The harder the problem, the stronger the solution
An approach proves its true value not when problems are simple, but when complexity and uncertainty take center stage. That is why, at 811, we deliberately chose to start with rare diseases.
Why we started with the hardest problem
Rare diseases are among medicine’s most complex challenges, where meaningful signals are scattered across time, specialties, and data sources. For us, this complexity is not just a challenge, it is a test. What we learn here can unlock solutions for broader challenges across the life sciences.
Why rare disease?
In rare diseases, clues to a diagnosis may emerge early in a patient’s journey. Yet when scattered across time and specialties, these clues can be difficult to connect into a meaningful pattern. The result can be years before the right diagnosis is reached.
- Findings are scattered, and lost across specialties.
- Repeated and unnecessary tests follow.
- Diagnoses are missed or delayed.
- Treatment and care are delayed.
This journey burdens patients, families, healthcare systems, and researchers alike. We see more than a diagnostic challenge. We see a challenge of connecting scattered clinical signals across time and data—so the right patterns can emerge when they matter.
The scale of the problem
- 1 in 4
- 01
Patients consult eight or more physicians before the right diagnosis
- ~60%
- 02
receive at least one incorrect diagnosis before diagnosis
- ~5 years
- 03
Average time to diagnosis is 5 to 8 years in Türkiye, up to 10.4 years in adolescents
- 5 million+
- 04
People affected in Türkiye alone is roughly 1 in every 16 people
- EURORDIS Rare Barometer, 2024 — European Journal of Human Genetics (13,300+ patients, 104 countries)
- Turkish Neurological Society — Rare Disease Day, 2026
- AIFD & IQVIA — Türkiye Pharmaceutical Sector Report, 2025
Worldwide, more than 300 million people live with a rare disease.
Sources
What are we working on today?
We are developing predictive models that evaluate together the findings in existing clinical data that carry no meaning on their own, so as to contribute to earlier risk assessment.
Our aim is not to replace diagnosis. Our aim is to support the right patient being referred to the right specialist earlier.
We intend to validate this approach scientifically by evaluating it against retrospective, real clinical data. Every new study is a step taken not only to develop a model, but to show that invisible signals can be understood earlier.
- Progressing
- Predictive research models that evaluate combinations of clinical findings for risk prioritisation and earlier specialist referral. Validation against real clinical data is underway.
- Active research
- Structured research workflows relating phenotype patterns to fragmented evidence across separate records.
- Hypothesis
- Earlier visibility may help teams decide which questions to investigate first. This is an open research question, not a demonstrated outcome.
Our models are research and decision-support tools. They organise relevant evidence for the people responsible for interpreting it; they do not diagnose, treat, or replace scientific and clinical judgement.
Our first proof is not our final goal
Rare disease is not a destination for us; it is the first proof of our approach. We believe the way of thinking we develop here can turn into new applications in human health, in animal health, in plant sciences and in many other areas of the life sciences. Diseases may change. Technologies may change. Only one need does not: being able to understand problems before they grow.
We are starting with rare disease today. Tomorrow we aim to contribute to the other invisible problems of the life sciences with the same approach.