2024 predictions in clinical intelligence

2024 predictions in clinical intelligence

Rohit Nambisan and Andreas Matern of Lokavant share insights on where they see AI in clinical research and personalized medicine development next year.

Rohit Nambisan, CEO & co-founder

Data sharing and cross-industry collaboration will power the AI revolution in clinical research in 2024. No one company has enough data to drive accurate productions around a single disease or use case – which is why cross-industry collaboration like we witnessed during the pandemic – will be reinvigorated. During COVID, pharmaceutical companies, clinicians, researchers, technology companies, and regulators worked together in harmony so it can be done.

A current example of how this can work is the MELODY trial. Melody is using federated learning, a data-sharing model that protects companies’ proprietary information while still sharing important research data, to provide much-needed, high-quality protein data to help AL/ML models design proteins faster. Protein drug development is notoriously long, arduous, and costly. But, in the MELODY trial, the contributing organizations can use AI to adopt generative biology and are experiencing greater efficiency than any individual organization could alone.

Without this level of collaboration, AI won’t work, as it won’t provide tangible ROI so investment (and adoption) will slow to a trickle.” 

 

Andreas Matern, executive vice president of product development

“Personalized medicine development will continue its fast pace in 2024, which will lead to a proliferation in data types (including an increased focus on genomic data) and more adaptive trial designs. Data collection, and, hopefully, data sharing will take center stage next year – enabling us to pursue additional research questions and perform meta-analyses. Despite all the hype around AI and Large Language Models, the key for AI success is our ability to access volumes of well-harmonized, governed, real-world data. With more personalized approaches, clinical trials grow more complex – requiring, again, better modeling and data collection plus a reliance on modern-day data engineering and data scientists to identify trends and understand the causality of the therapeutic interventions in question.

The side effects of the pandemic will continue to unfold in 2024, as well. We will see more remote monitoring of patients, as well as the adoption of more digital health technologies, including mobile apps and specialized devices. Collecting and gaining insights from these data sources, coupled with the continuing trend of distributed clinical trials will require data strategies from both sponsors and CROs that leverage cloud computing and data governance at a scale that is much different than today.”