Contact us: support@ingentium.com

About Ingentium


About Ingentium: Pioneering AI-Driven Drug Discovery

Ingentium is at the forefront of revolutionizing the life sciences industry through our comprehensive AI-powered knowledge management platform. We specialize in accelerating drug discovery and development by harnessing the power of advanced technologies, including:

  • Disease-focused knowledge graphs
  • Large Language Models (LLMs)
  • Cooperative AI systems
  • Cognitive intelligence platforms
  • Machine learning algorithms

Our Platform

Our cutting-edge platform integrates vast amounts of public and proprietary biomedical data, presenting it in a semantically rich format that enables researchers to uncover meaningful insights quickly. Key components include:

  1. Disease-Focused Knowledge Graphs: Daily-updated, semantically rich representations of complex biomedical relationships, tailored for pharmaceutical research.
  1. Specialized LLMs: AI models fine-tuned on extensive medical datasets, capable of understanding and predicting complex patterns in disease progression and treatment responses.
  1. Cooperative AI Platform: A state-of-the-art system that integrates multiple AI technologies, including multi-agent retriever systems, to address challenges across the entire drug discovery and development value chain.
  1. Charisma Cognitive Intelligence Platform: A revolutionary search and processing system for unstructured enterprise data, featuring advanced semantic structuring and intelligent query capabilities.
  1. The Ingentium Biomedical Knowledge Graph Scaffold: A comprehensive biomedical properties graph containing over 14 million interconnected nodes and 34 million edges, serving as a foundation for internal knowledge graph initiatives.

Our Impact

Ingentium’s solutions empower pharmaceutical and biotech companies to:

  • Facilitate cross-functional collaboration through our cooperative AI platform
  • Accelerate research and development cycles
  • Improve operational efficiency
  • Identify novel drug targets and repurposing opportunities
  • Optimize clinical trial design and patient selection
  • Enhance decision-making through data-driven insights

About Our Team and Experience

Led by experts with decades of experience in biomedical research, informatics, and artificial intelligence, Ingentium’s team brings diverse expertise from pharmaceutical research, computer science, and business leadership.

Keith Elliston, PhD – Executive Chairman

Dr. Elliston is a seasoned entrepreneur and leader in the biomedical field with over 15 years of experience in the pharmaceutical industry. He is the co-founder and Executive Director of the i2b2 tranSMART Foundation and has founded several biotechnology companies focused on biomedical computing, digital health, and artificial intelligence. His track record includes successful roles as CSO, CEO, and Executive Chairman for multiple companies, demonstrating his ability to drive innovation and growth in the biomedical sector..

Rudy Potenzone, PhD – Vice President and COO

Dr. Potenzone is a highly accomplished executive with extensive experience in delivering quality, profitable, and customer-focused products in the life sciences industry. He excels in developing product roadmaps and corporate strategies, with particular expertise in global life science informatics, knowledge management, and workflow systems. Dr. Potenzone is known for his ability to lead scientific and technology teams in delivering novel products and services, as well as his skills in organizational development and executive-level communications..

Richard Blevins, PhD – Vice President and CIO

Dr. Blevins brings a wealth of experience from the pharmaceutical R&D industry to Ingentium. He is a leader and scientist with expertise in computational biology, informatics, chemistry, biochemistry, and molecular biology. Dr. Blevins has a strong background in departmental creation, staffing, and administration in large pharma, small biotech, and academic environments. His visionary leadership and ability to establish strong relationships with scientists make him adept at applying informatics techniques to biomedical research and drug discovery processes.

About the Charisma Cognitive Intelligence Platform

Charisma is a cognitive intelligence platform that revolutionizes the way we search for and process vast amounts of unstructured data used and generated by an enterprise. Traditional databases are insufficient for handling the many types of media, sources, and languages in which information is now stored. Charisma addresses this problem by aggregating and semantically structuring data by meaning, then facilitating query and intelligent delivery of integrated results. It is capable of ingesting unstructured data from internal and public sources and conducts semantic normalization, metadata extraction, indexing, and normalization of the ingested material to allow the user to query vastly different types of data.

Charisma also has the ability to mine all sources of unstructured data to identify new knowledge such as disease biomarkers and pathways that were previously unconnected. The platform can be integrated with other tools, such as translational medicine platforms, to provide additional information feeds and automated curation for the data held inside the platform. Charisma allows scientists to quickly leverage large volumes of data that were previously unmanageable, enabling them to produce better science at a much faster rate. The result is that an organization can simultaneously do things it was previously unable to do and do it less expensively.

The Charisma Evidence Processing Pipeline

The Charisma Evidence Processing Pipeline is the workflow system behind the Charisma Cognitive Intelligence Platform. The pipeline comprises Crawlers, Evidence Data Preparation, Charisma Metadata, Charisma Categorization Engine, Charisma Clustering Engine, and Evidence Publication. The Charisma Categorization Engine automatically places evidence into the best-scored category against each machine learning model. The Charisma Clustering Engine generates a hierarchical list of named clusters that organize all knowledgebase evidence. Finally, the content is delivered through the Ingentium Magazines via Flipboard, AppleNews, RSS feeds, email reports, and social media platforms such as Twitter, Facebook, Slack and LinkedIn.

Charisma Machine Learning

Charisma Machine Learning is a suite of applications and algorithms used to process vast amounts of unstructured data for biomedical knowledgebases. The applications used include Mallet, Python NLTK, Python SciKit Learn, TensorFlow, and proprietary Ingentium applications. The algorithms used include sentence splitting, tokenization, lemmatization/stemming, POS tagging, shallow parsing, full parsing, support vector machines, and named entity recognition. These algorithms are used to map syntactic forms of words into their canonical base forms, to analyze the syntactic structure of sentences, and to categorize and recognize biomedical entities mentioned in text. By utilizing Charisma Machine Learning, Charisma is able to semantically structure and categorize vast amounts of unstructured data to provide valuable insights and knowledge for biomedical researchers and organizations.

The Ingentium Biomedical Knowledge Graph Scaffold

The Ingentium Biomedical Knowledge Graph Scaffold is a biomedical properties graph that contains the base nodes and edges required to represent the bulk of biomedical knowledge. It contains over 14 million interconnected nodes, including diseases, chemical compounds, biomolecules, and core concepts. The scaffold can be used to jumpstart internal knowledge graph efforts and can be augmented through the integration of knowledge sources like the Ingentium disease-focused knowledge bases. The scaffold is connected through more than 34 million edges, with various relationship codes and edge metadata for each type of relationship. The iKG semantic predication application is used to extract semantic predications from biomedical free text, which are processed and stored in the iKG.