Improving clinical trial patient recruitment
Our platform uses proprietary LLMs to analyze structured and unstructured EHR data, streamlining recruitment workflows and optimizing the process from end to end.
Features
Bond Health's services uniquely provide:
Automated Pre-Screening from EHRs
Combines structured fields and unstructured data insights (clinical notes, imaging, genomics, biopsies, etc.) from our proprietary LLMs to surface nuanced insights and reduce manual chart review.
Patient Match Scoring Engine
Each candidate receives a real-time match score out of 100 based on alignment with inclusion/exclusion criteria, with traceable rationale for site coordinators.
Real-Time Patient Tracker
Manage patient status across the recruitment pipeline, from screening to enrollment, with integrated timelines and update logs.
Built-In Metrics Monitoring
Track recruitment KPIs, enrollment rates, trial timeline dates, and cost-efficiency with real-time dashboards.
Benefits to Stakeholders
How we enhance the experience across the board
Clinical Research Coordinators
We streamline recruitment by automating early screening, surfacing relevant insights, and simplifying patient tracking across the trial pipeline.Automated Trial Matching
Uses structured fields and free-text clinical notes to flag likely candidates based on trial-specific parameters.
Centralized Recruitment Tracker
Provides a real-time dashboard of each patient's status, communication history, and site-level progress across all studies.
Enhanced Insight Extraction
Our LLMs parse unstructured data to resolve vague or complex eligibility factors, reducing screen failure rates and manual chart review.
Patients
Although not direct users, patients benefit from more accurate, inclusive, and ethical recruitment that aligns with their clinical needs and rights.Better Representation
The platform promotes equitable access by including overlooked demographics and patients with rare or nuanced conditions.
Privacy First
Patient data is handled with strict HIPAA compliance, and individuals may opt out of future analysis or trial matching at any time.
Empowered Access
Personalized matching is based on a patient's real health history and not limited by narrow filters or outdated inclusion logic.
Sponsors, CROs, and Researchers
We support more targeted trial design and efficient execution by enabling earlier identification of real-world patient characteristics, improving data quality and downstream impact.Deeper Cohort Insights
LLMs identify complex or subtle clinical features, such as disease subtypes or comorbidities, from unstructured data to refine inclusion criteria and study populations.
Recruitment Intelligence
Dashboards track key metrics including enrollment velocity, screen failures, and cost-efficiency, allowing sites and sponsors to adjust strategies in real time.
More Actionable, Generalizable Research
More representative and well-characterized cohorts enable researchers to generate findings that are both generalizable and more likely to translate into meaningful real-world clinical outcomes.
How we work
Our step-by-step process
Step 1: Sponsor Provides Trial Criteria
Inclusion/exclusion criteria, preferred demographic profiles, and endpoints are received.
Step 2: EHR Integration & Pre-Screening
The platform scans de-identified EHRs (including free text notes) to identify likely eligible patients.
Step 3: Research Coordinator Dashboard Interface
Research coordinators can view patient match scores to specific trials, unstructured insights (family history, biopsies, etc.), and patient enrollment status.
Step 4: Trial Matching Recommendations
LLM-generated rationales clarify why a patient is or isn't a fit for a trial, with guidance for ambiguous cases or additional screening.
Step 5: Ongoing Monitoring & Tracking
Research coordinators can manage communication, update patient status, and track recruitment progress.
Future Directions
Next steps for our services
Our commitment to streamlining these processes never stop! Here are current approaches we are working on to enhance our platform and services.
Incorporating data beyond standard medical records (wearable device metrics, patient-reported outcomes, social determinants of health, and lifestyle data) to enable more holistic and personalized trial matching.
Predictive models to identify patients at risk of dropout and enable early intervention.
Using real-time cohort insights to help refine inclusion/exclusion criteria and optimize trial protocols for more successful recruitment.
Supporting non-academic and community sites with recruitment tools to broaden geographic and demographic reach.
Collects communication preferences and referral patterns to recommend optimal outreach strategies for engaging physicians and patients more effectively.
Enabling researchers to model and test hypothetical cohorts by toggling criteria and thresholds dynamically.
Allowing users to trace back extracted insights to their original source documents for audit and validation.
Enabling sponsors and CROs to identify eligible patients across multiple sites by harmonizing data formats, eligibility logic, and compliance requirements.
Expanding platform compatibility with international EHR systems and regulatory frameworks to support global research sites and multi-country trials.
FAQs
Frequently Asked Questions
Here are some of the common questions surrounding our company's objectives and logistics.
Who is your platform for?
Bond Health is built for clinical research coordinators and is funded by CROs and sponsors to streamline patient screening and recruitment. While patients benefit indirectly, they are not the end users of the platform.
Do patients need to sign up or give consent?
No, the platform uses de-identified EHR data provided by partnered research institutions, so patients do not need to enroll or take any action. All data use is HIPAA-compliant and handled securely.
How do you make money?
We charge a flat fee to list each clinical trial on our platform, then apply tiered pricing based on the number of patients engaged and the clinical complexity of the trial. Higher tiers account for rare conditions, multi-site coordination, and expanded inclusion criteria.
Can the platform support rare disease or complex trials?
Yes, our proprietary language models extract insights from unstructured data, making them effective for identifying patients with rare or complex conditions. This improves pre-screening precision for even the most targeted studies.