image: Dr. Itay Koren, Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University
Credit: Courtesy Bar-Ilan University
Two cutting-edge research projects at Bar-Ilan University have been awarded Proof of Concept (PoC) Grants from the European Research Council (ERC)—a major achievement that highlights the university’s interdisciplinary leadership in both biomedical science and AI-driven public policy.
The prestigious PoC grants have been awarded to:
- Dr. Itay Koren (Goodman Faculty of Life Sciences) for Next-Gen Targeted Protein Degradation, a project aiming to revolutionize how cancer and other diseases are treated at the molecular level.
- Prof. Yuval Feldman (Faculty of Law), working with Prof. Yoav Goldberg (Department of Computer Science), for BEHAVREG, a project using artificial intelligence to study and enhance the effectiveness of government regulations.
These grants build on prior ERC-funded research by both teams and support the translation of breakthrough academic insights into practical applications.
Reshaping Disease Treatment Through Direct Protein Degradation
Dr. Itay Koren’s project seeks to overcome a major hurdle in targeted protein degradation (TPD)—a promising therapeutic strategy that instructs the body to eliminate disease-causing proteins. Traditional TPD approaches rely on PROTACs, which guide harmful proteins to destruction via a cellular tagging system involving E3 ligases.
However, the limited availability and specificity of E3 ligases restrict the effectiveness of current therapies. Dr. Koren’s lab discovered an alternative pathway: short peptide "tags" that send proteins directly to the proteasome (the part of the cell that degrades proteins), bypassing the need for E3 ligase tagging altogether.
With ERC PoC support, the Next-Gen Targeted Protein Degradation project will further develop this approach, with the goal of targeting difficult-to-treat proteins—such as the androgen receptor and BRD family proteins—which are involved in cancers like prostate and breast cancer.
“This technology could dramatically expand the universe of druggable targets,” said Dr. Koren. “We’re aiming to pioneer a new class of therapeutics that can improve precision medicine outcomes.”
Dr. Koren is a molecular biologist and recipient of a previous ERC Starting Grant for research on protein degradation mechanisms.
BEHAVREG – Using AI to Decode What Makes Regulation Work
In a completely different domain, the BEHAVREG project, led by Prof. Yuval Feldman and advised by AI expert Prof. Yoav Goldberg, seeks to bring clarity to a longstanding policy challenge: What makes government regulations effective?
Despite the vast amounts of money spent on regulation, there is surprisingly little systematic analysis of which design features actually drive citizen compliance. BEHAVREG addresses this gap by using machine learning and natural language processing to analyze regulatory texts, enforcement strategies, and behavioral outcomes.
"We're applying computational methods to understand patterns in regulatory success and failure," said Prof. Feldman, who leads the ERC-funded Voluntary Compliance Lab at Bar-Ilan University. "This could help policymakers design more effective interventions based on empirical evidence rather than intuition alone."
Prof. Goldberg explained the technical approach: "We will use machine learning and artificial intelligence-based system to analyze regulatory texts, implementation strategies, and outcome data, and to identify which design features correlate with behavioral change."
The team is working with a wide range of regulatory databases and is exploring partnerships with international bodies to enhance the project’s global relevance.
Prof. Feldman holds the Mori Lazarof Chair in Legal Research and is a Professor of Psychology (by courtesy) at Bar-Ilan University. He is currently the recipient of an ERC Advanced Grant for his work on voluntary compliance and behavioral aspects of regulation. Prof. Goldberg is an internationally recognized expert in natural language processing (NLP) and AI, with a focus on the application of machine learning to complex textual data.
From the Lab to the Real World
Both projects exemplify the goals of the ERC Proof of Concept program, which supports the early stages of turning high-risk, high-reward academic research into real-world applications. They also reflect Bar-Ilan University's commitment to impact-driven research that translates scientific innovation into applicable solutions addressing societal and technological challenges.
- Next-Gen Targeted Protein Degradation could revolutionize treatment options for patients with currently untreatable or drug-resistant diseases.
- BEHAVREG may become a critical predictive tool for governments seeking to craft smarter, more effective regulations across domains such as public health, safety, and environmental protection.