Incyte and Edison Scientific Announce Strategic Collaboration to Employ the Kosmos AI Platform for Research and Development

Key Terms

ai technical

Artificial intelligence (AI) is technology that enables machines to mimic human thinking and learning, allowing them to analyze information, recognize patterns, and make decisions. For investors, AI matters because it can improve how businesses operate, create new products, or identify opportunities faster and more accurately than humans alone, potentially impacting company success and market trends.

translational medical

Translational describes the process of turning basic scientific discoveries into practical medical tests, treatments or products that can be used with patients. For investors it signals how close a technology is to real-world use and potential revenue — like converting a prototype into a factory-made product — so strong translational progress can reduce technical risk and increase the chances of commercial returns.

clinical data medical

Clinical data are the facts and measurements collected from human studies about a medical product’s safety and how well it works, such as patient symptoms, lab results, and side effects. Investors care because this evidence determines whether regulators will approve the product, doctors will prescribe it, and patients will use it — much like test scores deciding if a new gadget can be sold widely and trusted by customers.

predictive models technical

Predictive models are tools that use historical and current data to estimate what is likely to happen next, like a weather forecast that translates past patterns into a probability of future conditions. For investors they matter because they turn complex information into actionable probabilities—helping estimate revenue, demand, price moves, or risks—so decisions can be made with an informed sense of likely outcomes rather than guesswork.

therapeutic performance medical

Therapeutic performance describes how well a medical treatment achieves its intended health benefits for patients—measuring effectiveness, safety, durability of effect, and real-world outcomes. Investors care because stronger therapeutic performance typically leads to regulatory approval, wider adoption by doctors and insurers, higher sales and pricing power, and lower commercial risk, much like how a reliable appliance wins more buyers and commands a higher price in the market.

target discovery and validation medical

The process of finding biological molecules or pathways that play a key role in a disease and then testing whether altering them changes the disease’s course—think of it as finding a lock (the target) and proving the lock actually controls access before designing a key. For investors, strong discovery and clear validation lower the scientific risk of a drug program, making development timelines, costs, and the odds of commercial success easier to judge.

biomarker data medical

Measurable biological signs — such as proteins, gene changes, or blood chemicals — taken from patient samples or tests that indicate disease presence, progression, or response to a treatment. For investors, biomarker data acts like a car’s dashboard: clear signals can speed up drug development, lower the risk of costly late-stage failures, and help regulators and doctors decide whether a medicine works, which affects a company’s value and commercial outlook.

biopharma medical

Biopharma companies discover and develop medicines and treatments derived from biological sources—such as proteins, cells, or genetic material—rather than from purely synthetic chemicals. For investors, biopharma matters because successful products can deliver large, protected revenues but require long, costly development and strict regulatory approval, creating a higher-risk, potentially higher-reward profile; think of them as chefs transforming living ingredients into precision medicines.

See more from StockTitan in Google Search and AI answers. Adds StockTitan as a preferred source · opens Google

Add on Google Not now

WILMINGTON, Del. & SAN FRANCISCO--(BUSINESS WIRE)-- Incyte (Nasdaq:INCY) and Edison Scientific today announced a strategic collaboration to employ Kosmos, Edison’s AI scientist, for Incyte’s discovery and development work.

Kosmos will be embedded across the Incyte discovery and development lifecycle, enabling continuous learning from translational and clinical data, real-time synthesis of evidence and predictive models of therapeutic performance.

The initial deployment will be focused on high-impact use cases in target discovery and validation and translational biology, centered on embedding Edison’s AI capabilities within Incyte’s research workflows to support more efficient exploration of experimental, clinical and biomarker data with the potential to expand across Incyte’s broader R&D organization. The companies will work together to measure impact on decision quality and long-term pipeline productivity as the system evolves.

“Our vision is for our data to become a learning system that enhances every decision,” said Pablo J. Cagnoni, M.D., President and Global Head of Research and Development at Incyte. “This partnership aims to maximize our data’s value by integrating AI to guide experimental design and improve the quality and consistency of scientific and development decisions. Our goal is not just faster development, but better outcomes across our programs.”

“By using systems that learn from our experimental and clinical data, we can enhance result interpretation, creating a feedback loop that boosts both speed and quality in future programs,” added Patrick Mayes, Ph.D., Executive Vice President and Chief Scientific Officer at Incyte.

At the core of the collaboration is a new model for biopharma: one in which a company’s data is not just stored and analyzed, but becomes a compounding asset, used to train AI systems that improve over time and systematically enhance experimental and clinical outcomes.

“Most AI efforts in pharma treat data as something to analyze,” said Sam Rodriques, Ph.D., Chief Executive Officer of Edison Scientific. “What we are building treats data as something to learn from continuously. The result is a system that compounds—where every experiment, every clinical readout and every decision improves the underlying models. That is how companies, like Incyte, will turn their data into a sustainable advantage over their competitors.”

About Incyte
Incyte is redefining what’s possible in biopharmaceutical innovation. Through deep scientific expertise and a relentless focus on patients, we have built an established portfolio of first-in-class medicines and an extensive portfolio of next-generation medicines across our key franchises: Hematology, Oncology and Inflammation and Autoimmunity.

To learn more, visit Incyte.com and Investor.Incyte.com. Follow us on social media: LinkedIn, X and Instagram.

About Edison Scientific
Edison Scientific is building the AI platform for scientific research and development. Kosmos, Edison’s collaborative AI scientist, partners with R&D teams to support critical decisions and workflows, leverage their proprietary data, and bring innovations to market faster. Edison is a scientist-led company that was spun out of the nonprofit research lab FutureHouse in 2025, backed by $70M from Spark Capital, Triatomic Capital, and other investors.

To learn more, visit edisonscientific.com and follow the company on LinkedIn and X.

Incyte Forward-looking Statements
This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995 and other federal securities laws, including statements regarding the potential for the parties’ collaboration and the Kosmos AI platform to enhance Incyte’s discovery and development lifecycle and to support more efficient exploration of experimental, clinical and biomarker data, Incyte’s aim to maximize the value of its data by integrating AI to guide experimental design and improve the quality and consistency of scientific and development decisions, Incyte’s goal of using AI to enable faster development and better outcomes across its programs, the expectation that Incyte’s data will serve as a compounding asset and competitive advantage and Incyte’s aspirations, Incyte's plans and expectations regarding the deployment of collaboration technology and goals as set forth under the heading “About Incyte.”

Actual results may differ materially from those indicated in the forward-looking statements as a result of various important factors, including: Incyte’s ability to use AI and improve the quality, consistency and speed of research and development decisions; Incyte’s ability to demonstrate the efficacy and safety of its products and product candidates; the sufficiency of clinical trial data to meet applicable regulatory standards or warrant continued development; the ability to enroll sufficient numbers of subjects in clinical trials; actions of regulatory agencies, which may affect the initiation, timing and progress of clinical trials and marketing approval; Incyte’s ability to achieve commercial success for its marketed products and product candidates, if approved; Incyte’s ability to obtain and maintain protection of intellectual property for its products and technology; Incyte’s reliance on third parties and partners; the acceptance of Incyte’s products in the marketplace; market competition, sales, marketing, manufacturing and distribution requirements; and those risks and uncertainties discussed in greater detail in Incyte’s reports filed with the U.S. Securities and Exchange Commission, including its annual report on Form 10-K and its quarterly report on Form 10-Q for the quarter ended March 31, 2026. Incyte disclaims any intent or obligation to update these forward-looking statements.

View source version on businesswire.com: https://www.businesswire.com/news/home/20260519992433/en/

Incyte Contacts:

Media
media@incyte.com

Investors
ir@incyte.com

Edison Scientific Contact:

Media
Simone Migliori
simone@sixeastern.com

Source: Incyte and Edison Scientific