Building on the operational foundation announced earlier this spring, and adapting our work to the current realities, OncoHelper AI is now strengthening its role as an international oncology project office.
In April and May, we shifted our focus toward grant development, project structuring, financial planning, and preparing oncology initiatives for competitive funding review. During this period, we submitted new grant applications, and they are now under review. We expect further information during the next review cycle.
At the same time, we continue to develop our own research initiatives and support international scientific and clinical teams in shaping strong, realistic, and fundable oncology projects.
Building the Foundation Behind Our WorkOur core projects remain the same. They are still central to our mission.
But strong projects need a strong foundation behind them.Like many early-stage nonprofits, we have been carrying much of this work through volunteer effort. We now need a stronger operational base for coordination, applications, reporting, communication, and project support.
That is why we have added a new project to our site: Building the Operational Foundation Behind Every Project.
This effort supports all of our other work.
We have completed the core specification of Interceptor v0, defining the internal structure of the system at the current stage of development.
Interceptor is being developed as a dynamic state model of a pediatric cancer patient. The system represents the patient as an evolving process described by a structured state vector and governed by mode-dependent dynamics.
The current specification introduces three key components:
First, a 10-component state vector that captures both tumor-related processes and the child’s physiological condition. This allows the model to track tumor progression and host response within a unified framework.
Second, a mode-switching structure that separates baseline periods, active treatment phases, and recovery intervals. Each mode is associated with different system dynamics, reflecting real clinical conditions.
Third, a strict separation between observations and interventions. Measured data (laboratory values, imaging-derived features, clinical events) are treated independently from clinical actions (therapy, procedures, supportive care),ensuring a consistent and interpretable modeling approach.
A key design principle of Interceptor is the joint modeling of tumor dynamics and host physiology. The system integrates both domains into a single evolving representation.
The goal of this specification is to establish a controlled, testable framework that can be incrementally expanded and validated.
To make our work more visible and easier to follow, the personal Facebook profile of our founder, Sergei Oleshkevich, has now been opened to the public and set to Professional Mode. In addition to updates on our website, we will now also share selected project news, milestones, and progress updates on Facebook. This gives supporters and interested readers another simple way to follow the development of OncoHelper AI and our work in pediatric oncology.
In the four months since receiving official U.S. nonprofit status, OncoHelper AI has moved from formation into execution. Research teams are now in place for our three core programs, and work is underway: our AI platform, the zinc plus iron platform, and our PARP inhibitor program. We have reached the point where small early contributions unlock real momentum.
If you support better outcomes in pediatric oncology, your donation helps us keep the work moving forward.
