N※N

Excelsior Sciences Secures $95 Million Series B to Accelerate AI-Driven Small-Molecule Drug Development

85

  //science-technology.news-articles.net/content/2 .. e-ai-driven-small-molecule-drug-development.html
  Published in Science and Technology on Wednesday, December 3rd 2025 at 10:10 GMT by reuters.com

• 🞛 This publication is a summary or evaluation of another publication
• 🞛 This publication contains editorial commentary or bias from the source

2025-12-03 200 x 200 / 3501 Bytes

2025-12-03 224 x 224 / 6137 Bytes

2025-12-03 224 x 224 / 7704 Bytes

2025-12-03 233 x 216 / 11131 Bytes

Excelsior Sciences Secures $95 Million to Accelerate Small‑Molecule Drug Development

In a move that underscores the growing focus on small‑molecule therapeutics, biotech start‑up Excelsior Sciences announced on December 3 that it has closed a $95 million Series B financing round. The round, led by a coalition of strategic investors including Biogen, Johnson & Johnson’s pharmaceutical arm, and the private‑equity firm Gores, aims to fast‑track the company’s proprietary platform and its early‑stage drug candidates into clinical development.

A Quick Look at the Deal

The announcement came through a press release that echoed the company's own narrative on its website (excelsiorsciences.com), where it details its mission: to create a next‑generation, machine‑learning‑driven discovery platform that shortens the path from target to candidate drug. The funding round also involved participation from smaller venture funds such as Atlas Venture and Flagship Pioneering, further cementing confidence in the company’s technology.

The Technology Behind the Promise

Excelsior’s core strength lies in its “Accelerated Discovery Platform” (ADP), a hybrid system that marries artificial‑intelligence‑guided molecular design with high‑throughput synthetic chemistry. The platform uses deep learning to predict physicochemical properties, potency, and ADME (absorption, distribution, metabolism, excretion) profiles before any compound is even synthesized. According to the company’s website, ADP has already produced more than 40,000 “lead‑like” molecules in less than 12 months of operation, a remarkable acceleration compared to traditional hit‑to‑lead timelines that can span 2–3 years.

The platform’s chief scientific officer, Dr. Lisa Huang, explained in the release that the AI models are trained on a proprietary dataset of over 2 million small‑molecule structures, including both publicly available data (e.g., ChEMBL, PubChem) and in‑house experimental results. This dataset gives the system a “wide chemical space” perspective, enabling it to suggest novel scaffolds that have not yet been explored by other developers.

Pipeline Highlights

While the company keeps detailed pipeline information somewhat guarded, the press release and subsequent LinkedIn post by CEO Michael Davis reveal two key therapeutic areas:

1. Metabolic Disorders – The first candidate, Exc‑01, is a selective inhibitor of the enzyme glucokinase regulatory protein (GCKR), targeting non‑alcoholic fatty liver disease (NAFLD). The compound has already completed pre‑clinical safety pharmacology and is slated to enter a Phase I/IIa dose‑ranging study in the first half of 2026.

2. Neurodegenerative Diseases – The second candidate, Exc‑12, is a small‑molecule modulator of the neuroinflammatory cascade that has shown efficacy in a mouse model of Parkinson’s disease. This candidate is planned to move into a toxicology package in 2027.

Excelsior also maintains a “dark‑box” portfolio of 10–15 compounds with potential in oncology and infectious disease, all of which are held back for further discovery work.

Strategic Partnerships and Market Context

One of the article’s highlights was the mention of a collaboration with the Molecular Discovery Center at the University of Pennsylvania. Under a joint research agreement, Excelsior’s platform will be used to screen for inhibitors of viral replication in the laboratory’s SARS‑CoV‑2 project, illustrating the platform’s versatility beyond small‑molecule therapeutics.

In the broader market, the company’s funding comes at a time when larger pharma conglomerates are reevaluating their in‑house discovery capabilities. Biogen, for instance, has been investing in generative AI tools for drug design—an investment that dovetails with Excelsior’s own approach. The partnership signals a strategic alignment between a nimble startup and a heavyweight in biologics, potentially creating a hybrid model that leverages the speed of small molecules with the sophistication of biologics.

Investor Perspectives

During a brief interview on the company’s LinkedIn page, Biogen’s head of R&D, Dr. Elena Garcia, stated: “Excelsior’s AI‑driven platform represents a new paradigm in drug discovery. We’re excited to be part of a journey that may bring affordable, oral therapies to patients faster than ever before.” Meanwhile, Gores’ partner, Thomas Gores, added: “We see a unique opportunity to blend technology and biology to unlock new treatment modalities. The company’s track record and the breadth of its pipeline provide a solid foundation for scalable growth.”

Next Steps and Milestones

With the new capital, Excelsior plans the following milestones:

• Manufacturing Scale‑Up – Expand its contract manufacturing organization (CMO) partnership with Catalent to produce GMP‑grade material for Phase I testing.
• Clinical Development – Initiate IND‑enabling toxicology studies for both Exc‑01 and Exc‑12 by Q3 2025.
• Regulatory Strategy – Engage early with the FDA to discuss potential accelerated approval pathways for NAFLD and Parkinson’s disease.
• Talent Acquisition – Hire senior chemists, pharmacologists, and regulatory affairs experts to support the pipeline.

The company’s website provides a detailed timeline that illustrates an ambitious 3‑year pathway from pre‑clinical to first‑in‑human trials, a dramatic reduction from the industry average of 7–10 years.

Bottom Line

Excelsior Sciences’ $95 million funding round is a watershed moment for a company that is aggressively pushing the boundaries of small‑molecule drug development with AI. The partnership with established pharma players like Biogen and Johnson & Johnson signals confidence in the technology’s potential to deliver clinically relevant therapies faster and more cost‑effectively. If the company can translate its accelerated discovery platform into regulatory‑approved drugs, it could reshape the pharmaceutical value chain and deliver oral therapeutics that fill gaps left by biologics. As the company gears up for its first human trials, the industry will be watching closely to see whether AI‑augmented discovery can truly accelerate the development of lifesaving medicines.