MolecuLern Partners with Halia Therapeutics on Chronic Inflammation

FOR IMMEDIATE RELEASE

April 15, 2024

American Fork, UT – MolecuLern, a leading AI-driven drug discovery platform, proudly announces a groundbreaking partnership with Halia Therapeutics aimed at advancing treatment options for patients with diseases rooted in chronic inflammation. This collaboration harnesses MolecuLern’s cutting-edge artificial intelligence capabilities alongside Halia Therapeutics’ innovative drug development expertise to identify and develop novel compounds based on Halia’s existing therapies.

Chronic inflammation represents a significant health challenge worldwide, impacting millions of individuals across various diseases. Through this strategic alliance, MolecuLern and Halia Therapeutics seek to accelerate the discovery and development of transformative therapies. “MolecuLern is thrilled to collaborate with Halia Therapeutics in our shared mission to leverage AI-driven insights for the development of next-generation treatments,” said Hariprasad Vankayalapati, M.Pharm, PhD, Chief Scientific Officer of MolecuLern. “This partnership represents a significant step forward in our commitment to advancing therapies and addressing unmet medical needs.”

Halia Therapeutics brings to the partnership its proprietary drug candidates and deep understanding of the biological mechanisms underlying chronic inflammation. By integrating MolecuLern’s state-of-the-art AI platform, which specializes in predictive modeling, the collaboration aims to expedite the identification of novel compounds that enhance therapeutic efficacy and patient outcomes.

“We are excited to partner with MolecuLern to harness the power of AI in accelerating the discovery of new therapies for chronic inflammation,” said Jared Bearss, COO of Halia Therapeutics. “This collaboration underscores our dedication to advancing innovative treatments that can make a meaningful difference in patients’ lives.”

The combined expertise of MolecuLern and Halia Therapeutics creates a robust synergy poised to drive significant advancements in drug development. By leveraging AI-driven insights and biological expertise, the partners aspire to deliver transformative medicines that address critical unmet needs in healthcare.

About Halia Therapeutics, Inc.

Halia Therapeutics is discovering and developing a pipeline of novel therapeutics to improve patients’ lives with chronic inflammatory disorders and neurodegenerative diseases, with its initial programs targeting NEK7 and LRRK2. Halia’s lead candidate, HT-6184, a novel NEK7/NLRP3 inhibitor, has completed a Phase I study (NCT05447546) evaluating the safety and tolerability of HT-6184 when administered as single or multiple oral doses at escalating dose levels in healthy volunteer subjects. Halia has also initiated 2 Phase II trials to evaluate the efficacy of HT-6184 for the treatment of lower-risk myelodysplastic syndromes (LR-MDS) and on post-procedure diagnostic biomarkers of inflammation and pain (NCT06241742).

About MolecuLern

MolecuLern is a leading AI-driven drug discovery engine dedicated to transforming healthcare by accelerating the discovery of novel therapeutics. Powered by advanced artificial intelligence and machine learning algorithms, MolecuLern is at the forefront of innovation in pharmaceutical research and development. MolecuLern partners with companies both to discover novel drugs as well as rapidly refine and develop existing drug candidates.  

Media Contact: Kyle Medley
Director of Business Development
MolecuLern
Email: kmedley@moleculern.com
Phone: +1.435.893.5473

When Real Data Meets Proven Experience: A Personal Commitment

Co-founder and Board Chair David J. Bearss, Ph.D., has over 20 years of experience in small-molecule drug development, cell biology, and translational research focused on genetic markers and modeling systems to predict drug sensitivity. David’s passion for drug discovery and development stems from the loss of his grandfather and mother to colon cancer, and to this day, it still motivates him to create new medicines. David is joined by co-founder and CSO Hari Vankayalapati, M.Pharm, Ph.D., a trained medicinal and organic chemist and the author of over 70 publications. Together, the team at MolecuLern boasts over 100 patents, filed over a dozen INDs, has been involved in hundreds of clinical trials, and has achieved significant exits from previous companies.

The product of over two decades of work, Moleculern combines a deep understanding of biology and chemistry with the power of modern technology. This includes cutting-edge computational tools and machine learning AI, which are revolutionizing the drug discovery process. MolecuLern leverages these tools to streamline the traditional trial-and-error methods that have dominated the field for centuries. Drs. Bearrs and Vankayalapati are pioneers in this field, having been among the first to utilize computational techniques for drug discovery.

Advantages include: 

  • AI Learning from Experience: MolecuLern trains its machine-learning models with decades of drug development knowledge, including successes and failures. This allows the AI to identify patterns and solve complex pharmacological problems.
  • Massive Chemical Library: MolecuLern has a vast library of over five billion potential drug designs, including diverse options like small molecules and peptides.
  • MolecuLern tackles complex challenges in drug development. This proprietary machine-learning algorithm and extensive compound library accelerate the process by solving pharmacological problems traditionally handled through lengthy research.
  • MolecuLern cuts years off development timelines.  Two examples of faster delivery include drugs targeting obesity and metabolic syndrome, developed in 2023 and are expected to enter clinical trials by early 2025.
  • Empowering companies with a robust preclinical pipeline with real-world applications. Companies other potential drugs will soon be ready for out-licensing or partnerships, indicating a strong future pipeline. Several promising partnerships are currently under discussion.