- Company launches initiative to become a dedicated AI infrastructure partner for the biotechnology industry — to deploy secure, on-premises AI systems directly within client environments where proprietary data never leaves the client’s control
- Platform-as-a-service model designed to generate recurring revenue by licensing AI capabilities to biotech and pharmaceutical companies of all sizes — addressing a market where the top 20 pharma companies invested approximately $167 billion in R&D in 2024 but have only recently begun to deploy meaningful AI budgets
- KALA to serve as its own first deployment client, applying Researgency to its proprietary MSC-S biological datasets and KPI-012 clinical program before scaling to external biotech partners
- Exclusive worldwide license secured for the Researgency platform in the biotechnology field for an initial 12-month term with successive renewal options; platform architecture designed from inception for multi-client deployment
- On-premises, data-sovereign architecture will differentiate Researgency from centralized AI platforms — will enable biotechs to leverage institutional-grade AI without surrendering control of their most valuable intellectual property
ARLINGTON, Mass., March 04, 2026 (GLOBE NEWSWIRE) — KALA BIO, Inc. (NASDAQ: KALA) (“KALA” or the “Company”), a clinical-stage biopharmaceutical company, today announced a strategic initiative to build a biotechnology industry dedicated, on-premises artificial intelligence (“AI”) infrastructure platform, designed to be deployed directly within biotech and pharmaceutical client environments, enabling companies across the life sciences sector to unlock additional potential of their proprietary biological data without ever surrendering control of it.
The Company also announced that it has entered into a Platform Development and Exclusive License Agreement (the “Agreement”) with 2624465 Ontario Inc., operating as Younet AI (“Younet”), for a proprietary AI research platform, internally designated “Researgency,” designed to deploy custom, secure, large language models (“LLMs”) purpose-built for biomedical research and data science applications. The Agreement provides KALA with initial platform access during a 12-month initial term and the option, in KALA’s sole discretion, to extend the Agreement for successive 12-month renewal terms.
The Vision: AI Infrastructure for the Entire Biotech Industry
The biotechnology industry faces a fundamental structural problem: thousands of small and mid-cap biotech companies are generating enormous volumes of proprietary biological data, from preclinical studies, clinical trials, genomic sequencing, protein interaction mapping, and secretome analysis, but the vast majority of these companies lack the internal resources, infrastructure, or specialized talent to deploy advanced AI capabilities against that data. At the same time, these companies are rightly unwilling to surrender their most sensitive intellectual property, the biological data, trade secrets, and clinical datasets that represent years of investment and form the core of their competitive advantage, to centralized, third-party cloud platforms.
KALA intends to solve this problem. The Company’s vision is to serve as a dedicated AI infrastructure partner for the biotechnology industry, deploying the Researgency platform directly within each client’s own secure environment, on their own servers, under their own control. In this model, KALA would provide the AI platform, the purpose-built biomedical agents, and the ongoing optimization, while the client would retain full ownership and custody of their data at all times. No proprietary information would ever leave the client’s infrastructure. No biological data would be shared with public AI services.
The Company believes this on-premises, data-sovereign approach represents a fundamentally different model from the centralized AI platforms currently operating in the life sciences space. While established AI drug discovery companies, including well-funded, publicly traded platforms with billion-dollar market capitalizations, typically require clients to upload proprietary data to centralized cloud environments, KALA’s architecture is designed from inception to go to the client, not the other way around. The Company believes this distinction is critical in an industry where intellectual property, trade secrets, and regulatory-sensitive data represent the most valuable assets a company possesses. Younet’s current go to market strategy is focused on morphing and tech augmenting existing operating companies into Agentic Companies where a large bulk of repeat and time consuming tasks and research are passed on to teams of proprietary agents. KALA intends to build on top of this approach and implement Agentic Company strategy in biomedical field.
“We are not building another centralized AI platform that asks biotechs to hand over their crown jewels,” said Avi Minkowitz, Chief Executive Officer of KALA BIO. “We are building the opposite. We want to be the company that shows up at the biotech company’s door, deploys institutional-grade AI on the biotech company’s servers, makes the biotech company’s data smarter, and never takes it from the biotech company. Hundreds of biotech companies are sitting on proprietary biological data that could yield breakthrough insights, but they cannot build this infrastructure themselves, and they should not have to trust a third party with their most sensitive assets. That is the gap we are filling. We intend to be an AI backbone of the biotech industry.”
The Market Opportunity: A $167+ Billion R&D Ecosystem Underserved by AI
The global AI drug discovery market is projected to grow at a compound annual growth rate approximately 25%,1 driven by AI’s demonstrated ability to compress traditional drug development timelines, which historically average 10 to 15 years and cost up to $2.6 billion per approved drug,2 to potentially as little as 12 to 18 months for preclinical candidate nomination, while reducing costs by an estimated 30 to 40 percent.3 Dozens of AI-designed drug candidates are currently in clinical trials globally, up from only three in 2016,4 with the first AI-discovered drug approvals anticipated in the near term.
The world’s twenty largest pharmaceutical companies collectively invested approximately $167 billion in research and development in 2024,5 yet the pharmaceutical industry’s combined investment in AI-driven drug discovery was estimated at approximately $4 billion in 2025, expected to grow to approximately $25 billion by 2030.6 The Company believes this represents one of the largest technology adoption gaps in any major industry.
More importantly, the Company believes the addressable market for on-premises, secure, purpose-built AI infrastructure, specifically designed for small and mid-cap biotech companies that cannot afford to build in-house AI capabilities and are unwilling to send proprietary data to centralized platforms, is substantially underserved. There are over 3,200 biotechnology companies in the United States alone,7 the majority of which are generating biological data that could benefit from AI-driven analysis but lack a viable, secure path to deploying it. KALA believes this segment represents a significant near-term revenue opportunity for a platform specifically architected to serve their needs.
What Is Researgency and How Does It Work?
Researgency is a proprietary biomedical AI research platform licensed to KALA by Younet AI, a specialized artificial intelligence development firm with experience deploying over 100 custom AI agents for enterprise clients across healthcare, technology, and life sciences sectors.
The platform is expected to be capable of deploying fully on-premises, secure AI systems that operate independently of any public AI service. In practical terms, Researgency works as follows: instead of relying on large teams of researchers to manually review thousands of scientific papers, clinical datasets, and biological records, a biotech company deploys purpose-built AI “agents”, specialized digital assistants trained exclusively on biomedical and pharmaceutical data, that can perform these tasks faster, more comprehensively, and at a fraction of the cost. Each agent is designed for a specific research function, such as analyzing protein interactions, reviewing drug safety literature, identifying new therapeutic targets, or modeling clinical trial outcomes. Intended narrow specialty of the agents shall significantly reduce hallucinations and save time on error corrections.
The platform’s core architecture includes advanced retrieval-augmented generation (“RAG”) pipelines, scalable AI infrastructure, and proprietary training algorithms that have been validated through a completed feasibility study confirming adaptability to the complex analytical demands of biomedical research, drug discovery, and clinical data science.
Key technical differentiators include:
- On-Premises Deployment: The entire AI system operates within the client’s own secure infrastructure. No data is transmitted to external servers, public clouds, or third-party AI services.
- Custom Agent Architecture: Purpose-built AI agents are configured specifically for each client’s therapeutic focus areas, data types, and research objectives, not generic, one-size-fits-all models.
- Full Data Sovereignty: Proprietary biological data, trade secrets, and intellectual property remain entirely under the client’s control at all times, meeting the highest standards of regulatory compliance and IP protection.
- Scalable Infrastructure: Platform architecture is designed from inception for multi-client deployment, enabling KALA to onboard additional biotech clients without rebuilding core systems.
The Platform Revenue Model: From Internal Tool to Industry Infrastructure
KALA intends to deploy the Researgency platform in a phased approach designed to validate performance, demonstrate value, and scale across the biotechnology industry:
Phase 1 — Internal Validation (Current): KALA serves as its own first deployment client, applying Researgency’s AI capabilities to the Company’s proprietary MSC-S platform datasets, KPI-012 preclinical and clinical data, and existing intellectual property portfolio. The Company expects to complete its initial AI-driven reassessment of historical datasets and report preliminary findings during the 12-month initial term.
Phase 2 — External Deployment: Following successful internal validation, KALA intends to begin licensing the Researgency platform to external biotech and pharmaceutical clients on a recurring subscription basis. Each deployment would be customized for the client’s specific therapeutic focus, data environment, and research objectives, with the platform installed directly on the client’s own infrastructure.
Phase 3 — Platform Expansion: As the client base grows, KALA intends to expand Researgency’s capabilities to include advanced predictive modeling for drug discovery workflows, AI-powered hypothesis generation and experimental design, secure regulatory-compliant data management, and collaborative research tools for academic institutions, CROs, and pharmaceutical partners.
This phased approach is designed to transform KALA from a single-pipeline clinical-stage biopharmaceutical company into a platform company with recurring, scalable revenue derived from licensing AI infrastructure to the broader biotechnology industry, while simultaneously enhancing the value of KALA’s own therapeutic programs.
Competitive Positioning: Why On-Premises Matters
The Company believes the current AI drug discovery landscape is dominated by centralized platform models that require biotech companies to upload proprietary data to third-party cloud environments. While these platforms have demonstrated the power of AI in drug discovery, they present significant barriers for the thousands of biotech companies whose proprietary biological data, trade secrets, and regulatory-sensitive information represent their most valuable assets.
KALA’s on-premises, data-sovereign model is designed to address this gap directly. The Company believes the competitive moat of the Researgency platform is built on several key advantages:
- Exclusive License: KALA holds exclusive worldwide rights to the Researgency platform within the biotechnology field.
- Data Never Leaves the Client: Unlike centralized models, the Researgency platform deploys within the client’s own environment. This eliminates a large barrier to AI adoption among data-sensitive biotech companies.
- Deep Customization: Each deployment features purpose-built AI agents tailored to the client’s specific datasets and therapeutic areas, creating high switching costs and long-term client retention.
- Platform Network Effects: As KALA deploys across multiple clients, the Company’s understanding of biomedical AI agent design, RAG pipeline optimization, and deployment best practices should increase — creating an operational expertise moat that is expected to grow with each new deployment.
How KALA Intends to Use Researgency Internally
As its own first deployment client, KALA intends to apply AI-driven analytical tools through the Researgency platform to:
- Reassess historical preclinical and clinical datasets — including the substantial biological data generated by the Company’s MSC-S platform across growth factors, protease inhibitors, matrix proteins, and neurotrophic factors
- Identify additional therapeutic indications or development pathways — by using AI to detect patterns in complex, multi-factorial biological data that conventional research methods may have overlooked
- Optimize trial design and probability-of-success modeling — reducing the time and cost associated with future clinical programs
- Support regulatory and commercialization strategy evaluation — including analysis of the Company’s existing FDA Orphan Drug and Fast Track designations for its KPI-012 product candidate
- Automate literature review and competitive intelligence — enabling the Company to continuously monitor developments across the rapidly evolving AI-biology landscape
The Company expects to report preliminary findings from its internal AI-driven data reassessment during the 12-month initial term, providing investors with tangible evidence of the platform’s capabilities prior to external deployment.
License Agreement and Terms
Under the Agreement, KALA has secured exclusive worldwide license rights to the Researgency platform within the biotechnology field (as defined in the Agreement) and has received initial platform access to evaluate and demonstrate its capabilities. The exclusivity applies to the custom, dedicated platform configured for KALA and does not restrict Younet from operating its standard, generally available, multi-tenant SaaS platform. The Company intends to assess the platform’s performance during the 12-month initial term and, subject to satisfactory results, may elect to extend the Agreement for successive 12-month renewal terms, which would include expanded deployment of custom biotechnology-focused AI agents, RAG pipeline optimization, and full-scale integration with the Company’s proprietary data systems.
The Agreement will be filed as an exhibit to the Company’s Current Report on Form 8-K with the Securities and Exchange Commission. Investors are encouraged to review the full text of the Agreement for complete terms and conditions.
Management Commentary
“The opportunity we see is simple but enormous,” said Avi Minkowitz, Chief Executive Officer of KALA BIO. “The biotech industry is generating more biological data than ever before, and the companies that can analyze that data fastest, find the patterns others miss, and translate those insights into therapies will help define the next era of medicine. But here is the problem: building AI infrastructure is expensive, complex, and requires specialized talent that most biotechs don’t have. And the existing options ask biotech companies to hand their most sensitive data to someone else’s cloud. We are building a third path, we expect to bring the AI to biotech companies, it will run on biotech companies’ servers, the data will stay with the biotech companies, and they will get the analytical information that the largest pharmaceutical companies obtain internally. That is the future we are investing in.”
Mr. Minkowitz continued: “We are starting with ourselves. KALA is client number one. We will prove this platform on our own data, our MSC-S platform, our KPI-012 program, our IP portfolio. And once we have demonstrated what it can do, we intend to make it available to the broader biotech industry. We believe the companies that win in the next decade will not be the ones with the most data, they will be the ones with the best AI infrastructure to extract value from that data. KALA intends to be a company that provides that infrastructure.”
Capital and Corporate Matters
The Company maintains an effective registration statement with the U.S. Securities and Exchange Commission, providing flexibility to access public capital, subject to market conditions and regulatory compliance. The Company may also attempt to raise capital privately. However, there is no assurance that the Company will be able to raise capital on favorable or acceptable terms.
About KALA BIO, Inc.
KALA BIO, Inc. (NASDAQ: KALA) is a clinical-stage biopharmaceutical company building a dedicated, on-premises AI infrastructure platform for the biotechnology industry. The Company’s dual strategy combines a proprietary biologics pipeline, including its mesenchymal stem cell secretome (MSC-S) platform and FDA Orphan Drug and Fast Track designated product candidates, with a scalable AI platform-as-a-service business designed to deploy secure, purpose-built AI systems directly within biotech and pharmaceutical client environments. Through its exclusive license for the Researgency AI research platform, KALA intends to serve as the dedicated AI infrastructure partner for the biotechnology industry, enabling companies of all sizes to unlock the value of their proprietary biological data without ever surrendering control of it. For more information, visit www.kalarx.com.
Forward-Looking Statements
This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, including statements regarding the Company’s strategic initiative to build an AI infrastructure platform for the biotechnology industry, plans to develop and deploy the Researgency AI platform both internally and to external clients, expectations regarding the potential benefits of AI-driven analytical tools, plans to reassess historical datasets and identify new therapeutic indications, expectations regarding the AI drug discovery market and industry trends, expectations regarding the Company’s ability to generate recurring platform revenue, plans regarding potential partnerships, client deployments, or technology licensing opportunities, expectations regarding the Company’s competitive position and the differentiation of its on-premises deployment model, the potential exercise of development continuation or renewal options under the Agreement, and other statements that are not historical facts.
The Company used words like “anticipate,” “believe,” “continue,” “could,” “estimate,” “expect,” “intend,” “may,” “might,” “plan,” “potential,” “predict,” “project,” “should,” “target,” “will,” “would” and similar expressions to identify these forward-looking statements. These statements involve known and unknown risks, uncertainties, and other factors which may cause actual results, performance, or achievements to be materially different from those expressed or implied by such statements. Important factors that could cause such differences include, but are not limited to: risks that AI technologies may not produce expected results in drug discovery or development; risks related to the development, deployment, and performance of the Researgency platform; risks that the Company may not successfully attract or retain external platform clients; risks that the platform-as-a-service business model may not generate anticipated revenues; risks that the Company’s product candidates may not be successfully developed or commercialized; risks related to the Company’s limited cash resources and ability to continue as a going concern; risks that the third-party information contained herein was not accurate at the time it was published and/or does not accurately predict the future; risks related to the Company’s ability to raise future capital and the possibility that market conditions may limit the Company’s ability to raise capital on favorable terms; risks related to the Company’s ability to regain compliance with Nasdaq listing requirements; competition from larger, better-resourced companies including major technology and pharmaceutical companies; dependence on key personnel and third-party technology providers; the accuracy of third-party market forecasts and projections cited herein; risks that the Company may elect not to expand or continue its deployment of the Researgency platform beyond the initial term; risks that Younet may not perform its obligations under the Agreement; and other risks detailed in the “Risk Factors” section of the Company’s Annual Report on Form 10-K as they may be revised in the Company’s Quarterly Reports on Form 10-Q and Current Reports on Form 8-K and other filings with the Securities and Exchange Commission.
Forward-looking statements speak only as of the date of this release, and the Company undertakes no obligation to publicly update or revise any forward-looking statements, whether as a result of new information, future events, or otherwise, except as required by law.
Contact:
Avi Minkowitz
Chief Executive Officer
AM@kalarx.com
__________________________
The Company has not independently verified the data or projections from third-party sources cited below. Such data involves risks and uncertainties and is subject to change based on various factors.
1 Mordor Intelligence, Artificial Intelligence in Drug Discovery Market — Size, Share & Trends Analysis Report (February 2026), estimating a CAGR of 25.94% from 2026–2031. See also Grand View Research, Artificial Intelligence in Drug Discovery Market Report, 2026–2033 (October 2024), estimating a CAGR of 24.8%.
2 Deloitte, Measuring the Return from Pharmaceutical Innovation (March 2025), reporting an average cost of $2.23 billion per drug for the world’s 20 largest pharmaceutical companies in 2024. See also Mulcahy, A. et al., “Use of Clinical Trial Characteristics to Estimate Costs of New Drug Development,” JAMA Network Open, Vol. 8, No. 1, e2453275 (January 2025), estimating a mean R&D cost of $1.31 billion per new drug approved by the FDA in 2019, after adjusting for cost of capital and discontinued products. Drug development timelines of 10 to 15 years are widely reported in peer-reviewed literature and industry analyses. See, e.g., U.S. Department of Health and Human Services, ASPE, Drug Development (October 2024); Human Specific Research, The Reality of Drug Discovery and Development (November 2025).
3 McKinsey & Company, Generative AI in the Pharmaceutical Industry: Moving from Hype to Reality (January 2024), estimating up to 50% cost reductions in clinical trial processes, and FounderNest, citing McKinsey & Company and industry data, reporting AI platforms can cut drug discovery costs by up to 40% and compress timelines from 5–6 years to 12–18 months for preclinical candidate nomination.
4 Jayatunga, M.K.P. et al., “AI in small-molecule drug discovery: A coming wave?” Nature Reviews Drug Discovery (2022), as cited in the CAS Insights report, “AI Drug Discovery: Assessing the First AI-Designed Drug Candidates to Go into Human Clinical Trials” (June 2024). See also PMC, “AI In Action: Redefining Drug Discovery and Development” (February 2025), documenting growth from 3 AI-designed clinical candidates in 2016 to 67 by 2023.
5 Hardman & Co, 2024 Pharma Statistics (April 2025). Cumulative R&D spend by the top 20 pharmaceutical companies by sales was $166.8 billion in 2024 ($153.1 billion in 2023). Total R&D spend across Hardman & Co’s universe of 45 pharma companies was $194.3 billion in 2024.
6 FounderNest, Pharma at an Inflection Point: Investment Trends 2024–2025 (December 2025), reporting that 95% of pharmaceutical companies now invest in AI, with aggregate AI spending expected to grow from approximately $4 billion in 2025 to $25 billion by 2030. See also McKinsey & Company (January 2024), estimating generative AI could generate $60 billion to $110 billion in annual economic value for the pharmaceutical and medical-product industries.
7 IBISWorld, Biotechnology in the US — Number of Businesses (2025), reporting 3,229 biotechnology businesses in the United States as of 2025 (NAICS classification).
