What's in store for cell and gene therapy in 2023

[Credit: National Human Genome Research Institute]

The complexity and diversity of cell and gene therapies and treatments still restrains the industry’s ability to identify and deliver the proper treatment and a positive patient experience. In 2023, I expect we will see a considerable increase in critical data gathering and machine learning analysis that will lead to substantive improvements. This use of machine learning requires a continual commitment to invest in technology as it develops to ensure the required infrastructure is in place to achieve the most significant advances. And, while the infrastructure required to optimize machine learning fully is still in development, we will begin to realize its impact on drug discovery and development and on our ability to deliver personalized medicine this year.

Such leaps forward in the cell and gene therapy industry requires a growing emphasis on innovation. And true innovation requires an organizational culture that gives employees the time and permission to tackle challenges without excessive oversight. In the right environment, like-minded people find each other and work toward ground-breaking solutions. Leaders need to trust that their people know where innovation can make the most impact, all the while clearly articulating that lack of success is not failure. Companies must organize their most innovative services around teams with the autonomy to take on the challenges they see as most critical. Leaders need to make it their priority to support employees by making sure they have the time to spend on innovation.

In such an environment, we will see researchers begin to utilize machine learning to identify underlying genetic factors for certain diseases by looking for genetic patterns in patients. This research has the potential to increase the industry’s knowledge about why certain patients respond to specific therapies. Knowing how genetic factors impact each patient’s treatment will clarify the overall complexity around different options and enable a model of shared decision-making where medical professionals partner with patients and their families to choose the best course of treatment.

Machine learning will also be important in lab-based data analysis of disease genomes to improve the quality of research leading to the development of better therapies. By synthesizing information across the entire supply chain, including patient, donor collection, shipping, manufacturing and outcomes data, our industry will develop insights that can drive improvements in the safety and efficacy of therapies.

Gregg Bodnar

Finally, the cell and gene therapy industry must expand the use of community-based providers to help identify and educate patients for whom these new therapies have not always been an option. Building more robust engagement with community-based providers also increase trust in groups where lack of transparency has caused skepticism. Providing consistent information from non-biased sources expands patients’ and their families’ knowledge about what options are available. Companies can pave the way for better patient experience by contributing to organizations that provide patient advocacy and financial support for those who, traditionally, have not had access to more expensive health care.

Gregg Bodnar is director, account management at Be The Match BioTherapies.