Harnessing AI for Drug Discovery Certara Amplifies CODEX Platform Capabilities

Certara, a leader in biosimulation, has recently expanded the horizons of AI in drug discovery with the introduction of artificial intelligence (AI) capabilities and data fabric connectivity to its clinical trials outcome analytics platform, CODEX.

Based in Princeton, New Jersey, Certara is renowned for its application of proprietary biosimulation software, technology, and services to speed up drug discovery and development. Serving over 2,000 biopharmaceutical companies, academic institutions, and regulatory agencies across 62 countries, Certara's objective is to redefine conventional drug discovery methods.

Their platform, CODEX, is central to this endeavor. Traditionally, CODEX has been a stalwart tool for trial sponsors, clinical research organizations, and biopharmaceutical companies to extract critical insights from clinical outcomes. Now, with the infusion of AI, the CODEX platform is set to further amplify its capabilities.

The drug development landscape is fraught with complexities and challenges. A case in point is the startling fact that only 1 in 5,000 drugs in development ultimately makes it to the market as a commercial product. Dr. Christopher Bouton, SVP and Head of AI at Certara, emphasizes the urgent need for a comprehensive insight system to improve these odds. He explains that the industry's knowledge of clinical trial outcomes is scattered across disparate sources, making it difficult for researchers to form a unified understanding.

In response to this challenge, the upgraded CODEX platform aims to bring a consolidated platform for analyzing and predicting trial outcomes, thereby substantially enhancing the success rates of phase-2 and phase-3 trials where the expenditure is typically at its peak.

The upgraded CODEX platform introduces several pivotal features:

1. Flexible Data Integration: Thanks to an underlying data fabric architecture, users can effortlessly integrate multiple first, second, and third-party databases, capitalizing on existing data storage.
2. Advanced Search and Unstructured Data Analysis: Powered by deep learning, large language models, and generative pre-trained transformers (GPTs), users can swiftly query and extract insights from unstructured documents, published research, and other content-rich resources.
3. Intuitive Interface: The user-friendly interface of the CODEX Analytics App simplifies the visualization and analysis of clinical outcomes data, allowing users to derive valuable insights to inform drug and overall trial performance.

These capabilities are backed by the advanced data fabric and deep learning platform that Certara acquired from Vyasa, a recognized solution for deep learning large language models. These models are vital for making structured, unstructured, and semi-structured data sources more accessible to clinical researchers.

In conclusion, Certara's incorporation of AI into the CODEX platform embodies a concrete step to streamline clinical trial processes and improve success rates. This development marks a practical application of advanced AI capabilities within the pharmaceutical industry's challenging landscape.