Toronto, Canada–January 2026
Pattern Agentix Inc, today announced its participation in a newly established AI Drug Development Consortium led by the University of West Attica. The consortium has been formed under the Horizon Europe framework to accelerate next-generation drug development through advanced artificial intelligence and computational modeling.

The collaboration brings together leading academic, clinical, and high-performance computing partners to create an integrated AI platform for compound prioritization, drug repurposing, and combination-therapy design.

The Horizon initiative aims to address one of the most pressing challenges in modern medicine: translating vast amounts of biomedical data into precise, explainable, and clinically actionable therapeutic insights. By combining UNIWA’s leadership in AI coordination and governance with Pattern Agentix’s expertise in compound modeling and knowledge-driven discovery, the consortium seeks to establish a new European benchmark for trustworthy AI in drug development.

Under the collaboration, Pattern Agentix will contribute:

• AI models for compound prioritization, repurposing, and combination design
• Algorithmic support for integrating mechanistic evidence into AI-driven decisions

The consortium’s work will focus initially on oncology and immune-inflammatory diseases, while maintaining a modular architecture that can be extended to additional therapeutic areas. Outputs from the initiative are expected to include open scientific resources, validated AI tools, and clinically relevant decision-support frameworks aligned with European regulatory and ethical standards.

Toronto, Canada — December 2025

Pattern Agentix today announced that the University of Gothenburg (UGOT) has joined its Horizon consortium through the adoption of the Agentix platform, enabling the university to participate directly in Horizon-aligned research activities.

By incorporating the Agentix platform, UGOT strengthens its ability to engage in large-scale European research initiatives that require integrated biomedical knowledge, explainable AI workflows, and clinically grounded data governance. The platform provides a unified environment for connecting molecular data, clinical evidence, and advanced computational models in support of Horizon objectives.

“The Horizon programme demands platforms that combine scientific depth with transparency, interoperability, and regulatory readiness,” said Pattern Agentix. “The University of Gothenburg’s adoption of the Agentix platform ensures it can contribute effectively to Horizon consortium activities while maintaining strong clinical and ethical foundations.”

UGOT will leverage the platform to support work in bioinformatics, preclinical validation, and clinical governance, collaborating closely with academic, SME, and infrastructure partners across Europe. The platform’s architecture is designed to meet Horizon expectations around reproducibility, open science, and responsible AI, while remaining practical for real-world clinical research environments.

UGOT’s participation strengthens the Horizon consortium by adding deep clinical and translational expertise, reinforcing a shared commitment to advancing trustworthy, scalable AI systems for European biomedical research.

About the University of Gothenburg

The University of Gothenburg is one of Sweden’s leading universities, with a strong international reputation in medicine, life sciences, and translational research. The university combines academic excellence with close integration into clinical practice, and is widely recognized for its work in bioinformatics, clinical governance, ethics, and adoption of digital health technologies across European research programmes.

Toronto Canada— October 2025 — Pattern Agentix is pleased to announce that Dr. Ravi Saini, a biochemical engineer and computational biologist from the Indian Institute of Technology (BHU), has joined its Scientific Advisory Board under the leadership of Dr. Erik Arabyan. Dr. Saini brings exceptional expertise in machine learning-based drug design, natural product inhibitor discovery, and biochemical process optimization.

Bridging Biology and AI

Dr. Saini’s research focuses on integrating biochemical engineering and computational modeling to design novel therapeutics. His doctoral work at IIT (BHU) explored the production and optimization of bioactive compounds from Streptomyces species, identifying potent antioxidant and anticancer agents through a combination of wet-lab analysis and molecular simulation. He is the inventor on a recently filed patent for the microbial production of bioactive compounds, and has authored more than 15 peer-reviewed publications in high-impact journals including Scientific Reports, Molecular Diversity, and Journal of Biomolecular Structure and Dynamics.

Leadership in Next-Generation Drug Design

At Pattern Agentix, Dr. Saini will advise on AI model validation for structure-based drug discovery and compound screening. His expertise in QSAR, molecular dynamics, and free-energy calculation will support the company’s efforts to integrate biochemical data with machine learning frameworks for precision drug targeting. He will also contribute to the development of AI-assisted pathway analysis tools for bioactive compound design.

“Ravi’s depth of biochemical insight and his cutting-edge work at the intersection of biology and computation will enhance our platform’s ability to uncover new therapeutic opportunities,” said Dr. Erik Arabyan, Chair of the SAB. “He represents the new generation of computational scientists bridging the gap between bench science and AI.”

A Global Scientific Perspective

Dr. Saini has received prestigious SERB, ICMR, and EMBO international travel grants for presenting his research in the United States, Italy, and Germany. He is also a reviewer for leading journals such as Scientific Reports and iScience and serves on the Board of Studies at the Noida Institute of Engineering and Technology. He holds a Ph.D. and M.Tech in Biochemical Engineering from IIT (BHU) Varanasi and a B.Tech in Biotechnology from Dr. A.P.J. Abdul Kalam Technical University.

Toronto, Canada — October 2025 — Pattern Agentix, a pioneer in AI-driven research and scientific data transformation, is pleased to announce the appointment of Dr. Aziz Abu-Saleh to its Scientific Advisory Board (SAB). A computational chemist and data scientist with extensive experience in computer-aided drug design, molecular modeling, and machine learning, Dr. Abu-Saleh will strengthen the company’s growing focus on AI-enabled compound discovery and predictive modeling. He joins under the leadership of Dr. Erik Arabyan, Chair of the SAB.

Advancing Computational Discovery

Dr. Abu-Saleh brings more than eight years of expertise spanning academia and translational research. As a Computational Chemist at the Structural Genomics Consortium (University of Toronto), he leads development of the Pan-Canadian Chemical Library, a collection exceeding 100 billion compounds designed to target disease-related proteins and RNA structures. His recent work involves building machine learning models for drug candidate prediction and integrating AI workflows into industrialized drug discovery pipelines.

Dr. Abu-Saleh’s career reflects a unique blend of computational chemistry and data science innovation. His research at the University of Windsor and Memorial University has produced multiple validated drug inhibitors and U.S. patents, advancing the frontiers of structure-based drug design and AI-augmented screening.

A Strategic Role in AI-Enabled Science

Through his position on the Scientific Advisory Board, Dr. Abu-Saleh will advise on Pattern Agentix’s computational strategy for large-scale data analysis, molecular simulation, and multi-modal model integration. His leadership will support the company’s efforts to accelerate drug discovery through standardized benchmarks, automated hit identification, and predictive analytics.

“Aziz’s blend of computational rigor and machine learning acumen aligns perfectly with our mission to translate data into discovery,” said Dr. Erik Arabyan, Chair of the SAB. “His vision for scalable, AI-powered drug design will help Pattern Agentix extend its lead in the next generation of computational biology.”

Commitment to Scientific Excellence

Dr. Abu-Saleh has been recognized with numerous awards and fellowships, including the CAS Future Leaders Award by the American Chemical Society, and research grants from the Digital Research Alliance of Canada and Mitacs Canada. He holds a Ph.D. in Computational Chemistry from Memorial University of Newfoundland.

Ontario, Canada, May 22, 2025 — Pattern Agentix, a leader in AI-powered biomedical research, is pleased to announce the successful completion of its new Canadian corporate structure. This transition was undertaken to accommodate new opportunities and support the company’s long-term strategy for expansion and innovation.

The new Canadian corporate structure strengthens Pattern Agentix’s ability to finance in its generative AI technologies, pursue strategic partnerships, and expand its footprint across key research markets. It also enhances the company’s governance framework and sets the stage for deeper collaboration with industry, academia, and government entities.

Pattern Agentix Establishes U.S. Corporation

Ontario, Canada, November 20, 2024 — Pattern Agentix, a leader in AI-powered biomedical research, is pleased to announce the formation of its United States corporation. This strategic move signals the company’s commitment to expanding its presence in one of the world’s most dynamic innovation ecosystems, and to accelerating collaboration with leading U.S. research institutions, pharmaceutical firms, and government agencies.

Strengthening Global Operations and Scientific Impact

The new U.S. corporation will serve as a key operational hub for Pattern Agentix’s generative AI platform and scientific development efforts. It will support ongoing initiatives in drug discovery, personalized medicine, and multi-omics data integration—while positioning the company to engage more deeply in federally funded research and regional commercialization opportunities.

“The United States remains a global epicenter of life science innovation,” said the company’s CEO. “By establishing a formal presence, Pattern Agentix is deepening its commitment to scientific partnership, talent development, and regulatory collaboration in one of our most important markets.”

A Platform for Innovation at Scale

The U.S. company will initially focus on advancing deployment of the company’s Research. The resulting technologies will underpin Pattern Agentix’s vision of a transparent, explainable AI infrastructure that enables disease-aligned drug development.

Pattern Agentix is building the next‑generation bioscience platform. By unifying enriched datasets, advanced tools, and customizable workflows, it enables teams to generate deeper insights and accelerate discovery.

Pattern Agentix Appoints Dr. Erik Arabyan to Lead Scientific Advisory Board

Ontario, Canada, May 13, 2025 — Pattern Agentix, a pioneer in AI-driven research and scientific data transformation, is pleased to announce the appointment of Dr. Erik Arabyan as Chair of its Scientific Advisory Board. An expert in drug discovery and translational science, Dr. Arabyan brings a unique blend of academic insight and industry experience to guide the company’s scientific strategy across biomedical and interdisciplinary domains.

Advancing Scientific Leadership

Dr. Erik Arabyan is a leading voice in the fields of virology, oncology, and metabolic disease research. With extensive experience collaborating with pharmaceutical companies, he has contributed to the identification of novel drug targets and the acceleration of therapeutic development pipelines.

Dr. Arabyan’s expertise spans drug discovery consulting, biomarker annotation, biological database curation, scientific communication, and medical writing. His work bridges the gap between data and actionable insight—key to Pattern Agentix’s mission to enhance scientific workflows with advanced AI.

A Strategic Role in Research Innovation

As Chair of the Scientific Advisory Board, Dr. Arabyan will provide strategic guidance on scientific direction, data modeling, and domain-specific applications for AI-driven research. His interdisciplinary approach will support Pattern Agentix’s platform evolution, particularly in life sciences and healthcare.

“Dr. Arabyan’s leadership in drug discovery and deep understanding of biological data challenges make him an invaluable addition to our team,” said the CEO of Pattern Agentix. “His insights will help ensure that our platform delivers meaningful impact across research and clinical settings.”

A Commitment to Precision and Progress

Dr. Arabyan holds a strong academic foundation in biochemistry and molecular biology. Through his advisory role, he will help Pattern Agentix refine its tools for biomarker analysis, scientific data structuring, and domain-specific LLM integration—further accelerating discovery in precision medicine and related fields.

Pattern Agentix Appoints Veteran Tech Executive Daniel Assouline to Board of Directors

Ontario, Canada, February 25, 2025 — Pattern Agentix, a leader in AI-powered scientific research and data transformation, is pleased to announce the appointment of Daniel Assouline to its Board of Directors. With a proven track record in scaling digital platforms and leading innovative software companies, Mr. Assouline brings a wealth of strategic expertise to support Pattern Agentix’s continued growth and vision.

Strengthening Strategic Leadership

Daniel Assouline co-founded the e-commerce platform UpClick in 2006 and served as its CEO, helping to drive global expansion and digital innovation. He later held CEO roles at cybersecurity and software firms adaware and Avanquest, where he focused on product modernization, user growth, and operational scale.

With a Bachelor of Engineering from Polytechnique Montréal and an MBA from Queen’s University, Mr. Assouline combines technical acumen with strategic insight—skills that align closely with Pattern Agentix’s mission to integrate AI into complex scientific domains.

A Shared Vision for Innovation

“Daniel’s entrepreneurial background and deep experience in software leadership will be instrumental as we scale Pattern Agentix’s platform and deepen our impact across genomics, material science, and interdisciplinary research,” said the company’s CEO. “We’re thrilled to welcome him to the board.”

Guiding the Future of AI-Driven Science

As Pattern Agentix expands its patent portfolio and research platform, the appointment of Mr. Assouline signals a commitment to strong governance and forward-thinking leadership. His experience navigating both startup environments and global markets will help guide the company’s next phase of growth.

Pattern Agentix Files Three Patents to Transform Data Processing in Genomics, Material Science, and Scientific Research

Ontario Canada, December 30, 2024, a pioneer in leveraging artificial intelligence (AI) for scientific advancement, is proud to announce the filing of three process patents. These patents establish innovative methods for structuring complex datasets, enabling advanced analysis by Large Language Models (LLMs) across diverse fields including genomics, material science, and interdisciplinary research.

The Patents Filed Include:

1. Method and System for Formatting Genomic Data for Analysis by Large Language Models
   This patent introduces a methodology to preprocess genomic data—such as DNA sequences and gene expression profiles—into structured formats optimized for LLMs. By bridging the gap between raw genomic data and AI-driven analysis, this innovation empowers researchers to accelerate discoveries in genomics and personalized medicine.
2. Method and System for Formatting Material Science Data Sets for Analysis by Large Language Models
   Addressing the complexity of material science datasets, this patent outlines a method to preprocess and annotate data, such as crystallographic structures and material properties. By enabling LLMs to analyze and predict material behaviors, the invention supports advancements in material discovery and industrial applications.
3. Method and System for Formatting Scientific Data Sets for Analysis by Large Language Models
   This broad patent covers the preprocessing and structuring of scientific datasets across various domains, including biology, chemistry, and physics. The approach simplifies data interpretation and enhances the ability of LLMs to generate actionable insights, paving the way for interdisciplinary research breakthroughs.

A Vision for Transformative AI Integration

Pattern Agentix is committed to advancing the role of AI in science and industry. These patent filings underscore the company’s dedication to solving complex data challenges, making scientific exploration more efficient and accessible.

Implications for Industry and Research

The filed patents position PA as a leader in applying LLMs to domains traditionally limited by complex and voluminous datasets. By enabling AI to process and interpret these datasets, the company anticipates driving advancements in areas such as:

• Genomics: Accelerating discoveries in genetics and healthcare.
• Material Science: Facilitating the development of next-generation materials for aerospace, electronics, and energy.
• Interdisciplinary Research: Promoting collaboration across scientific disciplines.