The global move towards AI-powered tools is sweeping across the life sciences industry. In particular, the roles biostatisticians play in both clinical trial design and programming lend themselves to AI-based innovations.

Earlier this month, Cytel launched its first AI-driven solution for clinical trial design code generation and joined the artificial intelligence revolution. This innovation is predicated on several years of research and development, coupled with the recent maturing of AI-focused service providers. The solution is designed for optimal functioning within the East Horizon platform and intended to enhance R integration functionalities that are now embedded within our software.

What makes Cytel’s AI-powered R coding assistant unique?

The coding assistant generates R code with required parameters for East Horizon. Unlike generic AI-based coding tools that generate standalone R scripts, this solution ensures the generated code includes function templates, expected arguments, and input variable names; is structured for direct integration into East Horizon’s simulation engines; and is aligned with industry best practices for regulatory-compliant clinical trials. In addition, the coding assistant is purpose-built for biostatistics and clinical trial design.

General-purpose AI tools do not innately relate to adaptive trial designs, survival analyses, or clinical trial randomization. Cytel’s AI-powered R coding assistant allows biostatisticians to generate custom statistical tests beyond software-native options; perform advanced patient data modeling such as Quasi-Poisson, longitudinal outcomes, etc.; and allows for alternative randomization and drop out modeling methods.

Finally, the coding assistant is embedded within an industry-standard solution for trial design. The solution ensures compatibility with East Horizon’s statistical engine, generating code that is formatted correctly and validation-ready.

How does the solution work?

Users interested in augmenting their trial design simulation work can select the R integration features within the software and gain access to the coding assistant. Users then enter prompts in natural language to illicit a response. The user can review the response, iterate and refine with additional queries, and modify the code to fit the task at hand. Once refined, the code can be employed in simulation runs for additional validation and debugging.

Why does this matter?

The AI-powered R coding assistant in East Horizon enables biostatisticians to generate complex R code instantly; customize trial simulations with precise statistical methods; and reduce manual coding errors and speed up model validation.

Custom R coding for oncology designs

The ability to augment design characteristics with custom R code is especially relevant to the ever-evolving oncology area of study. As regulatory guidelines are routinely adjusted to comply with clinical practice and current research, oncology studies often require specific analysis approaches and/or patient outcome data generation methods to conform to changing evidence thresholds. For example, the testing method and analysis type chosen for a specific design can be highly sensitive to the underlying distribution of the data. Therefore, simulating designs with a variety of analysis types can help design studies that are robust to a variety of possible data distributions.

With this in mind, using commercial software to generate patient outcome data through simulation takes full advantage of the software’s native workflows and computing power. These data are then analyzed against a variety of analysis types using R code augmentation. This approach to analysis variation also lends itself to advanced Bayesian tests, affording biostatisticians maximum flexibility.

Want to learn more?

In our recent webinar, “Evaluating Different Analysis Options for Your Oncology Study Design by Combining East Horizon and R,” J. Kyle Wathen and Valeria Mazzanti discuss clinical trial design using a combination of R coding and Cytel’s proprietary statistical software, with a focus on analysis testing variations:

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