By Melane Sampson
Closely held AINGENS is addressing one of healthcare’s most persistent operational challenges—the costly, laborious process of transforming scientific data into compliant, actionable content. The company developed an integrated, evidence-first AI platform built specifically for medical affairs, biotech, clinical, and research teams.
“Rather than functioning as a generic generative AI tool, our proprietary MACg platform is designed as a purpose-built system that supports the entire scientific communication workflow—from literature search and evidence synthesis to citation management, document drafting, slide creation, and collaboration,” Ome Ogbru, PharmD, founder and CEO of AINGENS, says in an interview with BioTuesdays.
Maryland-based AINGENS, which stands for AI Narrative Generation and Engagement Solutions, was founded after Dr. Ogbru spent decades working across biotech, pharma, clinical practice, academia, and medical communications roles, experiencing firsthand the operational bottlenecks facing scientific teams. He points out that regulatory submissions, medical information letters, slide decks, training materials, and clinical summaries all require extensive literature review, specialized expertise, multiple layers of review, and strict compliance standards.
“Translating science into documents for education, product communication, or regulatory purposes is incredibly labor-intensive,” Dr. Ogbru notes. “It requires specialized training, significant time, and adherence to regulatory requirements. Even a single scientific document can take days, weeks, or months to complete, depending on complexity.”
While the life sciences industry has adopted numerous digital tools to support parts of the workflow, Dr. Ogbru explains that many organizations still rely on fragmented systems that operate independently. Literature search may occur on one platform, citation management in another, editing in another, and presentation development somewhere else entirely.
“What’s missing is a technology platform that can help with the actual writing and synthesis process while maintaining scientific rigor and compliance,” he contends. “Generative AI creates that opportunity, but only if it is implemented correctly and responsibly.”
MACg integrates multiple AI agents and workflow tools into a unified platform built specifically for scientific and medical content generation. Dr. Ogbru describes the platform as having an evidence-first framework, requiring users to ground outputs in verified scientific sources rather than relying solely on large language model training data.
“Our evidence-first principle is central to everything we do,” he says. “AI is not all-knowing. The customer brings the expertise and the evidence, and the platform helps accelerate the process. That’s when generative AI becomes truly valuable.”
Dr. Ogbru emphasizes that MACg integrates direct access to PubMed and PubMed Central, enabling users to search more than 37 million scientific citations and rapidly generate drafts from selected evidence. Users can upload proprietary documents, create a wide variety of content, generate citations automatically, and build scientific presentations within the same environment.
The company has also embedded proprietary citation-generation technology and reference management tools that automatically extract and format citations according to scientific standards. Additional capabilities include prebuilt prompts for common life sciences use cases, advanced editing tools, translation support, data visualization, and slide deck generation.
“Many in the industry struggle with prompting and workflow fragmentation,” Dr. Ogbru says. “We wanted to eliminate those pain points by creating a system that already understands the structure and demands of scientific communication.”
Unlike many public AI platforms, MACg was designed from inception with enterprise-grade privacy and compliance standards. The platform is SOC 2 and ISO 27001 certified, uses encrypted infrastructure, and does not use customer data to train AI models.
“We designed the platform so customer information remains private and secure,” Dr. Ogbru assures. “The AI uses the information to generate outputs, but does not retain or ingest the data into the model itself. If a customer deletes their work, it’s gone.”
He adds that the platform also ensures transparency and traceability—critical concerns for regulated healthcare environments. Users can trace generated content back to its original source material, including page references, tables, and supporting citations. Enterprise customers will also receive annotation capabilities identifying author, publication year, paragraph, and page number.
“One of the big issues with generative AI today is trust,” Dr. Ogbru says. “When errors occur, it’s often because systems are using generalized training knowledge instead of verified evidence. We built MACg to clearly distinguish between sourced information and inference.”
He highlights that if users attempt to generate content without uploading supporting evidence, the platform alerts them that it is using its general training knowledge rather than grounded scientific references. MACg also indicates when it does not have enough information to respond. In other words, it can say “I don’t know.” AINGENS views this transparency as essential for responsible adoption within healthcare and life sciences organizations.
The company believes its broader opportunity reflects the growing demand for AI solutions tailored specifically to regulated industries. Dr. Ogbru points out that pharmaceutical and biotech companies continue to face mounting pressure to accelerate development timelines, reduce operational costs, and manage increasing volumes of scientific data and documentation.
“Life sciences organizations are fundamentally content-generation organizations,” he says. “Whether it’s regulatory submissions, medical affairs, clinical development, or training, the industry runs on scientific communication.”
AINGENS believes the market opportunity extends beyond a single application. Rather than creating isolated point solutions, the company is building an integrated ecosystem capable of supporting multiple scientific workflows within one secure evidence-first platform.
“One of the problems emerging with generative AI is tool sprawl,” Dr. Ogbru says. “Organizations are adopting disconnected solutions for different workflows, which creates inefficiency and duplication. Our approach is to consolidate those capabilities into one integrated platform.”
The company offers both web-based and enterprise deployments. Individual users and smaller teams can access MACg through subscription or pay-as-you-go plans, while enterprise customers can deploy customized environments designed around specific therapeutic areas or organizational structures.
Notably, AINGENS believes enterprise implementation can occur rapidly compared with traditional software deployments. “In many cases, organizations can be operational with MACg within days,” Dr. Ogbru says. “We focus heavily on accessibility, scalability, and ease of adoption.”
Although MACg currently serves as the company’s flagship product, Dr. Ogbru suggests the platform is the foundation for broader workflow intelligence across life sciences. Future expansion could include analytics, additional workflow tools, and further automation capabilities, all integrated within the same infrastructure.
“We are not a one-product company,” he says. “We’re building integrated AI systems that address how medical, biotech, and clinical teams actually work.”
As healthcare organizations continue evaluating the role of generative AI in regulated environments, Dr. Ogbru believes that domain-specific, evidence-based platforms will ultimately outperform generalized AI tools that lack scientific oversight and workflow integration.
“We are not saying MACg is a magic bullet but it’s an amazing tool that is transforming the way experts conduct scientific communication—enabling them to work faster, more efficiently, and with greater confidence,” he concludes. “The expertise comes from the user. We are simply delivering a platform that unlocks that expertise more effectively.”
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