Evinova AI: Accelerating Clinical Trials with Confidence

Evinova’s AI platform accelerates clinical development while giving sponsors control, compliance, and confidence across every phase of the trial lifecycle.

Evinova’s AI Enabled Platform diagram: a semicircular arch labeled “Agentic AI” containing five colored segments—“Portfolio Management” (purple), “Study Design & Optimization” (green), “Accelerated Patient Recruitment” (gray), “Digital Trial Solutions” (pink), and “Analysis & Submission” (yellow). Centered below the arch is “AI Enabled Platform,” and a rectangular base beneath reads “Data Foundation.”

Turning Clinical Complexity into Clarity

Busy clinical teams are overwhelmed, buried under protocols, paperwork, and endless streams of data. Evinova's AI-enabled clinical development platform helps teams reduce operational inefficiencies, improve workflows and accelerate trial delivery.

Designed by a team who's lived through your challenges, our platform is anchored in scientific excellence, delivering precise, data-driven insights you can trust. By automating routine tasks and highlighting what truly matters, Evinova’s AI platform frees your team to focus on what they do best: driving scientific progress and delivering the next breakthrough medicine.

Designed to Solve What Matters

Clinical development is often slowed by fragmented systems, manual processes, and inefficiencies that delay timelines, increase costs, and limit patient access.

Protocol authoring can take at least 3–4 months; approximately 45% of amendments are avoidable, each costing an average of $500K. [1] [2]

55% of sites identify technology as their top operational burden—managing
multiple sponsor platforms simultaneously creates fragmented workflows and
redundant data entry. [3]

Patient burden leads to high dropout rates—up to 40% of site visits could be eliminated. [4]

Recruitment is slow and costly, with timelines often slipping by months. [5]

Limited portfolio visibility can significantly hinder strategic decision making, potentially costing sponsors hundreds of millions of dollars in unrealized value each year. [6]

Scalable Solutions, Proven Results

Our platform embeds AI from end-to-end to streamline operations, reduce burden, and drive faster, more informed decision-making.

Optimize Your Portfolio

Transform portfolio strategy to maximize probability of success and net present value, mitigate large risks, and shift focus from data wrangling to decisive action.

Accelerate Study Design

Slash protocol development from months to days, reducing costly and time-consuming amendments and enabling rapid scenario modeling across key design variables – including 97% costing accuracy – while powering downstream automation.

Streamline Study Start Up

Launch studies faster with seamless eConsent, GenAI-powered workflows, and single sign on to simplify site operations and reduce startup friction.

Enhance Trial Execution

Enable 25–40% of site visits from home with seamless eCOA and connected
device integration, accelerate enrollment by as much as 30%, and reduce
dropouts by up to 60% with a unified, digital trial experience.

Solutions on the Evinova AI platform stand apart through proven performance. Developed and scaled within large pharma, our evidence-led approach delivers measurable outcomes for even the most complex, matrixed organizations. We don't just promise results—we prove them.

How Our Platform Works

Built for clinical development at scale, the Evinova AI platform offers a modular, secure architecture that integrates seamlessly with sponsor systems to enable faster deployment, consistent data flow, and greater control across every phase of the trial.

Built on Secure, Scalable Infrastructure

The Evinova AI platform is built on a robust, multi-tenant architecture designed for performance, compliance, and sponsor control. At its core is a scalable data foundation that ingests and harmonizes information from diverse sources such as protocol documents, operational systems, and more, transforming them into structured, machine-readable formats aligned to USDM and M11 standards. This enables consistent data flow across modules and supports AI-driven insights throughout the clinical lifecycle.

Each sponsor’s data is logically isolated in virtual containers, encrypted with AES-256, and managed with customer-specific keys. Role-based access, SAML 2.0/OAuth 2.0 identity federation, and global data localization ensure compliance with ICH E6, GxP and regional regulations. Evinova applies rigorous governance to every AI capability – outputs are traceable to source documents, models are trained on validated data, and sponsors can configure thresholds, review flows, and audit trails.

Our AI is always human-in-the-loop, designed to enhance expert judgment, not override it. From AI-generated drafts refined by specialists to site workflow experts, our solutions blend automation with human judgment to drive smarter, faster clinical trials. Our platform eliminates mundane tasks and highlights critical insights, empowering teams to concentrate on strategic decision-making and enhanced patient outcomes.

The Evinova AI platform is designed to integrate into your existing ecosystem. With open APIs, standards-based data models, and modular deployment, sponsors can connect Evinova to their CTMS, EDC, eTMF, and analytics tools to drive value without disruption. The platform also supports a bring-your-own-model (BYOM) approach, allowing sponsors to embed proprietary algorithms within Evinova’s secure infrastructure – maintaining control, compliance, and continuity across their clinical systems.

Ready to accelerate your clinical development with Evinova AI?

Book a personalized consultation to explore how Evinova’s platform can streamline operations, enhance patient experience, and deliver measurable results across your trials.

Contact Us

Sources

[1] Getz, K., Campo, R., and Kaitin, K. (2018). Variability in protocol design complexity by phase and therapeutic area. Nature Reviews Drug Discovery, 17(8), 592.
[2] Getz, K., Stergiopoulos, S., Short, M., Surgeon, L., Krauss, R., Pretorius, S., Desmond, J., and Dunn, D. (2016). The impact of protocol amendments on clinical trial performance and cost. Therapeutic Innovation and Regulatory Science, 50(4), 436-441.
[3] Society for Clinical Research Sites. (2024). 2024 Site Landscape Survey. Retrieved from https://myscrs.org/learning-campus/white-papers/
[4] Durán, C.O., Bonam, M., Björk, E. et al. Implementation of digital health technology in clinical trials: the 6R framework. Nat Med 29, 2693–2697 (2023).
[5] McDonald, A. M., Knight, R. C., Campbell, M. K., Entwistle, V. A., Grant, A. M., Cook, J. A., Elbourne, D.R., Francis, D., Garcia, J., Roberts, I., and Snowdon, C. (2006). What influences recruitment to randomisedcontrolled trials? A review of trials funded by two UK funding agencies. BMJ Open, 332(7550), 1107-1111.
[6] McKinsey & Company. The road to positive R&D returns. McKinsey Quarterly, 2010. Retrieved from 
https://www.scribd.com/document/37958312/McKinsey-Pharma-Case
Z4-70095 | November 2024