Cell and gene therapies (CGT) hold the promise of treating or even curing some cancers and rare diseases. But these emerging therapies are also among the world’s most expensive treatments—with some priced between $400,000 and $2 million per dose, sometimes more. Still, a potential wave of new gene therapies is building on the horizon. The CGT market is expected to nearly quadruple over the next three years—from $5.3 billion in 2022 to $19.9 billion by 2027.1
Last year was a breakthrough year for cell and gene therapies, with seven FDA approvals in the U.S. and one in the European Union. Currently, more than 2,000 clinical trials are being conducted globally. With approximately 10% of them in Phase III, it is likely that 75 therapies will be approved much sooner than 2030. Projections for 2024 are set at about 17 approvals between the U.S. and EU.
2023 cell and gene therapy approvals
Currently, there are 33 approved cell and gene therapy products listed on the FDA’s website. Seven of those approvals occurred in 2023 alone, including:
- Casgevy: cell-based gene therapy for the treatment of sickle cell disease;
- Lyfgenia: cell-based gene therapy for the treatment of sickle cell disease;
- Elevidys: gene therapy for the treatment of pediatric patients with Duchenne muscular dystrophy;
- Vyjuvek: gene therapy for the treatment of wounds in patients with dystrophic epidermolysis bullosa (DEB) with mutation(s) in the collagen type VII alpha 1 chain (COL7A1) gene;
- Roctavian: gene therapy for the treatment of adults with severe hemophilia A without pre-existing antibodies to adeno-associated virus serotype 5;
- Omisirge: cell therapy to quicken the recovery of neutrophils (a subset of white blood cells) in the body and reduce the risk of infection;
- Lantidra: cellular therapy made from deceased donor pancreatic cells for the treatment of type 1 diabetes.
At over 3,700 developmental candidates, the pipeline for advanced genetic therapies is both growing and diversifying. Gene and cell therapies are expanding well beyond their original proof-of-concept indications, and the COVID-19 pandemic has validated the potential of RNA vaccines.
In 2024, up to 21 cell therapy launches and as many as 31 gene therapy launches are expected1, possibly including the first-ever approval of adoptive cell therapy for solid tumors and the first U.S. approval of an allogeneic T-cell therapy.
“The use of CAR-T cell therapy to treat cancer has been remarkably successful in the treatment of blood cancers (leukemia, lymphoma, myeloma),” said David Sykes, MD, Physician Investigator, Center for Regenerative Medicine, Massachusetts General Hospital. “In 2024, I anticipate that we will see CAR-T cell treatment successes in advanced solid tumor malignancies like colon cancer and ovarian cancer. It will be fascinating to see how far scientists and doctors can push these cellular therapies (CAR-T, CAR-Macrophages, CAR-NK-cells, CAR-Neutrophils) for the treatment of cancer and autoimmune disease.”
The use of AI
To date, no new drug has been developed and approved based on fully AI-generated drug discovery; however, the pipeline of drugs in development with AI-associated platforms are growing. In 2023, at least 19 drugs were in clinical development attributed to AI, and some of these drug candidates may be advancing in the clinical pipeline in 2024.
While AI can bring value to cell and gene therapy R&D across multiple stages, the consulting firm McKinsey & Company sees its biggest impact in target identification, payload design optimization, and translational and clinical development.2 For example, AI and machine learning (ML) can help researchers hone in on the appropriate target to optimize the probability of therapeutic success.
For viral therapeutics that aim to edit the genome, algorithms to predict CRISPR target sites can help identify genomic sites with genetic sequences or epigenetic features that permit increased efficiency of editing with minimal off-target activity. For mRNA-based vaccines, AI and ML can be used to predict tumor epitopes that could be bound by the therapeutic molecule. For CAR T-cell therapies, the technology can be used to facilitate the identification of appropriate antigens and binding sites, thereby enabling the design of CARs that have improved on-target activity and minimal cytotoxicity.2
Similarly, AI and ML models can also be used to screen high numbers of candidates rapidly and select designs that fulfill the desired criteria. To be most effective, the models should be part of an AI-enabled closed-loop research system, with initial primary screening results automatically fed into an ML pipeline. This pipeline starts to learn how the assay responds to each payload based on its computational features. It then suggests a next batch of optimized payload candidates for experimentation. Resulting experimental data are in turn automatically fed back to continue the learning, closing the research system.2
During the translational and clinical development stage, AI and ML can assist in getting cell and gene therapy to the clinic by minimizing safety risk in clinical trials, specifically by finding translational biomarkers indicative of success, identifying the right patients, estimating optimal dosing, and predicting severe adverse events based on patient profile and real-world data from similar treatments.2
The cell and gene therapy workflow
Regardless of the workflow, cell and gene therapy manufacturing faces challenges in ensuring consistency and product quality. Ideal instruments are those designed to reduce cell damage during sorting and improve cellular metabolic analysis and high-throughput visualization to increase quality.
On-chip Technologies offers instruments that enable sterile, damage-free cell sorting, easy generation of stable droplets, easy adjustment of droplet size and real-time monitoring of droplet generation. The On-chip Droplet Generator, for example, allows for mass production of micrometer-sized aqueous droplets suspended in oil by utilizing a unique microfluidic chip. The individual water-in-oil droplets function as a miniaturized vessel for reactions such as microbial/cell cultivation and genetic analysis.
Imaging and analysis systems for 2D and 3D cultured cells are also integral to the cell and gene therapy workflow. Capturing this data at high speed allows high-confluence and non-uniform organoid images to be accurately extracted, measured and detected by degree of differentiation and cell morphology.
For cancer immunotherapies like CAR T-cell therapy and T-cell receptor (TCR)-based therapies, cellular metabolic activities are a crucial data point. A main component of cellular energy metabolism is the glycolytic pathway. While, traditionally, glycolytic pathway analysis has been conducted using estimates of glucose and lactate concentrations derived from data points taken from periodic sampling, some researchers have turned to live cell metabolic analyzers. These instruments provide real-time, continuous monitoring and visualization of glycolytic changes—without periodic sampling. Instead, they reveal changes in metabolic rate that occur between each media change.
A critical tenet of cell and gene therapy is low contamination risk. Researchers achieve that goal in a multitude of ways, including employing single use technology products whenever possible. Single use technology solutions are known for their reduced risk of contamination, as well as shortened turnover time for equipment. Common single use technology products include bioprocess containers, mixers, bioreactors, bottle, fluid transfer assemblies and more.
Lastly, in cell therapy, closed manufacturing systems are designed to minimize contamination risks and reduce ISO cleanroom requirements. In combination with digital connectivity, these systems enable repeatable, trackable and GMP-compliant manufacturing processes.
References
1. The Evolution and Future of Cell & Gene Therapy. Deloitte United States. https://www2.deloitte.com/us/en/blog/health-care-blog/2023/the-evolution-and-future-of-cell-and-gene-therapy.html
2. How artificial intelligence can accelerate research and development for cell and gene therapies | McKinsey. www.mckinsey.com. https://www.mckinsey.com/industries/life-sciences/our-insights/how-ai-can-accelerate-r-and-d-for-cell-and-gene-therapies