AI and Biology Unite to Forge Next-Gen Pill for Heart Disease

REHOVOT, Israel and DAEJEON, South Korea – July 22, 2026 – In a move that underscores the shifting paradigms of pharmaceutical development, Israeli computational chemistry firm Evogene Ltd. and South Korean biotech ELEO Inc. have announced a strategic collaboration. Their goal is to develop a next-generation oral therapy for high cholesterol, targeting the lucrative but challenging PCSK9 pathway. While the press release signals a bold step into a market projected to hit $23 billion by 2035, the partnership's true significance lies in the fusion of two powerful, and very different, discovery engines: generative artificial intelligence and natural product science.

This collaboration isn't happening in a vacuum. It arrives just days after the U.S. FDA approved Merck's LIPFENDRA®, the first-ever oral PCSK9 inhibitor. That landmark approval validates the scientific and commercial viability of a pill-based alternative to the costly, injectable treatments that have dominated the market, setting a new, fiercely competitive baseline for all who follow.

The Race for an Oral Solution

Cardiovascular disease remains the world's leading killer, and elevated LDL cholesterol is a primary culprit. For years, the most potent weapons against it, beyond statins, have been injectable PCSK9 inhibitors like Amgen's Repatha and Regeneron's Praluent. These therapies work spectacularly well, but their high cost, inconvenient delivery method, and restrictive access have left a significant gap in patient care. The industry has been in a race to fill that gap with a simple, daily pill.

Merck's recent victory with LIPFENDRA® proves it can be done, transforming the competitive landscape overnight. By pricing its drug at roughly half the list price of its injectable rivals, Merck has not only established a new standard of care but also a new commercial reality. The challenge for newcomers like the Evogene-ELEO partnership is no longer just to create an oral PCSK9 inhibitor, but to create a better one—with superior potency, safety, or a differentiated mechanism that can carve out a niche in an increasingly crowded field. With a market poised to grow at a compound annual growth rate of over 18%, the financial incentives for getting it right are immense.

AI Meets Natural Biology: A New Discovery Engine

The strategic logic of this collaboration hinges on a powerful synergy. Evogene brings its proprietary ChemPass AI™ platform, a generative AI engine designed to navigate a chemical universe of 38 billion molecular structures. Unlike conventional methods that screen existing compounds, ChemPass AI™ is built to design novel molecules from the ground up. Its key differentiator is its ability to perform multi-parameter optimization, simultaneously solving for potency, selectivity, bioavailability, and synthesizability—the very factors that determine whether a promising compound can become a viable drug.

Evogene has been actively honing this tool. An expanded partnership with Google Cloud, finalized in June, integrated advanced AI agents into the platform to accelerate the entire design-make-test-analyze cycle. The company claims this system achieves 90% precision in its generative models, a significant leap over traditional approaches. This computational horsepower is precisely what’s needed to tackle a notoriously difficult target like PCSK9, where disrupting the protein-protein interaction with a small molecule has been a long-standing challenge for medicinal chemists.

Complementing this digital prowess is ELEO Inc., a biotech firm rooted in the tangible world of natural product science. ELEO's CEO, Dr. Kyungseop Ahn, revealed that his team's work has already led to the identification of a "PCSK9 inhibitor candidate with a novel mechanism." This biological insight, derived from the rich pharmacopeia of nature, provides a critical starting point. ELEO will contribute its proprietary biological models and screening platforms to experimentally validate and refine the molecules designed by Evogene's AI. This integrated feedback loop—where AI designs and biology validates—is intended to dramatically accelerate the discovery process and increase the probability of success.

The Hidden Costs and High Stakes of AI Drug Discovery

While the promise is vast, the path forward is fraught with the hidden costs of 21st-century progress. The narrative of AI as a panacea for drug discovery often overlooks the immense challenges of translating digital predictions into biological reality. The effectiveness of any AI model is contingent on the quality of its training data, and the gap between an in silico prediction and a successful in vivo result remains a significant hurdle.

Furthermore, the "black box" nature of some AI systems can obscure the scientific reasoning behind a chosen candidate, complicating optimization and regulatory discussions. The Evogene-ELEO partnership represents a high-risk, high-reward venture into this new frontier. The financial terms of the deal remain undisclosed, a common practice for early-stage discovery alliances, but the capital required to advance a candidate through preclinical and clinical trials is monumental. Success will depend not only on the sophistication of the technology but on rigorous experimental validation and a deep, unwavering understanding of the underlying biology.

As stated by Ofer Haviv, CEO of Evogene, the goal is to "advance differentiated, next-generation therapeutic candidates with significant potential value for future strategic partners." This highlights the ultimate strategy: to develop a highly valuable asset that can be licensed or co-developed with a global pharmaceutical giant equipped to handle late-stage trials and commercialization. In the high-stakes pursuit of a pill to mend the heart, this fusion of artificial intelligence and natural biology represents one of the most compelling bets in modern medicine.