Unlearn, an AI-enabled company creating digital twins of clinical trial participants, announced a partnership to advance ALS research with biotechnology company Trace Neuroscience, which creates genomic therapies for neurodegenerative diseases.
Unlearn, founded in 2017, uses machine learning to create digital twins of clinical trial participants before being randomized in a controlled trial.Â
The digital twin can provide researchers insight into participants’ health outcomes. The company pitches its technology as a way to run smaller clinical trials more quickly since researchers can find fewer participants for the control group. Â
Additionally, Unlearn offers a Digital Twin Generator (DTG) for ALS, a machine learning model trained on more than 13,000 longitudinal clinical records from the ALS-focused digital research platform APST, the PRO-ACT database for ALS research and the Northeast ALS Consortium (NEALS).  Â
Digital twin generators predict how an individual may progress under the standard of care or in the placebo group in a clinical trial, creating a “digital twin” for each trial participant based on their data.Â
Trace Neuroscience will use Unlearn’s DTG ALS and its Unlearn Platform for the biotech company’s Phase 1/2 clinical trial, which targets the UNC13A protein, a genetic target directly linked to ALS progression.
Unlearn’s offerings will be used to simulate ALS disease progression and evaluate the relationship between clinical endpoints, disease status at baseline and biomarkers over time.
Trace will also use Unlearn’s platform to inform clinical trial protocol decisions.
“This collaboration brings together two powerful approaches—AI and genomic medicine—to rethink how ALS trials are designed,” Dr. Eric Green, cofounder and CEO of Trace Neuroscience, said in a statement.Â
“Working with Unlearn to mine their extensive, well-curated database through the use of the ALS DTG 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.”
THE LARGER TREND
Last year, Unlearn secured $50 million in Series C funding, bringing its total raise to more than $130 million.Â
In 2022, the company scored $50 million in a Series B financing round two years after garnering $15 million in Series A funding. Â
In December, Unlearn partnered with German-based APST Research (APST) to integrate data from over 8,000 participants in an APST longitudinal study into its DTG ALS. The dataset includes clinical data, biomarker analyses, common ALS clinical assessments and patient self-assessments.
Unlearn announced a partnership last year with biotechnology company ProJenX, which would use Unlearn’s DTG ALS to produce digital twins of clinical trial participants living with ALS.Â
The digital twins would act as a placebo for trial participants dosed with prosetin—a brain-penetrant, MAP4 kinase inhibitor—in ProJenX’s Phase 1 clinical trial.
In 2023, Unlearn announced a partnership with clinical-stage biotechnology company QurAlis Corporation to speed up QurAlis’ ALS-focused clinical program using Unlearn’s genAI technology.  Â
Other companies using digital twin technology include Singaporean startup Mesh Bio, which uses digital twins to help manage rising cases of chronic diseases, particularly in Southeast Asia.
Twin Health, a digital metabolic care company, offers its Whole Body Digital Twin, an AI-backed model aimed at providing individualized nutrition, sleep and activity guidance to help people prevent and reverse metabolic diseases like Type 2 diabetes.
Unlearn, an AI-enabled company creating digital twins of clinical trial participants, announced a partnership to advance ALS research with biotechnology company Trace Neuroscience, which creates genomic therapies for neurodegenerative diseases. Unlearn, founded in 2017, uses machine learning to create digital twins of clinical trial participants before being randomized in a controlled trial. The digital twin can provide researchers insight into participants’ health outcomes. The company pitches its technology as a way to run smaller clinical trials more quickly since researchers can find fewer participants for the control group.  Additionally, Unlearn offers a Digital Twin Generator (DTG) for ALS, a machine learning model trained on more than 13,000 longitudinal clinical records from the ALS-focused digital research platform APST, the PRO-ACT database for ALS research and the Northeast ALS Consortium (NEALS).   Digital twin generators predict how an individual may progress under the standard of care or in the placebo group in a clinical trial, creating a “digital twin” for each trial participant based on their data. Trace Neuroscience will use Unlearn’s DTG ALS and its Unlearn Platform for the biotech company’s Phase 1/2 clinical trial, which targets the UNC13A protein, a genetic target directly linked to ALS progression. Unlearn’s offerings will be used to simulate ALS disease progression and evaluate the relationship between clinical endpoints, disease status at baseline and biomarkers over time. Trace will also use Unlearn’s platform to inform clinical trial protocol decisions. “This collaboration brings together two powerful approaches—AI and genomic medicine—to rethink how ALS trials are designed,” Dr. Eric Green, cofounder and CEO of Trace Neuroscience, said in a statement. “Working with Unlearn to mine their extensive, well-curated database through the use of the ALS DTG 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.” THE LARGER TREND Last year, Unlearn secured $50 million in Series C funding, bringing its total raise to more than $130 million. In 2022, the company scored $50 million in a Series B financing round two years after garnering $15 million in Series A funding.  In December, Unlearn partnered with German-based APST Research (APST) to integrate data from over 8,000 participants in an APST longitudinal study into its DTG ALS. The dataset includes clinical data, biomarker analyses, common ALS clinical assessments and patient self-assessments. Unlearn announced a partnership last year with biotechnology company ProJenX, which would use Unlearn’s DTG ALS to produce digital twins of clinical trial participants living with ALS. The digital twins would act as a placebo for trial participants dosed with prosetin—a brain-penetrant, MAP4 kinase inhibitor—in ProJenX’s Phase 1 clinical trial. In 2023, Unlearn announced a partnership with clinical-stage biotechnology company QurAlis Corporation to speed up QurAlis’ ALS-focused clinical program using Unlearn’s genAI technology.   Other companies using digital twin technology include Singaporean startup Mesh Bio, which uses digital twins to help manage rising cases of chronic diseases, particularly in Southeast Asia. Twin Health, a digital metabolic care company, offers its Whole Body Digital Twin, an AI-backed model aimed at providing individualized nutrition, sleep and activity guidance to help people prevent and reverse metabolic diseases like Type 2 diabetes.
