AI-generated digital twins to strengthen SOLA's early-phase ALS study and support disciplined, data-driven development decisions
SAN FRANCISCO, CA / ACCESS Newswire / March 10, 2026 / Unlearn, a pioneer of AI-generated digital twins for clinical development, today announced it will support SOLA Biosciences Inc. ("SOLA") in its Phase 1/2 clinical study of SOL-257, an investigational gene therapy designed to address a key pathological driver of amyotrophic lateral sclerosis (ALS).
Detecting meaningful changes in clinical outcomes during early-stage ALS studies is critical for evaluating investigational therapies and informing decisions about progression to later-stage development. These efforts are often complicated by disease heterogeneity, functional decline over time, and the difficulty of generating confident, interpretable findings from small early-phase studies. SOLA is designing a long-term Phase 1/2 study intended to better assess early, directional signals of clinical activity in patients with ALS.
The Phase 1/2 study is designed as a single-arm trial, a common approach in early-stage ALS development where the use of a concurrent control group may be impractical. In the absence of a traditional control arm, digital twins of trial participants can be used as external comparators to help contextualize observed outcomes and support the interpretation of early clinical data. Digital twins are intended to work within the framework of, and not replace, established statistical and clinical analyses. All digital twin analyses are prespecified and conducted alongside standard methodologies, consistent with regulatory expectations for external comparators.
"Early-phase single-arm studies in ALS are often where promising therapies lose clarity. That's exactly the problem digital twins are designed to solve, and why we're excited to support SOLA's program," said Steve Herne, CEO of Unlearn.
Unlearn's digital twins of study participants are created by an ALS-specific Digital Twin Generator, an advanced machine-learning model trained on extensive, patient-level historical ALS clinical data. The digital twins will be used to support trial planning and prespecified analyses in the Phase 1/2 study.
"SOL-257 is designed to address a core pathological driver of ALS. In this Phase 1/2 study, our objective is to generate data that meaningfully informs downstream development decisions. Incorporating AI-generated digital twins strengthens the scientific rigor of our study design and supports disciplined, data-driven development decisions as we advance SOL-257," said Keizo Koya, Founder and CEO of SOLA.
Unlearn's support will follow a staged approach, beginning with data-driven trial planning and regulatory support and extending into the incorporation of digital twins as participant-level external comparators during the Phase 1/2 study and long-term follow-up.
About Unlearn
Unlearn exists to transform clinical development by making every trial smarter. Partnering with pharmaceutical and biotechnology companies, Unlearn harnesses data, AI, and digital twins to enable faster, more robust studies and clearer decision-making across clinical development. With a science-first approach and deep regulatory engagement-including EMA qualification and FDA support-Unlearn brings unmatched scientific credibility to applying AI in clinical trials.
For more information, visit www.unlearn.ai or follow us on LinkedIn and X/Twitter.
Media Contact:
Heather D'Angelo
heather@unlearn.ai
SOURCE: Unlearn AI
View the original press release on ACCESS Newswire:
https://www.accessnewswire.com/newsroom/en/business-and-professional-services/unlearn-to-support-sola-biosciences-clinical-study-using-ai-gene-1144119
