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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)

global world map
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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

Rar diseases

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

Featured

OUR TEAM

Global

szymon piatkowski

Szymon
Piątkowski

CEO/Founder

grzegorz basak
joanna jarmoc

Prof.
Grzegorz
Basak

CMO/Founder

Joanna Jarmoc
Business Development

Poland/CEE

karol lis

Karol Lis, MD
General Manager/Founder

marek dudzinski
adrian michalski

Marek Dudziński, MD, PhD
Medical Director/Founder

Adrian Michalski Technology Director

Brazil

henrique malina

Henrique Malina 
General Manager

Business & Operations

Germany

maciek klein

Maciek Klein 
General Manager

AI / Data Science

US/Canada

szymon piatkowski

Szymon Piątkowski
Interim

IT / Programming

Maciej Majewski

Bloodlab Product Lead

Maciej Majewski

Karolina Popławska

HR Manager

Karolina Poplawska

Mateusz Firlej

Business Analyst

Mateusz Firlej

Marta Koryga

RD Virtual Clinic Product Lead

Marta Koryga

Dominika Materka

Office Manager

Dominika Materka

Szymon Okoniewski

Business Analyst

Szymon Okoniewski

Wojtek Amtmański

Data Science Specialist

wojciech amtmanski

Piotr Przymus, PhD

AI Advisor

Piotr Przymus

Alina Baranowska

Junior Data Scientist

Alina Baranowska

Arkadiusz

Sycz

ML Engineer Lead

arkadiusz sycz

Marta Osińska

Junior ML

Engineer

Marta Osińska

Aleksandra Kaczmarska

Junior Data Scientist

Aleksandra Kaczmarska

Michał Bruzdowski

Lead Programmer

michal bruzdowski

Dawid Cieślewicz

Mid Software Developer

Dawid Cieślewicz

Bartek Bruzdowski

Databases specialist

Bartłomiej Bruzdowski

Paulina Jasińska

Database interface

Paulina Jasinska

Medicine

Beata Ufnal

Head of Medical Partnerships

Beata Ufnal

Sara Zawadzka-Leska, MD

Medical expert

Sara Zawadzka Leska

Publications, R&D 

Michał Dąbrowski, PhD

R&D Publications 

Michał Dąbrowski

Michał Kloska

R&D Publications

Michał Kloska

Anna Kloska

Junior Data Scientist

Anna Kloska

Adam Bielniak

Mid ML

Engineer

Adam Bielniak

Agnieszka Sowa-Latos

Medical Partner Consultant

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Emilia Krupiczojć

Medical Content Creator

Emilia Krupiczojć_edited.jpg

Magdalena Fijałkowska

Medical Content Creator

Magdalena Fijałkowska

Joanna StankiewiczMD

Medical expert

Joanna Stankiewicz

Marcin Rymko, MD, PhD

Medical expert

Marcin Rymko
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Contact

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).

sarah platform logo
icon medical papers
icon database
icon nlp
icon data anonymised
icon process of patients
icon statistics

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
saventic foundation logo
  • 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.

icon patients
icon online platform
icon coordinator
icon algorithms analyze data
icon patient reffered
icon provision of reports

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

Partners

OUR PARTNERS

eusapharma logo
recordati logo
Pharmaceutical / biotechnology industry
takeda logo
novartis logo

Not all disclosed due to confidentiality reasons

Medical services providers
Foundations & Patients' associations
plugandplay alberta logo
hotmilk logo
eit health logo
assiociation of families with fabry disease logo
biosaxony logo
Enterprise_Forum_logo_long_cee.abbrev
assiociation of families with gaucher disease logo
plugandplay cleveland logo
pucpr logo
Demo
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