The Holy Grail in Healthcare Delivery

Intersect on FHIR™ is a fully integrated, real-time virtual care platform with the capability to enable the practice of genomic medicine.

Intersect on FHIR™ is a fully integrated, real-time virtual care platform with the capability to enable the practice of genomic medicine. Built on the FHIR standard, it streamlines clinical workflows while delivering real-time insights for chronic disease management and virtual care.

A key strength of Intersect on FHIR is its seamless integration of genomic and clinical data, allowing clinicians to make informed decisions based on a comprehensive view of the patient. By combining genomic insights with real-time clinical data from EHRs, predictive analytics, and data from remote monitoring, the platform further enhances the personalization of treatment plans. This integration supports more precise medication management, enables targeted therapies, and helps optimize patient outcomes, particularly in areas like cardiology, endocrinology, and oncology pharmacogenetics. The result is a holistic approach to care that empowers clinicians to provide tailored, evidence-based treatment strategies across primary care, hospitals, and specialty practices.

Here’s how Intersect on FHIR’s genomic capabilities can integrate into clinicians’ daily workflows across primary care, hospitals, and specialty practices—focusing on cardiology, endocrinology, and oncology pharmacogenetics.

Pharmacogenomics for Precision Prescribing

1. Realtime medication guidance

   - The platform will analyze a patient's genetic profile to predict drug response and recommend dosage requirements.

2. Adverse event prevention

   - Identifies genetic variants that impact drug metabolism, reducing the risk of adverse drug reactions (e.g., warfarin, statins, antidepressants).

3. Automated clinical decision support (CDS)

   - Alerts and recommendations integrated into the system (and EHR) when prescribing cardiology (beta-blockers), endocrinology (diabetes meds), and oncology (targeted therapies) drugs.

Genomic Risk Stratification and Early Disease Detection

1. Proactive analytics for chronic disease

   - Identifies genetic predispositions for conditions like cardiovascular disease, Type 2 diabetes, and hereditary cancer syndromes.

2. Risk-based screening recommendations

   - Personalized alerts to guide screening intensity for high-risk patients (e.g., cardiac imaging for those with FH mutations).

3. Population health integration

   - Uses genomic data to enhance risk models for stratifying patient cohorts in primary care, hospitals, and specialty clinics.

Integrated Genomic-Clinical Data for Personalized Care

1. FHIR-native genomic data exchange: Supports integration with labs and genomic testing services (e.g., polygenic risk scores, whole genome sequencing).

2. Longitudinal genomic records: Patients' genomic data is stored and updated alongside EHR records, ensuring continuity of care and better long-term management.

3. Dynamic treatment adaptation: Adjusts diabetes treatment plans based on genetic insulin resistance markers or cardiology interventions based on inherited cardiac risks.

Genomics-Driven Remote Monitoring and Virtual Care

1. Personalized remote monitoring alerts

   - Combines wearable data (HR, glucose, BP) with genetic predisposition insights to flag high-risk trends in chronic disease management.

2. Oncology virtual visits for precision medicine

   - Enables genomic tumor profiling integration in virtual visits to guide targeted therapy decisions.

3. Automated patient engagement

   - AI-driven education and personalized risk assessments help patients understand their genetic risk and lifestyle interventions.

EHR Interoperability and Real-Time Genomic Decision Support

1. Seamless genomic-EHR integration:

   - Embeds genomic reports into patient records without requiring external logins or additional tools.

2. FHIR-based genomic data sharing

   - Supports clinicians, specialists and researchers in leveraging biomarkers for clinical trials, research and precision therapy optimization.

3. Customizable genomic workflows

   - Allows clinics, hospitals, and specialists to configure disease-specific genetic insights for their practice.

Clinical Impact Summary

• Cardiology:

  Predicts drug response to beta-blockers, statins, and detects inherited cardiac conditions (e.g., Long QT syndrome).

• Endocrinology:

  Personalizes Type 2 diabetes by assessing genetic insulin resistance and medication metabolism.

• Oncology Pharmacogenetics:

  Matches tumor genomic profiles to targeted therapies, ensuring optimal treatment response with minimal toxicity.

Here are examples of how INTERSECT on FHIR's genomic capabilities will integrate into clinician's daily workflows across primary care, hospitals, and specialty practices - focusing on cardiology, endocrinology, and oncology pharmacogenetics.

Primary Care Workflow: Genomic Risk Assessment and Chronic Disease Prevention

Example: A 40-year-old patient with a family history of early heart disease visits for a routine checkup.

Step 1: Risk Stratification and Alerts

1. The system cross-references genomic data with vitals, (BP, cholesterol, BMI) and lifestyle factors

2. A real-time risk score suggests earlier statin initiation and lifestyle interventions

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Step 2: Clinical Decision Support (CDS) and Personalized Treatment

1. The CDS system flags a genetic variant (APOE ε4) linked to increased cardiovascular risk.

2. A guideline-based recommendation appears:

3. Start statin therapy at a lower dose due to potential metabolism issues

4. Increase frequency of lipid monitoring.

5. Offer referral for advanced cardiac screening

Step 3: Remote Monitoring and Virtual Visit Integration

1. The patient receives a mobile device configured with wearables to support a care plan to track BP and physical activity.

2. Real-time monitoring adjusts alerts based on genomic risk factors

3. The platform enables virtual visit follow-ups for adherence and lifestyle coaching

Cardiology Workflow: Pharmacogenomic-Driven Medication Management

Example: A 55-year-old male patient with atrial fibrillation needs anticoagulation therapy.

Step 1: Genomic Drug-Gene Interaction Check

1. Before prescribing warfarin, the platform automatically checks CYP2C9 and VKORC1 gene variants.
2. The system flags: Patient has a slow metabolism for warfarin → Increased bleeding risk.

Step 2: Personalized Medication Guidance

A popup suggests:

1. Lower initial dose of warfarin.
2. Monitor INR levels more frequently.
3. Consider alternative anticoagulants if needed.

Step 3: Continuous Monitoring and Risk-Based Interventions

1. Integrated remote INR monitoring detects variability in response.
2. If high INR is detected, a clinical decision support (CDS) alert advises immediate dose adjustment or switching therapy.

Endocrinology Workflow Genomics-Driven Diabetes Management

Example: A 35-year-old female patient with persistent hyperglycemia despite metformin use.

Step 1: Genetic Analysis of Drug Response

1. The platform flags a SLC22A1 variant that reduces metformin effectiveness.
2. The CDS tool suggests: Switch to SGLT2 inhibitors or GLP-1 receptor agonists.
3. Adjust lifestyle counseling based on insulin sensitivity profile.

Step 2: AI-Driven Digital Engagement

1. The patient receives personalized nutrition and exercise recommendations via INTERSECT's mobile patient application.
2. Wearable data integration (CGM, activity tracking) helps refine insulin therapy in real time.

Step 3: Virtual Visits Optimization

1. Endocrinologist reviews glucose trends remotely and adjusts therapy without requiring in-person visits.

Oncology Workflow: Precision Medicine and Targeted Therapy

Example: A 60-year-old lung cancer patient is undergoing genomic tumor profiling for treatment selection.

Step 1: Automated Tumor Genomic Analysis

1. The platform retrieves NGS (next-gen sequencing) results from the lab and integrates them into the EHR.
2. It detects an EGFR mutation, which suggests eligibility for targeted therapy.

Step 2: Clinical Decision Support and Personalized Therapy

1. The system flags FDA-approved targeted therapies (e.g., Osimertinib).
2. It suggests dose modifications based on the patient's liver enzyme metabolism genes (CYP3A4 variant).

Step 3: Treatment Monitoring and Genomic Adaptation

1. The platform continuously updates the tumor response profile and flags resistance mutations.
2. Oncology virtual visit follow-ups allow real-time dose adjustments and side-effect management.

EHR and Interoperability Workflow: Genomic Data Sharing and Clinical Collaboration

FHIR-based genomic data exchange ensures that primary care physicians, specialists, and pharmacists have access to up-to-date genetic insights.

1. Integrated FHIR APIs allow nteroperability with major genomic testing providers (e.g., Invitae, Foundation Medicine).
2. Secure, consent-driven data sharing enables collaboration between oncologists, cardiologists, and endocrinologists for cross-specialty care.

INTERSECT on FHIR has the capability to host eConsults between providers. Even when the specialist is not part of the same healthcare organization, they will be able to view the patient record and schedule and conduct virtual visits.

Are you ready to revolutionize chronic disease management? Let's talk.

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