insitro and Bristol Myers Squibb have expanded their ALS collaboration with two new targets identified using AI.

The companies said the agreement now includes two additional therapeutic targets, ALS-2 and ALS-3, alongside the previously nominated ALS-1, as they look to develop disease-modifying treatments for amyotrophic lateral sclerosis.

The expansion triggers a $10 million milestone payment to insitro and broadens the scope of the collaboration, which focuses on identifying biological drivers of ALS using human-derived data and machine learning.

insitro will continue to advance an oligonucleotide programme for ALS-1, while also progressing a small molecule programme for Bristol Myers Squibb targeting the same biology. The multi-modality approach reflects ongoing uncertainty in how best to intervene in ALS, where multiple therapeutic strategies are often explored in parallel.

The newly nominated targets were identified through insitro’s Virtual Human platform, which combines cellular data with computational models to map disease mechanisms. The company said the targets are linked to pathways associated with TDP-43 dysfunction, a hallmark of ALS seen in the majority of patients.

Preclinical validation in motor neuron models showed that modulating these targets improved neurite growth and reversed key molecular features associated with the disease, including abnormal RNA processing.

Daphne Koller, founder and chief executive officer of insitro, said: “We are driven by a sense of urgency to translate our biological insights into meaningful clinical outcomes for the ALS community.”

She added: “By expanding our collaboration with Bristol Myers Squibb, we are broadening our approach to tackling this devastating disease, with a set of compelling targets that address its fundamental mechanisms.”

The collaboration highlights continued interest in applying AI to target discovery, particularly in complex neurodegenerative diseases where traditional approaches have had limited success. ALS remains a high unmet need, with few effective treatments and a poor prognosis.

While the addition of new targets suggests progress in early discovery, the programmes remain at a preclinical stage. The long-term impact of the collaboration will depend on whether these targets can translate into viable clinical candidates.

The deal also reflects a broader trend of large pharma companies partnering with AI-driven biotech firms to expand early-stage pipelines, particularly in areas such as neuroscience where biological complexity has slowed drug development.