DrugOS™ · AI-Augmented Therapeutics

Deeper patient understanding
More precise treatment

Understand patients through their habits, symptoms and treatment responses.
Build precision therapies and new treatment technologies on that understanding.

Official introduction · English · 5:20

DrugOS™
AI Agent
Patient Data
Clinician

Everyday life is part of treatment

Life and symptoms change between consultations.
DrugOS™ develops technology to understand those changes and inform treatment.

Daily habits

Patterns of sleep and activity

Symptom changes

Symptoms over time

Treatment responses

Changes during treatment

DrugOS™

From Data to Decision: The DrugOS™ System

A cycle of patient understanding and treatment development

01 / 04
Continuous Data Collection

Bring everyday and treatment records together

Understand patients through Dr.SAM conversations, DTx treatment records and health information.

02 / 04
Personalized Intelligence

Understand individual patterns and responses

Analyze daily habits, symptom changes and treatment responses together.

03 / 04
Treatment development

Turn patient understanding into treatment technology

Develop precision therapies and extend applications to DTx and digital combination drugs.

04 / 04
Evidence feedback

Bring treatment records back into development

Use accumulated treatment records and responses to deepen patient understanding.

Applying patient understanding to treatment

SleepQSerenQ
DTx

Condition-specific treatment programs

Treatment records inform condition-specific programs.

SleepQ® · MFDS authorized · Commercial
SerenQ® · MFDS authorized

Explore products
Medication and Dr.SAM concept
Digital combination drugs

Interpretable Decision Support

Developing technology to follow symptoms and medication responses and organize treatment progress.

In development

Explore digital combination drugs

Development and evaluation

Follow-on pipeline development time

54%

shorter

27 months12.5 months

SleepQ® SerenQ®

Dr.SAM medical-dialogue evaluation

65.8%

reduction in evaluation error rate

Before 4.50%After 1.54%

Same AI model · Internal evaluation, September 2026

How we evaluated Dr.SAM

The evaluation tested whether AI accepted fabricated conditions or misleading medical information as fact. Adding Dr.SAM to the same AI reduced the share of assessment items that failed the criteria from 4.50% to 1.54%.

Evaluation set
MHB-Dialogue · 2,602 dialogues and 11,623 assessment items
Comparison
The same AI model (GPT-5.6) and basic execution conditions were compared with and without Dr.SAM’s instructions and operating layer.
Date and evaluator
September 2026 internal company evaluation

65.8% is the relative reduction from 4.50% to 1.54% in this medical-dialogue evaluation. It is not a real-world clinical error rate, diagnostic accuracy measure or clinical efficacy result.

Develop new treatment possibilities together

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