2.0 introduces key innovations including whole-slide, highspeed imaging, scalable multiplexing, and simplified workflows (Figure 2).

• “AI can deal better and more reproducibly with large amounts of data from multiplex and hyperplex studies. AI can help analyze data and identify
  patterns we may not be able to discern.” —Suzanne Coberly, MD, Bristol Myers Squibb
• “The intricacies of oncology as revealed by spatial biology, along with its ever-evolving landscape of treatments and methodologies, stand to benefit immensely from AI.” —Doug Flora, MD, St. Elizabeth Healthcare, and a pioneer in utilizing AI in precision oncology

Conclusion

The convergence of spatial biology and AI marks a transformative era in precision oncology. By harnessing the detailed cellular insights provided by spatial biology and the pattern recognition of AI, this approach offers insights into cancer complexity that translate directly to the clinic. The result: more precise diagnoses, personalized treatment strategies, and a deeper understanding of cancer and other diseases.

As we continue to push the boundaries of possibility, the future of cancer treatment has never looked brighter.

To gain exclusive insights from leading experts in spatial biology:

Watch on-demand webinar
www.akoyabio.com/webinar-gen-aacr2024

Download 100-plex application note
www.akoyabio.com/100-plex

Talk to us
www.akoyabio.com/contact

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Emulate recently presented a webinar discussing a novel workflow that models the unique and critical mechanisms of CAR T-cell trafficking, recruitment, migration, and killing in a unified Organ-Chip assay. The assay and workflow were designed to help researchers develop new mechanisms to interrogate CAR T cells and discover new pathways to improve the efficacy of these cells in solid tumors.

The vast majority of cancer deaths are associated with solid tumors. Yet, efforts to adapt CAR T-cell therapy to treat solid tumors have proven challenging. Solid tumors are extremely heterogeneous and express a myriad of antigens, making targeting difficult. The immune-suppressing microenvironment and CAR T-cell exhaustion also play major roles.

“But the T cells have to reach the tumor first,” said Anita Mehta, PhD, Principal Scientist and Immunology Team Lead at Emulate. CAR T cells need to migrate out of the bloodstream and make a long, demanding, well-orchestrated journey.

“To effectively model what is happening in vivo, we have to understand critical components of T-cell recruitment and migration into the tumor,” Mehta noted.

The Workflow

Emulate Organ-Chips, which were used to model this entire journey, have a top and bottom channel separated by a porous membrane. “In the top channel, we seed tumor cells, and in the bottom channel, we seed tissue-relevant endothelial cells” Mehta detailed. “To develop the workflow, Emulate used non-small cell lung cancer (NSCLC) cells, A549 cells, which express HER2 as a target antigen. Expression of the HER2 antigen was analyzed by flow cytometry, and the mean fluorescence intensity demonstrated expression of HER2 but not CD19 (a target antigen for blood cancer).

“At 24 hours prior to CAR T-cell administration, the bottom channel is primed with cytokines, and the top channel with tumor-relevant chemokines. The cytokines prime the endothelial cells to express adhesion molecules, which are critical for the CAR T cells that we flow through the Organ-Chip at a high rate to attach in an inflammation-specific manner.”

Once administered in the vascular channel, HER2⁺ CAR T cells attach to the adhesion molecules and travel through the membrane into the top channel, where they recognize the antigen expressed by the tumor cells and begin antigen-specific killing.

Confocal imaging was coupled with image quantification to analyze the complex datasets. “You can see the attachment of the CAR T cell, either in the endothelium, inside the membrane, or in the epithelial
channel, to quantify attachment and migration,” Mehta said.

To demonstrate the antigen-specific killing response, CD19⁺ CAR T cells were administered as a negative control and recruited into the top channel but did not kill the tumor cells. Meanwhile, the HER2⁺ CAR T-cell killing of the tumor cells, with the expressed antigen, was visually striking, facilitating quantification.

“The assay allows you to track the killing in real time or in a kinetic manner,” Mehta said. “This is a powerful tool to understand different CAR designs and provides mechanisms of action over time to enhance efficacy.”

IL-2 was used experimentally as a co-treatment. Although IL-2 did not affect recruitment significantly, the fitness of the CAR T cells was drastically improved. They were capable of killing more tumor cells compared to a monotherapy approach.

Summary

The robust, validated, and flexible CAR T-cell Organ-Chip workflow for solid tumors allows modeling of CAR T-cell vasculature attachment, recruitment, and killing in one assay. Co-therapeutics testing, CAR T-cell extraction, and immunophenotyping analysis can also be accomplished, and the complexity of the model can be expanded as experimentally desired.

The model was built using Emulate’s Basic Research Kits. The protocol provides guidance on how to adapt the workflow to specific needs.

To view the webinar, visit: emulatebio.com.

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In recent years, the life sciences industry has undergone significant transformations, driven largely by the COVID-19 pandemic. The U.S. government’s push for increased domestic production by biotech and pharmaceutical companies aimed to secure the drug supply chain and reduce dependence on foreign entities, ensuring timely access to medications for patients. However, this endeavor poses challenges in terms of cost and time for U.S. manufacturers, making ongoing innovation and favorable funding essential for success.

Funding Challenges

During the pandemic, funding for non-COVID-19 drug studies was scarce. Nevertheless, there are positive indications in Q1 of 2024 that funding for early-phase studies is stabilizing, particularly for biologics and small molecules. The rise in Phase I studies underscores the importance of economical manufacturing across all scales, including small-scale production for orphan drugs and rare diseases. This is particularly relevant as regulators tighten restrictions around keeping production in the U.S. Drug companies certainly face cost pressures, and production in the U.S. must make financial sense for it to be espoused. Continuous flow technology emerged as a winning solution, offering significant cost, quality, and safety benefits.

Continuous Flow Technology

Curia has over 25 years of experience in continuous flow, which has gained traction due to heightened market interest. This technology, spanning from discovery to manufacturing, offers speed and increased efficiency, with automated controls ensuring quality at each production stage. Early detection and removal of defective product translates to enhanced quality, reduced waste, energy savings, and lower production costs. Diligent monitoring also simplifies regulatory compliance.

Additionally, continuous flow is more economically feasible than batch processing for orphan drugs and those with narrow profit margins. The technology provides process safety information for achieving safer operations and is amenable to extreme temperatures and pressures, as well as hazardous reagents. These advantages prompted Curia to adopt continuous flow chemistry for both small molecules and mRNA manufacturing to speed higher quality, life-improving therapies to patients.

mRNA Opportunities and Challenges

mRNA, another recent innovation, offers a wealth of advantages for both patients and manufacturers. Compared to small molecules, mRNA-based production presents numerous advantages over traditional methods, including simplified manufacturing and enhanced safety for patients. The volume of material required is much less than a small molecule or antibody, and the chemistry is significantly less toxic than DNA therapeutics. Despite its promise, mRNA production requires expertise, especially in template development and purification. Fortunately, Curia is only adding to its already wealth of mRNA experience, by investing in R&D to address known challenges and actively pursuing partnerships to advance mRNA technology. To help advance mRNA technology and other matters of medical interest, Curia is engaging in several private and public partnerships.

Collaborations and Partnerships

We are pleased to be partnering with a university on continuous flow processing for mRNA production to accelerate its timelines. We also have a collaboration with Corning to advance continuous flow chemistry for targeted development and commercial-scale manufacturing of APIs and intermediates. Government collaborations further our mission to advance drug research and development, leveraging our expertise across therapeutic areas. These collaborations underscore our commitment to improving patient outcomes.

Artificial Intelligence

Emerging technologies such as artificial intelligence will also have a positive impact on patients, as they are poised to revolutionize drug discovery and development and manufacturing, reducing timelines and enhancing quality. AI’s predictive capabilities, combined with human expertise, hold tremendous potential for expediting drug development and improving patient care.

A Personal Note

As a part of Curia, I take pride in our patient-centric approach to innovation. Our dedication to improving patient lives remains unwavering, driving us to push the boundaries of pharmaceutical research and development.

By embracing innovation, fostering partnerships, and prioritizing patient needs, Curia is poised to shape the future of the pharmaceutical industry, delivering impactful solutions to global healthcare challenges.

Learn more about Curia. Connect with our experts. https://ter.li/p0ku83

Christopher Conway is R&D President at Curia Global.

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Why Aren’t More Oligonucleotide Drugs Getting to Market?

Interest in oligonucleotide-based therapeutics has steadily increased over the last decade, particularly following the successful use of the Pfizer mRNA vaccine to protect populations from SARS-CoV-2. Our market research has identified 430 active oligonucleotide research programs spanning six therapeutic areas, with 448 drugs in development focusing on three major modalities: antisense oligonucleotides (ASOs), messenger ribonucleic acids (mRNAs), and short-interfering ribonucleic acids (siRNAs). However, the vast majority of these products remain in purgatorial preclinical and clinical development phases.

Despite the growing body of evidence supporting the efficacy of oligonucleotide therapeutics, drug developers encounter challenges bringing their products to market due to bioanalytical testing bottlenecks. Few biotech companies possess the capabilities, budget, or regulatory experience to handle these assays in-house.

So, Why Not Outsource?

Many small companies hesitate to outsource because they fear losing control over essential analytical testing processes. Experiences with oversubscribed large contract research organizations (CROs) including long wait times and opaque services may have been discouraging as well.

We propose finding CRO partners that will provide open communication and flexible approaches, because developing bioanalytical methods for oligonucleotides requires iterative R&D experimentation, data analysis, and optimization.

It is essential to have reliable quantification methods with sensitivity and selectivity, particularly during toxicokinetic (TK) and pharmacokinetic (PK) studies. These methods provide critical information about the absorption, distribution, metabolism, and excretion patterns in vivo as well as the safety and efficacy of the product.

Challenges in Bioanalytical Method Development

1. Analytical Sensitivity: Oligonucleotides often exhibit low concentrations in biological matrices, necessitating high analytical sensitivity to detect and quantify them accurately. The challenge lies in developing sensitive methods that can reliably measure oligonucleotide concentrations even at these low levels, minimizing the risk of false negatives or incomplete data.

2. Selectivity and Specificity: Differentiating the therapeutic oligonucleotide from endogenous oligonucleotides and other interfering substances is critical for reliable PK and TK analysis. Achieving selectivity and specificity is a complex task, especially considering the potential for off-target binding and interference from similar biomolecules or metabolites.

3. Sample Preparation and Stability: Due to their susceptibility to degradation by nucleases and other factors, oligonucleotides require careful sample preparation and handling to maintain their integrity during PK and TK studies. Ensuring stability throughout the analysis process is crucial for obtaining accurate and reliable data.

Achieving High Sensitivity and Selectivity Is Crucial for Bioanalytical Success

Take our high-resolution mass spectrometry (HRMS) method for Inclisiran, a double stranded siRNA product, for instance. In particular, our implementation of ion-pairing reagents during the mobile phase improved ionization and chromatographic separation significantly. This demonstrated the method’s ability to overcome matrix effects and solidified its suitability for absolute qualification and comprehensive profiling.

Consistent sensitivity for chromatographic readings at each extracted sample from matrix with injection volume of 5 µL, indicated that the method was highly reproducible and sensitive, achieving a lower limit of quantification (LLOQ) of 50 ng/ml. This LLOQ was within expected parameters and is highly suggestive of selectivity with minimal risk of off-target binding in vivo.

Transparent CRO Partnership Provides Detail Necessary for Regulatory Success

Direct communication of results enabled our clients to go further with their analyses, obtaining quantitative data on sense and antisense strands that would not have been possible without an agile and flexible approach. Likewise, because our lab team is directly in client meetings, speaking scientist to scientist, we are able to clearly understand our clients’ concerns regarding finite sample volume and develop methods that required minimal injection volumes.

Drug development is evolving, and our client base is expanding as companies recognize the importance of transparent communication and flexibility among collaborators to overcome research bottlenecks, particularly in the dynamic biologics market. With 300+ validated methods, 11 successful regulatory audits, and 168 active global customers, our core focus on quality, speed, and flexibility is proving successful.

Learn more www.sannova.net.

For more information contact: Charlie Zogzas, PhD, SVP of Business Development, czogzas@sannova.net.

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In 1986, the FDA approved the first therapeutic monoclonal antibody.¹ Now, nearly 40 years later, “antibodies have become the fastest-growing class of biological drugs approved for the treatment of a wide range of diseases, from cancer to autoimmune conditions,” according to a team of experts from the Pennsylvania-based Geisinger Commonwealth School of Medicine.²

Although therapeutic antibodies offer a wide range of benefits, from high affinity and specificity to multiple mechanisms of attack on diseases, scientists need tools that “address the challenge of screening millions of antibody-producing cells to find the best candidates,” says Bob Chen, PhD, senior director, discovery systems at OmniAb.

Traditionally, scientists produced monoclonal antibodies by applying hybridoma technology to mice, subsequently testing the therapeutic potential of the antibodies, one by one. Such methods, however, “cause the loss of valuable immune repertoire information and time,” Chen says. “Instead, we have the ability to  utilize AI-empowered single-cell screening to analyze millions of B-cells and efficiently identify high-affinity clones directly from our animals, including transgenic mice and rats, as well as cows and chickens. Then, we use AI to further expand the insights gained from a few hundred well-validated sequences, broadening our understanding over a larger space.”

To analyze the potential therapeutic antibodies, OmniAb developed xPloration®, which incorporates AI in a platform that can collect thousands of antibody variants from millions of single B cells. This platform includes about 1.5 million microcapillaries that are just 40 micrometers in diameter and one millimeter long. “This enables robust spatial separation of
single cells for various assays,” Chen explains. “Our most common use case is a selective binding assay for antibodies.”

Then, automated imaging and AI-based machine vision algorithms, including classification and segmentation, identify the B cells that are creating antibodies with the desired features, such as binding a particular target. “These AI models are trained on expert-labeled data,” Chen notes. “So, we can use AI to democratize the skill set of expert users to all users of the platform.” B cells identified with the desired phenotype are collected with a proprietary laser recovery technology.

Selecting the sequences

OmniAb turns to Biological Intelligence, the interplay between rational genetic design and immunization, to generate the initial large, high-quality antibody repertoire. “To get the most out our diverse repertoires, we need high-throughput tools,” according to Chen. For the large-scale mining of the immune repertoires, OmniAb utilizes xPloration, in which a single run can screen millions of B cells and identify thousands of potential hits.

Then OmniAb can use its suite of in silico tools, OmniDeep, which integrates structural modeling, multi-species antibody databases, molecular dynamics simulations, AI, and machine and deep learning sequence models, to aid in narrowing down to hundreds or thousands of antibodies that possess the desired affinity, specificity, and other features that enhance the odds of efficiently developing a novel therapy. For example, one of OmniAb’s collections of data produced about 10 million antibody sequences, generating 5,000 hits which were sorted with xPloration and characterized with hundreds of affinity measurements, resulting in hundreds of high affinity and well behaved clones.

OmniAb is spearheading the use of AI with immunized animals, using deep learning to strengthen the core ability of the company. “After AI learns the space, it can suggest a large number of clones to test,” Chen says. “To improve the iteration-cycle time, we are using expression libraries to evaluate AI-selected sequences on the order of thousands of selections.”

Moreover, OmniAb’s approach features two fundamental capabilities. “We analyze antibodies secreted by B cells against membrane-based targets, such as GPCRs and ion channels, in their native format on the surface of cells,” Chen continues. “Plus, we have the throughput to find rare binding events—if they exist.”

The vast antibody space offers millions of opportunities to develop therapies that precisely target diseases. Developing the best therapeutic antibodies over the next 40 years, though, depends on efficiently finding the best ones.

Learn more www.omniab.com

References

1. Lu, R-M., Hwang, Y-C., Liu, I-J., et al. Development of therapeutic antibodies for the treatment of diseases. Journal of Biomedical Science 27: 1. (2020).
2. Sharma, P., Joshi, R.V., Pritchard, R., et al. Therapeutic antibodies in medicine. Molecules 28(18): 6438. (2023).

The post Accelerating the Search for Therapeutic Antibodies appeared first on GEN - Genetic Engineering and Biotechnology News.

Rapid determination of the concentrations of endogenous metabolites in biological systems is of unquestionable scientific value across applications such as drug discovery and development, microbiome science, synthetic biology, health, nutrition, and agriculture. Yet, it remains a holy-grail problem in the analytical sciences.

Absolute quantitation offers objective measurements that connect directly to translational biology, kinetics, and phenotype in a way that relative quantitation simply does not. Furthermore, grounding measurements in absolute concentration units inherently provides seamless comparability across data sets acquired at different times, on different instruments and across different studies or experiments.

To address these challenges, we harnessed recent breakthroughs in machine learning to reimagine how LC-MS–based untargeted metabolomics is performed. Our approach enlists large-data semantic models and transformer-based architectures, to learn the quantitative relationship between raw MS data and the concentrations of the molecules present in the sample.

Pyxis is an AI-enabled technology for absolute quantitation of untargeted analytes that: (1) standardizes analysis to remove custom method development; (2) allows non-experts to rapidly determine absolute analyte concentration by eliminating highly specialized tasks; and (3) return concentrations for an increasingly broad set of analytes.

Quantitative Metabolomics—The Problem

LC-MS is a spectacularly powerful tool for the detection and identification of biologically critical metabolites. While peaks in an untargeted LC-MS chromatogram can be associated directly with molecular identity, integrated peak area is only indirectly associated with concentration.

The functional output differences between relative and absolute quantitation are demonstrated in Figure 1—which shows relative quantitation in panel A and absolute concentration in panel B. The x-axis in both panels is the true concentration of 50 analytes. In Figure 1A, changes in concentration are captured as increases in peak area, yet both the experimentally observed abundance (peak area), and the scale of the change (slope), are deeply analyte dependent.

In contrast, the y-axis in Figure 1B is in micromoles per liter (µM)–a universal and reproducible scale. Even more powerful than the experimental utility of global comparability, absolute metabolite concentration is a deeply biologically relevant quantity. Absolute concentration can be used to gain better understanding of enzyme kinetics to model pathways and in the development and validation of mathematical models of metabolism.

While the power in directly reporting absolute concentrations of metabolites is evident, in conventional workflows, converting peak area to concentration is achieved by explicit analyte-by-analyte calibration. Absolute concentration is thus limited to narrow panels of selected molecules for which a method is developed, and standards are available.

Introducing Pyxis

The first application of the Pyxis technology is focused on the identification and quantitation of polar metabolites. It includes five critical technology pillars—(1) universal calibrators (StandardCandles) to represent chemical space of polar metabolites, (2) a turn-key LC-MS method optimized for speed and broad, sensitive detection, (3) an immense, well labeled internal training data set used as input for (4) the unique Pyxis ML model, and (5) the secure cloud-based software platform.

The model is constructed to predict absolute concentration based on generic chemical structure, not specific analyte behavior and is thus functionally an untargeted assay designed to identify and quantify a broad range of analytes, rather than a targeted assay where the results are applicable to a small subset of analytes.

Matterworks has recognized the immense power of absolute quantitation to metabolomics and has reimagined what is possible from raw LC-MS data. In a truly interdisciplinary effort, we are taking powerful AI techniques developed for language and image processing and applying them to LC-MS data, enabling the direct transformation of uninterpreted, raw LC-MS data to a biologically actionable list of the identities and concentrations of detected metabolites.

Learn more www.matterworks.ai/pyxis.

The post Simple, Scalable Absolute Concentrations in Untargeted Metabolomics appeared first on GEN - Genetic Engineering and Biotechnology News.