Case Study: Building the ASPIRE Integrated Computational Platform for AI-Driven Chemical Research

Background

The accelerating pace of biomedical research and the growing complexity of chemical synthesis have highlighted the need for integrated, intelligent platforms to support data-driven discovery. Traditional approaches to drug development often suffer from fragmented workflows, limited data accessibility, and inefficient knowledge sharing across disciplines. At the same time, advances in artificial intelligence, cheminformatics, and high-throughput experimentation have created new opportunities to rethink how scientific knowledge is generated and applied.

Within this evolving landscape, the National Center for Advancing Translational Sciences (NCATS) launched the ASPIRE (A Specialized Platform for Innovative Research Exploration) program to advance the development of integrated, AI-enabled tools for accelerating translational science. The ASPIRE Integrated Computational Platform (AICP) was conceived as the program’s core informatics backbone, designed to unify data, algorithms, and user workflows into a cohesive environment that supports the full lifecycle of chemical research. The platform’s development was driven by a need to modernize and streamline how scientists access, analyze, and act on chemical and biological data in a reproducible and scalable way.

Problem

NCATS generates and manages vast amounts of chemical and biological data across diverse experimental workflows. However, many scientists lack the computational expertise needed to effectively access, analyze, and apply this data using advanced tools. This gap has made it difficult to fully capitalize on the potential of AI and data-driven methods within the ASPIRE program. There was a clear need for intuitive, scalable solutions that could bridge this divide, enabling domain experts to harness complex data and models without requiring deep technical knowledge.

Nextonic's Solution

Nextonic’s work led to a significant improvement in the software development culture within the AICP program. By introducing modern development practices, such as version control, modular design, automated testing, and cloud-native architecture, we helped establish a sustainable and scalable foundation for future tools and research efforts. Our solutions empowered scientists to access advanced cheminformatics capabilities without disrupting their research workflows, striking a balance between innovation and usability.

The adoption of these tools not only streamlined day-to-day operations but also accelerated data processing and model deployment timelines. As a result, our team played a direct role in supporting the publication of multiple peer-reviewed research papers—demonstrating the scientific impact and operational value of our collaboration.

Impact

Nextonic’s contributions have strengthened the technical foundation of translational science efforts within the AICP program. By embedding robust software engineering practices and building user-centered computational tools, we have helped NCATS bridge the gap between experimental research and data-driven discovery. Our work has enhanced the organization's ability to translate complex scientific data into actionable insights, supporting the broader mission of accelerating therapeutic development through technological innovation.