
AI-DRIVEN DIAGNOSIS OF
RARE (HIDDEN) DISEASES
Our mission is to support all market stakeholders in diagnosing patients with rare diseases for clinical trials, treatment or patients’ monitoring. Developed algorithms, that analyse EHRs, are implemented on our platforms: (i) SARAH Platform – for medical clinics, (ii) VIRTUAL CLINIC Platform – for patients.
OUR PRESENCE
Canada (Calgary)
USA (Boston)
Germany (Leipzig/Berlin)
Poland/CEE (Warsaw)






Brazil (Sao Paulo)
Comprehensive solutions to diagnose rare diseases
Inverted pyramid approach enables data structuring and patients' pathway optimization
100% population
Users
Input data (EHRs)
Output data (for MDs*)
Primary
care
Outpatient
specialist
Inpatient
specialist
Triage
Diagnosis
Primary
Care
-
Complete Blood Count
-
Optional: Biochemistry
-
Optional: Limited interview notes, physical examination (converted into 5-10 symptoms)
Outpatient
Specialist Care
-
Complete Blood Count & Biochemistry parameters
-
Interview notes, physical examination, radiology (converted into 8-15 symptoms)
-
Optional: ICD-10, drugs
-
CBC irregularities
-
Suggested interview & physical examination
-
Likely disease (segment)
-
Suggested tests & specialists' consultations
-
Identified symptoms & irregularities
-
Suggested diseases (group of diseases)
-
Rationale
-
Recommended next steps
Inpatient
Specialist Care
-
CBC & Biochemistry
-
Interview notes, physical examination, surgeries, treatment & other events
-
Radiology, histopathology and other tests
-
Other ICD-10, drugs
-
Identified symptoms & irregularities
-
Suggested disease
-
Rationale
-
Recommended next steps (e.g. type of genetic tests)
~6-8% RD population
OUR FOCUS ON RARE DISEASES
Key facts
6-8% (550 mln)
of global population suffer from rare diseases
50%
affected are children
>7 000
known rare diseases
only 10%
of rare diseases have treatment
~5 years
on average takes the diagnostic process of rare diseases from first symptoms
only 1 out of 8
patients with rare diseases is diagnosed & duly treated, many remain undiagnosed
Our current focus
Blood and bone
marrow diseases
-
Blood cancers (various including, mastocytosis and myelofibrosis)
-
CTCL
-
TTP
-
PNH
-
Castleman
-
ITP
-
HLH
-
PNH
Metabolic
-
Gaucher disease
-
Fabry disease
-
Pompe disease
-
HAE
-
MPS 1
-
MPS 2 (Hunter)
-
MPS 3
Immune system
-
Common variable immunodeficiency (CVID)
-
Severe combined immunodeficiency (SCID)
-
DiGeorge syndrome
-
Chronic granulomatous disease (CGD)
Cardiology
-
Amyloidosis AL
-
Amyloidosis ATTR
do wpisania
OUR TEAM
Global
Szymon
Piątkowski
CEO/Founder

Prof.
Grzegorz
Basak
CMO/Founder
Joanna Jarmoc
Business Development
Poland/CEE

Karol Lis, MD
General Manager/Founder


Marek Dudziński, MD, PhD
Medical Director/Founder
Adrian Michalski Technology Director
Brazil

Henrique Malina
General Manager
Business & Operations
Germany

Maciek Klein
General Manager
AI / Data Science
US/Canada
Szymon Piątkowski
Interim
IT / Programming
Maciej Majewski
Bloodlab Product Lead

Karolina Popławska
HR Manager

Mateusz Firlej
Business Analyst

Marta Koryga
RD Virtual Clinic Product Lead

Dominika Materka
Office Manager

Szymon Okoniewski
Business Analyst

Wojtek Amtmański
Data Science Specialist

Piotr Przymus, PhD
AI Advisor

Alina Baranowska
Junior Data Scientist

Arkadiusz
Sycz
ML Engineer Lead

Marta Osińska
Junior ML
Engineer

Aleksandra Kaczmarska
Junior Data Scientist

Michał Bruzdowski
Lead Programmer

Dawid Cieślewicz
Mid Software Developer

Bartek Bruzdowski
Databases specialist

Paulina Jasińska
Database interface

Medicine
Beata Ufnal
Head of Medical Partnerships

Sara Zawadzka-Leska, MD
Medical expert

Publications, R&D
Michał Dąbrowski, PhD
R&D Publications

Michał Kloska
R&D Publications

Anna Kloska
Junior Data Scientist

Adam Bielniak
Mid ML
Engineer

Agnieszka Sowa-Latos
Medical Partner Consultant

Emilia Krupiczojć
Medical Content Creator

Magdalena Fijałkowska
Medical Content Creator

Joanna StankiewiczMD
Medical expert

Marcin Rymko, MD, PhD
Medical expert

IMPLEMENTATION
SARAH PLATFORM FOR MEDICAL PROVIDERS
-
SARAH Platform with AI-driven algorithms is implemented in medical clinics.
-
Integration with existing database (pre-defined tables' format).







Signing an agreement with a medical clinic, team organization
Preparation of datasets locally by the clinic (pre-defined tables)
Workshops with clinics' physicians to re-train NLP algorithms
Algorithms' implementation locally based on data fully anonymised
Organization of diagnostic process of selected patients
Provision of reports with statistics & efficacy of the algorithms
3-6 weeks
SARAH VIRTUAL CLINIC PLATFORM FOR INDIVIDUAL PATIENTS

-
Online platform for: (i) patients actively looking for a diagnosis that can upload medical data, and (ii) RD specialists (medical council) to analyse it and refer patients to the appropriate specialist / clinic.
-
Foundation's website is promoted in online & offline media.






Patient actively looks for help (e.g. specialist) and finds the Foundation
Online platform allows to fill-in questionare & attach medical data
Co-ordinator verifies data completeness, may ask for extra data
Algorithms analyze data and indicate the most likely rare disease
Patient referred to the specialist to continue the process
Provision of reports with statistics & efficacy of the algorithms
6-8 weeks
OUR PARTNERS


Pharmaceutical / biotechnology industry


Not all disclosed due to confidentiality reasons
Medical services providers
Foundations & Patients' associations









NEWS

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