Clinical Trial Design & Optimization Suite

AI-powered tools to design smarter trials, optimize protocols, and accelerate execution.

Trial Intelligence Platform

MODULE 1

AI-Assisted Trial Design & Planning

Evidence-Based Protocol Optimization

MODULE 2

Investigator, Site & Geo-Intelligence Mapping

Multi-Source Evidence Integration for Site Selection

MODULE 3

Trial Matching & Emulation

Optimizing Protocol Intent for Trial Success

MODULE 4

Trial Protocol Digitalization

From Static Documents to Intelligent Assets

THE FOUNDATION: BENEATH THE SURFACE

INTEGRATED REAL-WORLD DATA (RWD)

Direct pipelines into claims, EHR-derived datasets, & patient registries to ground clinical assumptions in real-world journeys.

LIVING KNOWLEDGE BASE

Continuously updated, AI-curated repository harmonising global research, trial registries, & internal institutional memory.

HUMAN-IN-THE-LOOP (HITL)

Expert-led validation ensuring AI-driven extractions meet rigorous clinical & regulatory accuracy standards.

AI-Assisted Trial Design & Planning

NouStarX transitions clinical trial design from manual documentation to a dynamic, data-driven scenario analysis. By leveraging a multi-dimensional Living Knowledge Base—synthesized from global trial registries, peer-reviewed literature, and internal datasets—our platform provides the scientific logic required to justify endpoints, optimize cohorts, and mitigate operational risks before protocol finalization.

MODULE 1: AI-Assisted Trial Design & Planning

Key Capabilities

  • Intelligent Design Benchmarking: Synthesize historical protocols and literature to identify proven design patterns while avoiding competitive "white spaces" and past failure points.
  • Protocol & Population Optimization: Use AI to refine eligibility criteria and lean out assessment schedules, accelerating recruitment and reducing operational costs.
  • Evidence-Grounded Strategy: Justify endpoint and comparator selection using a robust foundation of regulatory precedents, clinical guidelines, and current standards of care.
  • Regulatory & Safety De-Risking: Minimize clinical holds and amendments through real-time alignment with FDA/EMA guidance and historical safety signals.
  • Predictive Feasibility & Value: Forecast enrollment trajectories and automate the creation of a consistent scientific narrative from early development through to payer submission.
  • Cross-Layer Evidence Integration: Harmonize data across literature, trial registries, RWE, and internal insights to ensure a defensible, submission-ready trial design.

Investigator, Site & Geo-Intelligence Mapping

NouStarX optimizes trial placement through the convergence of our Living Knowledge Base and Real-World Data (RWD). We utilize high-fidelity geospatial epidemiology, which derived from EHR, claims, and physician databases to quantify patient density and phenotype Principal Investigators (PIs) based on scientific output and operational history.

MODULE 2: Investigator, Site & Geo-Intelligence Mapping

Key Capabilities

  • Principal Investigator (PI) Phenotyping: Quantifying investigator impact through longitudinal analysis of citation indices, therapeutic leadership roles, and technical experience with specific mechanisms of action (MoA).
  • Quantitative Site Performance Analytics: Ranking clinical sites by integrating historical accrual and retention metrics with RWD signals that indicate current institutional capacity and research infrastructure.
  • Geospatial Patient Density Mapping: Utilizing EHR and claims data to pinpoint geographic "hotspots" with high concentrations of protocol-eligible patients, mitigating the risk of site-level recruitment failure.
  • Diversity & Health Equity Stratification: Facilitating compliance with regulatory diversity mandates (e.g., FDA DEPICT Act) by mapping sites in regions with verified demographic representation and health equity metrics.
  • Longitudinal Evidence Surveillance: Continuous monitoring of the investigator landscape to capture emerging scientific leaders, new trial results, and shifts in regional standards of care.

Trial Matching & Emulation

NouStarX bridges the gap between protocol design and execution through AI-powered trial emulation. By translating complex eligibility criteria into computable logic and applying it to high-depth Real-World Evidence (RWE), we enable teams to "test-run" their trials in silico. This ensures your design is optimized for recruitment speed, statistical power, and real-world relevance before the first patient is ever enrolled.

MODULE 3: Trial Matching & Emulation

Key Capabilities

  • AI Patient Matching: Convert protocol criteria into structured logic to instantly find eligible patient cohorts within EHR and claims data.
  • Protocol Stress-Testing: Simulate different eligibility rules and endpoints to see how they impact enrollment speed and trial outcomes.
  • Design Trade-off Analysis: Find the "sweet spot" between recruitment speed, patient diversity, and statistical power to maximize your ROI.
  • Precision Geo-Mapping: Validate site and regional patient density to ensure your trial is placed where the patients actually are.
  • Traceable Evidence: Every design decision is backed by a transparent, audit-ready link between your protocol and real-world data. Shape

Trial Protocol Digitalization

NouStarX transforms narrative clinical protocols into dynamic, machine-readable assets. By utilizing a metadata-driven design and CDISC-aligned standards, we encode trial elements into computable definitions. This ensures total semantic interoperability, enabling the automation of trial registries, screening tools, and data capture configurations.

MODULE 4: Trial Protocol Digitalization

Key Capabilities

  • Semantic Encoding & CDISC Alignment: Automatically map protocol narratives to standardized terminologies (MedDRA, SNOMED-CT), ensuring your trial is "born digital."
  • Automated Recruitment & Screening: Enable API-ready connections between protocols and site-level tools for real-time patient matching and automated feasibility checks.
  • Structured Schedule of Activities (SoA): Digitize assessment windows and procedures to automate site tasks and drastically reduce procedural deviations.
  • Recursive Change Propagation: Track amendments through a version-controlled repository that automatically flags downstream impacts on EDC forms and statistical plans.
  • Cross-Stakeholder Consistency: Eliminate interpretive variance between sponsors, CROs, and sites by providing a "Single Source of Truth" for all trial criteria.
  • Governance & Verification Bridge: Ensure clinical intent remains intact with integrated workflows for experts to audit and validate AI-generated logic.