Trace plans ALS trial of UNC13A treatment with help from AI tools
Study will utilize Unlearn's ALS DTG to make a 'duplicate' of each participant
Trace Neuroscience plans to test genomic medicine that targets the UNC13A protein in people with amyotrophic lateral sclerosis (ALS) in a Phase 1/2 clinical trial that will be supported by artificial intelligence (AI)-powered tools from Unlearn.
Unlearn’s Digital Twin Generator for ALS (ALS DTG) will be used to create a “digital twin” for each trial participant, this way predicting how their disease would progress under standard care or in a placebo group of a clinical trial.
Trace, which launched last year with more $100 million in capital, will use the data to inform trial protocol decisions, such as inclusion/exclusion criteria and study endpoints, to boost the likelihood of detecting a therapy’s effectiveness on clinical outcomes and biomarkers.
“This collaboration brings together two powerful approaches — AI and genomic medicine — to rethink how ALS trials are designed,” Eric Green, MD, PhD, co-founder and CEO of Trace, said in a company press release. “Working with Unlearn … will enable us to explore smarter designs and make confident and informed decisions as we plan our Phase 1/2 trial. Ultimately, these insights can help us to move faster for people living with ALS who are waiting for new treatment options.”
In ALS, the nerve cells that communicate with muscles to control voluntary movement are progressively lost, leading to worsening muscle weakness that drives movement difficulties and problems with breathing, swallowing, and speaking.
Trace’s lead candidate is intended to improve nerve-muscle communication by enabling more normal production of UNC13A, a protein that’s important for nerve cell communication and which is deficient in most people with ALS.
Targeting the UNC13A protein in ALS
For some people, mutations in the UNC13A gene have been linked to ALS development and progression. For others, problems with the TDP-43 protein can lead to a loss of UNC13A protein production even when no UNC13A mutation is present.
In nearly all cases of ALS, an abnormal version of TDP-43 clumps up in parts of the cell that it shouldn’t. Normally, TDP-43 helps ensure proper gene activity within the cell’s nucleus, where genetic material is stored. But the abnormal version of TDP-43 in ALS instead accumulates in the cytoplasm, or fluid-filled space outside the nucleus, and isn’t able to serve its usual role. This can disturb activity of the genes TDP-43 usually targets and affect production of important proteins. One such gene is UNC13A, which encodes the UNC13A protein.
Trace’s candidate is an antisense oligonucleotide, or small strand of genetic material that’s designed to bind to UNC13A’s genetic template molecule called messenger RNA and ensure it can be properly processed to produce a functional protein. Restoring UNC13A levels will help aid nerve-muscle communication to preserve or improve muscle function in ALS, the company maintains. Because UNC13A deficiency seems to be nearly universal in ALS, this could be effective for most patients.
“Trace Neuroscience is advancing its development program targeting the UNC13A protein … and we’re proud to support their mission by helping lay the foundation for more efficient trials and faster paths to potential treatments,” said Unlearn’s CEO Steve Herne.
Unlearn’s ALS DTG was trained to predict ALS disease trajectories from more than 13,000 clinical records obtained from various sources, including large ALS databases. The algorithm uses this information to predict a person’s likely disease course based on their characteristics. Along with simulating disease progression, the tool can help evaluate relationships between disease status at a study’s start with clinical endpoints and biomarkers over time.
The two companies plan to co-author scientific publications based on this collaboration.
While Trace is initially focusing on ALS, it believes its UNC13A-targeted approach may also aid other neurodegenerative conditions, such as Alzheimer’s disease or frontotemporal dementia.
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