Peer-Reviewed Paper
Exploiting Epigenetics to Systematically Optimise Culture Conditions for Cellular Therapies

Over the last two decades, scientists have sequenced the genome and epigenome of all known cell types in the human body, in addition to mapping hundreds of possible protein-protein interactions. The availability of biological data at this resolution and scale has enabled the development of computational tools capable of addressing the challenges associated with the development of scalable cell therapies.

Application Note
Defining Cell Culture Conditions to Drive Cell Identity and Scalability in Cell Therapy

Cell therapy is a powerful strategy to treat and cure diseases that have been untreatable to date. For many diseases, including heart disease, diabetes, and liver failure, cell replacement remains the only option for curative therapy. However, the development of cell therapies is tightly linked to our ability to culture cells in artificial environments outside of the body, i.e., in vitro conditions. In our bodies, cells live in highly regulated and specialized microenvironments, also known as niches.

Webinar: The Epigenetics Approach to Driving Cell Identity and Scalability in Cell Therapy

In the delivery of scalable cell therapies, there is a fundamental need to derive viable cells in vitro. In addition to developing cell cultures that mimic in vivo conditions for the maintenance of target cell types, cells need to acquire and develop specific therapeutic characteristics. How can epigenetics and innovative computational approaches be implemented to drive cell identity and scalability in cell therapy?

The webinar features panelists Dr. Zoe Hewitt (UK Regenerative Medicine Platform), Dr. Owen Rackham (Duke-NUS Medical School) and Dr. Rodrigo Santos (Mogrify).

White Paper
Realizing Retinal Regeneration: How can data-driven in vivo reprogramming be used to treat retinal and optic nerve degeneration?

Approximately 1 in 2,000 people worldwide are affected by inherited retinopathies but few treatment options are available for retinal degeneration. The FDA’s 2017 approval of LUXTURNA to treat inherited retinal degeneration caused by biallelic mutations in RPE65 has established viral vectors as a viable clinical therapy to monogenic retinal disease. Furthermore, advances in pluripotent stem cell techniques have enabled retinal pigment epithelium (RPE) to reach clinical trials as a cell therapy for treating age-related macular degeneration (AMD).

Application Note
Accelerating Regenerative Medicine Approaches to Type 1 Diabetes Through Direct Cell Reprogramming

Current treatment of type 1 diabetes mellitus (T1DM) depends on regular subcutaneous injections of exogenous insulin. Unfortunately, insulin therapy is associated with patient compliance issues and life-threatening hypoglycaemic events. Alternatively, recent convergences of biomaterial and regenerative medicine advances suggest transplantation of stem cell-derived beta cells as an “off-the-shelf” cell therapy treatment approach to T1DM, potentially providing long-term therapeutic benefits to patients, with minimal adverse effects.

White Paper
The progression & delivery of adoptive cellular immune therapies: leveraging single-cell resolution & novel algorithms to overcome the challenges associated with allogeneic & autologous immune cell therapies

This review published in Cell & Gene Therapy Insights discusses the current challenges for autologous and allogeneic adoptive cellular therapies (ACT) and how big dataset analysis is opening paths to overcome resistance and enhance the efficacy of ACT.

10 Considerations for Enhancing Your iPSC Processing Pipeline

How can you enhance your induced pluripotent stem cell (iPSC) processing pipeline? In this infographic, discover 10 questions you should answer to optimize your iPSC processing pipeline, enhance your protocols and ensure you have achieved your desired cell type.

Webinar: A Systematic Approach for Driving Cell Identity and Accelerating Regenerative Medicine

Discover high-resolution data, computational power, and novel algorithms as a means of exploring transcriptomic networks, systematically discovering the key regulatory switches driving cell identity and accelerating regenerative medicine.

Cell Conversion Shortcuts Mapped with Predictive System

In the cell-fate conversion landscape, the road less traveled is transdifferentiation, even though it is the straighter path between one cell type and another. The more circuitous route, up to pluripotency and then down again, is better trod, in part because the pluripotency-inducing conversion factors—Oct3/Oct4, Sox2, c-Myc, and Klf4—are so well known.

ISMB 2020 | Mogrify: A computational framework to convert between cell types

Poster presented by Kalaivani Raju, our Senior Bioinformatician, at the 28th Intelligent Systems for Molecular Biology from July 13-16, 2020.

Webinar Highlight: Transforming Personalized Medicine into Off the shelf Cell Therapies

Highlights from our webinar on transforming cell therapies from personalized, ad hoc manufacturing processes into a more scalable and accessible treatment.

Webinar: Transforming Personalized Medicine into Off the shelf Cell Therapies

Discover novel data-driven solutions to tackle the scalability and accessibility challenges associated with advanced therapeutic medicinal products.

Application Note
Computational Tools for Accelerating Regenerative Medicine

The combination of high-resolution data, computational power and novel algorithms, are enabling accelerated development of in vivo cell transdifferentiation and current cell therapies toward shorter, safer, and more robust strategies.

Application Note
Cell Therapy Manufacturing: Addressing the growing pains in cell therapy manufacturing

Cell therapy is gradually taking center stage in immuno-oncology. Developmental focus is now shifting from proving the clinical benefits of cell therapy to optimizing the processes of manufacturing products for hundreds of patients, for different conditions and at a reasonable price. Here we discuss some of the growing pains faced by the industry and possible solutions.

Application Note
Using big data approaches to develop cell therapies

Stem cell biology and medicine are effectively enabling the establishment of new cell therapies. However, current therapies are limited to a narrow set of cell types that can be isolated or created and expanded in vitro. Dr. Owen Rackham discusses how computational approaches will further enhance cell therapy applications.

Application Note
Transforming Personalized Medicine into Off-the-Shelf Cell Therapies

Despite major progress in the commercialization of advanced medicinal products (ATMPs), the development of these treatments presents manufacturability challenges and questions about bypassing patients’ immune systems. How are they addressed in the autologous and allogeneic approaches to cell therapy?

Application Note
Computational Algorithms and Large-Scale Data for CAR T Cell Therapy Resistance

CAR T cell therapy has demonstrated exceptional clinical success, despite several coexisting issues to be addressed in future products. How can computational algorithms and big data be used to overcome these challenges in future generations of CAR T cell therapy?

Application Note
Biology 3.0: The Single-Cell (R)evolution

Understanding cell regulatory pathways is one of the great challenges in biology. How do new technologies, like single-cell approaches, provide valuable insight and reduce guesswork in the future development of cell and gene therapies?

A new technology for direct cell reprogramming

How can big data and network-based algorithms be applied to transform Dr. Yamanaka’s Nobel winning discovery of induced pluripotent stem cells (iPSCs) to direct cell reprogramming of any starting cell type to any other?

Cell Therapy - Falling short of its potential?

The success of cell therapy products is defined by three factors: safety, efficacy and scalability. Gene editing technologies (CRISPR, TALENs and ZFNs) are paving the way towards allogeneic safety and ‘universal donor cells’. However, progress is difficult without the ability to produce functional cells at scale.