In the gene therapy space, 2023 ended with a bang: Two cell-based gene therapies – Casgevy and Lyfegenia – received FDA approval for treating sickle cell disease.1 Casgevy marks a significant milestone for the genome editing community as the first FDA-approved CRISPR-based therapy.
With these monumental successes in the rearview and JPM 2024 right around the corner, it’s natural to wonder what gene therapy breakthroughs await us this new year. Artificial Intelligence (AI) is also poised to continue its transformation of various aspects of gene therapy development and accelerate progress in 2024 and beyond.2
Let’s look at what’s in store for the gene therapy industry in the new year.
1. Highly Personalized Treatment Plans Will Become More Common
Advances in sequencing and bioinformatics have enabled a deeper understanding of individual genomes, and this year, we expect to see an increase in treatments that are not only disease-specific but also patient-specific, taking into account a person's unique genetic biomarkers. This has long been an objective of medicine, particularly for cancer, where genetic biomarkers have been integral to diagnosis, prognosis, and clinical decision-making.
By the end of 2024, AI-driven tools may be more frequently used to create highly personalized gene therapy treatment plans, tailoring interventions to each patient's unique genetics, particularly for those living with rare diseases.3
2. Predictive Modeling Will Drive Biomanufacturing Optimization
The integration of advanced computational models, which leverage machine learning (ML) and AI, with different stages of the gene therapy development pipeline will significantly enhance the efficiency and effectiveness of biomanufacturing processes in 2024.
Furthermore, predictive AI models can also help de-risk early-stage vector designs, helping to avoid downstream safety and manufacturing issues.
3. Optimized Drug Delivery Will Improve Efficiency
With the emergence of innovative delivery mechanisms, such as targeted nanoparticles and viral vectors, gene therapies can be administered more precisely to the affected cells or tissues. This precision reduces systemic side effects and improves therapeutic outcomes by ensuring that the maximum therapeutic payload reaches the intended site of action. Additionally, optimized delivery systems are expected to overcome previous challenges like immune system evasion and efficient cell entry, which have historically limited the effectiveness of gene therapies.
These improvements in 2024 will heighten the efficacy of treatments and broaden the scope of treatable genetic conditions, marking a pivotal step forward in the field of gene therapy.
4. AI Will Begin To Streamline Regulatory Process and Approval
AI algorithms can analyze vast datasets from clinical trials and real-world evidence much more rapidly and accurately than traditional methods.4 This capability allows for more efficient safety and efficacy data review.
The further implementation of AI in gene therapy development in 2024 is set to streamline the regulatory process and approval for gene therapies significantly. Moreover, AI can assist in identifying potential adverse effects or patient subgroups that might respond differently to treatment, leading to more informed decision-making.
Regulatory bodies are expected to increasingly rely on AI tools to assess complex gene therapy data, thus speeding up the approval process without sacrificing safety. This advancement is crucial in bringing new gene therapies to patients faster and addressing urgent medical needs in areas where traditional treatments have fallen short.
5. AI Will Accelerate Clinical Trial Design
AI can analyze vast datasets to identify potential patient populations and predict outcomes, leading to more efficient and targeted clinical trial designs. The application of AI in clinical trial design is set to significantly accelerate the development of gene therapies in 2024.
This approach enables researchers to refine inclusion and exclusion criteria, ensuring that trials are more likely to demonstrate the effectiveness and safety of a therapy. Additionally, AI can optimize trial protocols by predicting the best dosage and administration schedules, reducing trial durations, and increasing the likelihood of successful outcomes. The use of AI in trial design streamlines the development process, reduces costs, and enhances patient safety. As a result, the path to discovering and validating new gene therapies is expected to become more efficient and effective, driving innovation and accelerating the delivery of new treatments to patients.
6. Real-time Monitoring Will Enhance Patient Care
The integration of wearable devices and biosensors has enabled continuous monitoring of patient's physiological responses to therapies. In 2024, the gene therapy industry is expected to enhance patient care significantly through implementation of real-time monitoring technologies.
This real-time data collection allows for immediate adjustments in treatment plans, ensuring optimal dosages and minimizing potential side effects. Furthermore, remote monitoring capabilities facilitate more frequent and detailed patient-provider interactions, improving the quality of care and patient adherence to treatment protocols. Real-time data also provides invaluable insights for healthcare providers, allowing them to track the effectiveness of therapies over time and make data-driven decisions. This advancement in gene therapy patient monitoring will improve the quality of care and empowers patients in their treatment journeys, leading to better health outcomes and enhanced patient satisfaction.
In the coming year, AI is positioned to accelerate the design, manufacturing, and commercialization of gene therapies.
At Form Bio, we will continue our partnerships with gene therapy companies as an extension of their team, leveraging our in silico capabilities to accelerate research and development. These capabilities are founded on our FORMsightAI technology, enabling next-generation optimization of AAV viral vector sequences and manufacturing protocols.
AI Disclosure: Feature image was generated by AI image development tool MidJourney.