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Generative AI-Driven Collaboration to Research Treatments for Brain Hemorrhage Complications

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Brain Injury, Blood in Injured Brains (stroke, brain hemorrhage, intracerebral hemorrhage, subarachnoid hemorrhage, arteriovenous malformation, brain aneurysm rupture, traumatic brain injury) | Image Credit: © Arugula Pica – stock.adobe.com

Proteros biostructures GmbH, an early-stage drug discovery services provider in Germany, has announced an agreement with Qanatpharma of Switzerland, Zuse Institute Berlin (ZIB), and Ukraine-based Enamine to launch a research collaboration intending to leverage innovations from all four partners—notably, ZIB’s artificial intelligence (AI)-based generative ligand design—to accelerate discovery of novel therapeutics targeting cerebral perfusion deficits associated with subarachnoid hemorrhage (SAH) (1).

The partners said in a press release on July 9, 2025 that they hope the collaboration will set a precedent for generative AI to be used in early-stage discovery to treat cerebrovascular conditions (1). The partnership’s initial focus will be on a protein target identified by Qanatpharma that helps regulate cerebrovascular resistance in the brain, a mechanism that has been shown to be compromised in patients with SAH, which is a severe form of stroke.

Risky unmet need for stroke survivors

Key Takeaways

  • Proteros, Qanatpharma, Zuse Institute Berlin, and Enamine have partnered to apply generative AI to early-stage drug discovery for treating cerebral perfusion issues in subarachnoid hemorrhage (SAH).
  • The collaboration targets delayed cerebral ischemia, a common and currently unaddressed complication of SAH, aiming to improve outcomes.
  • Compound screening is underway, with in-vitro validation expected later in 2025, reinforcing a broader industry trend of thoughtfully integrating generative AI tools.

A leading complication, and heretofore unmet need, for SAH survivors is delayed cerebral ischemia (DCI), which reduces cerebral perfusion and may result in long-term neurological damage, disability, or death (1). The current standard of care for SAH fails to target the molecular mechanism that prompts the occurrence of DCI.

“Delayed cerebral ischemia is a major contributor to poor outcomes following subarachnoid hemorrhage, and current treatment options remain limited,” Steffen-Sebastian Bolz, MD, PhD, chief medical and scientific officer at Qanatpharma, said in the release (1). “By building this consortium, we are bringing together the brightest machine learning engineers, chemists, structural biologists, and other scientists to tackle this critical complication. Together, we aim to accelerate the development of a targeted therapy that could significantly improve recovery and long-term outcomes for patients affected by SAH.”

The four partners said they have already begun compound screening efforts and plan to proceed to in-vitro validation studies as the second half of 2025 progresses (1).

Companies collaborating on AI innovation

Other partnerships involving, at least in part, the adoption of generative-AI approaches have been announced in 2025. In February, two United States companies, Delaware-based Incyte and California-based Genesis Therapeutics, agreed to a strategic collaboration making use of generative and predictive AI to help research, discover, and develop novel small-molecule medicines for various targets (2).

Some companies are working generative-AI technologies into their workflows even as they remain cautious about overuse or overexposure. In May 2025, St. Louis-based Emerson, building on its acquisition of Aspen Technology, announced a new AI-driven approach aimed at enhancing reliability and performance of mission-critical manufacturing operations, including those in the pharmaceutical sector (3). At the same time, however, the company warned that public generative-AI tools—up to this point, at least—remain unsuitable for industrial settings due to security and reliability concerns.

As part of Pharmaceutical Technology® Group’s “Industry Outlook” series for 2025, Preeya Beczek, managing director and co-founder of Beczek.COM Ltd, a specialist in regulatory affairs and compliance, said overall, generative AI is a top trend to watch as it relates to the ways in which companies in the industry operate (4).

“I think we’re just going to have lot more people adopting [generative AI and] that way of working, in their day-to-day work,” Beczek said in the interview (4). “I think that there’s going to be some push to get speed, [in] things like manufacturing timelines, [so] they become shorter.”

Click here to view the full interview.

References

1. Proteros biostructures GmbH. Qanatpharma, Zuse Institute Berlin, Enamine, and Proteros biostructures Announce Generative-AI Driven Lead Discovery Collaboration. Press Release. July 9, 2025.
2. Incyte. Incyte and Genesis Therapeutics Announce Strategic AI-Focused Research Collaboration. Press Release. Feb. 20, 2025.
3. Emerson. Emerson’s Expanded AI Portfolio Paves the Way for More Optimized Autonomous Operations. Press Release. May 22, 2025.
4. Thomas, F. Industry Outlook 2025: Personalizing Precision Medicine and Adopting AI. PharmTech.com, Feb. 20, 2025.



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EU Publishes Final AI Code of Practice to Guide AI Companies

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The European Commission said Thursday (July 10) that it published the final version of a voluntary framework designed to help artificial intelligence companies comply with the European Union’s AI Act.

The General-Purpose AI Code of Practice seeks to clarify legal obligations under the act for providers of general-purpose AI models such as ChatGPT, especially those posing systemic risks like ones that help fraudsters develop chemical and biological weapons.

The code’s publication “marks an important step in making the most advanced AI models available in Europe not only innovative but also safe and transparent,” Henna Virkkunen, executive vice president for tech sovereignty, security and democracy for the commission, which is the EU’s executive arm, said in a statement.

The code was developed by 13 independent experts after hearing from 1,000 stakeholders, which included AI developers, industry organizations, academics, civil society organizations and representatives of EU member states, according to a Thursday (July 10) press release. Observers from global public agencies also participated.

The EU AI Act, which was approved in 2024, is the first comprehensive legal framework governing AI. It aims to ensure that AI systems used in the EU are safe and transparent, as well as respectful of fundamental human rights.

The act classifies AI applications into risk categories — unacceptable, high, limited and minimal — and imposes obligations accordingly. Any AI company whose services are used by EU residents must comply with the act. Fines can go up to 7% of global annual revenue.

The code is voluntary, but AI model companies who sign on will benefit from lower administrative burdens and greater legal certainty, according to the commission. The next step is for the EU’s 27 member states and the commission to endorse it.

Read also: European Commission Says It Won’t Delay Implementation of AI Act

Inside the Code of Practice

The code is structured into three core chapters: Transparency; Copyright; and Safety and Security.

The Transparency chapter includes a model documentation form, described by the commission as “a user-friendly” tool to help companies demonstrate compliance with transparency requirements.

The Copyright chapter offers “practical solutions to meet the AI Act’s obligation to put in place a policy to comply with EU copyright law.”

The Safety and Security chapter, aimed at the most advanced systems with systemic risk, outlines “concrete state-of-the-art practices for managing systemic risks.”

The drafting process began with a plenary session in September 2024 and proceeded through multiple working group meetings, virtual drafting rounds and provider workshops.

The code takes effect Aug. 2, but the commission’s AI Office will enforce the rules on new AI models after one year and on existing models after two years.

A spokesperson for OpenAI told The Wall Street Journal that the company is reviewing the code to decide whether to sign it. A Google spokesperson said the company would also review the code.

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Researchers develop AI model to generate global realistic rainfall maps

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Working from low-resolution global precipitation data, the spateGAN-ERA5 AI model generates high-resolution fields for the analysis of heavy rainfall events. Credit: Christian Chwala, KIT

Severe weather events, such as heavy rainfall, are on the rise worldwide. Reliable assessments of these events can save lives and protect property. Researchers at the Karlsruhe Institute of Technology (KIT) have developed a new method that uses artificial intelligence (AI) to convert low-resolution global weather data into high-resolution precipitation maps. The method is fast, efficient, and independent of location. Their findings have been published in npj Climate and Atmospheric Science.

“Heavy rainfall and flooding are much more common in many regions of the world than they were just a few decades ago,” said Dr. Christian Chwala, an expert on hydrometeorology and machine learning at the Institute of Meteorology and Climate Research (IMK-IFU), KIT’s Campus Alpin in the German town of Garmisch-Partenkirchen. “But until now the data needed for reliable regional assessments of such extreme events was missing for many locations.”

His research team addresses this problem with a new AI that can generate precise global precipitation maps from low-resolution information. The result is a unique tool for the analysis and assessment of extreme weather, even for regions with poor data coverage, such as the Global South.

For their method, the researchers use from that describe global precipitation at hourly intervals with a spatial resolution of about 24 kilometers. Not only was their generative AI model (spateGEN-ERA5) trained with this data, it also learned (from high-resolution weather radar measurements made in Germany) how precipitation patterns and extreme events correlate at different scales, from coarse to fine.

“Our AI model doesn’t merely create a more sharply focused version of the input data, it generates multiple physically plausible, high-resolution maps,” said Luca Glawion of IMK-IFU, who developed the model while working on his doctoral thesis in the SCENIC research project. “Details at a resolution of 2 kilometers and 10 minutes become visible. The model also provides information about the statistical uncertainty of the results, which is especially relevant when modeling regionalized events.”

He also noted that validation with weather radar data from the United States and Australia showed that the method can be applied to entirely different climatic conditions.

Correctly assessing flood risks worldwide

With their method’s global applicability, the researchers offer new possibilities for better assessment of regional climate risks. “It’s the especially vulnerable regions that often lack the resources for detailed weather observations,” said Dr. Julius Polz of IMK-IFU, who was also involved in the model’s development.

“Our approach will enable us to make much more reliable assessments of where heavy rainfall and floods are likely to occur, even in such regions with poor data coverage.” Not only can the new AI method contribute to disaster control in emergencies, it can also help with the implementation of more effective long-term preventive measures such as flood control.

More information:
Luca Glawion et al, Global spatio-temporal ERA5 precipitation downscaling to km and sub-hourly scale using generative AI, npj Climate and Atmospheric Science (2025). DOI: 10.1038/s41612-025-01103-y

Citation:
Researchers develop AI model to generate global realistic rainfall maps (2025, July 10)
retrieved 10 July 2025
from https://phys.org/news/2025-07-ai-generate-global-realistic-rainfall.html

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Musk unveils Grok 4 AI update after chatbot posted antisemitic remarks

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Elon Musk’s artificial intelligence chatbot, Grok, received a major update.

Musk introduced Grok 4 during a livestream on X late Wednesday, calling it “the smartest AI in the world.” He praised the chatbot’s capabilities, saying it is smarter than “almost all graduate students in all disciplines, simultaneously.”

“Grok 4 is at the point where it essentially never gets math/physics exam questions wrong, unless they are skillfully adversarial,” Musk said. “It can identify errors or ambiguities in questions, then fix the error in the question or answer each variant of an ambiguous question.”

RELATED STORY | Musk’s AI company scrubs inappropriate posts after Grok chatbot makes antisemitic comments

Musk, who also owns Tesla, said in a separate social media post that Grok will be integrated into the electric vehicles as early as next week.

Grok 4’s release came just one day after the earlier model, Grok 3, shared several controversial posts, including some that praised Adolf Hitler.

In a statement, xAI, the company behind Grok, said it is actively working to remove hate speech from the platform and took swift action to update the model.

The controversial posts have since been deleted.

RELATED STORY | X CEO Linda Yaccarino leaves social media platform after 2 years





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