---
title: Akkemensia Case Study
description: How whole genome sequencing and advanced gut microbiome testing revealed the root cause of chronic brain fog and digestive problems.
image: https://casestudies.bioscope.ai/hubfs/Case%20Study%20Hubspot%20Featured%20Images-3.png
---

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# Akkermansia Case Study

Lina, a 34-year-old woman, experienced debilitating brain fog and digestive issues that lingered for months after a stomach flu. Her routine labs all came back normal. The solution wasn't a simple "IBS" diagnosis, but a deep dive that connected her **whole genome sequence** with her **gut microbiome** to find the missing link.

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### Frequently Asked Questions (FAQs)

Is Bioscope Service DTC?

No, it’s for physicians.

Does Bioscope.AI diagnose?

No. It works as an intelligent colleague helping human physicians do everything better, including diagnosing and treating patients.

Do you provide Buccal Swab Kit for Whole Genome Sequencing?

Yes. Once you sign up on our page, you should receive the buccal swab kit within 3-5 business days.

Who is this best suited for?

Any clinician who wants to deliver **personalized, precision care** — especially primary care, concierge practices, and health systems seeking to stand out. It’s also a powerful tool for research, population health, and nonprofit foundations addressing **health equity**.

Can you show me what a physician actually sees?

Yes, they see a **synoptic dashboard** (like a pilot’s cockpit) with green/yellow/red risk indicators across 14 health dimensions (e.g. metabolism, cardiovascular, immune, hormonal, environmental). They also see a **timeline view** of medical records, and can open an **AI Consultant Window** to ask questions.

How secure is patient data?

All data lives in a **HIPAA-compliant secure cloud repository**. Information is encrypted, access-controlled, and audit-logged. Each patient’s EMR, genome, and microbiome data are kept in their own secure profile, accessible only to authorized clinicians.

What makes Bioscope.ai trustworthy?

We don’t let the model guess. First, we **give the LLM all the context it needs**—the patient’s relevant clinical, genomic, and microbiome data, **plus a curated, continuously refreshed medical-knowledge store** (e.g., **ClinVar, ClinPgx, ClinGen**, along with **MONDO**, **HPO**, **MedGen**, **gnomAD**, **dbSNP**, and more). The LLM is then **tasked to reason strictly within that context**, not freestyle.

 

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