Bench to bedside problem-solving

We use a Community of Practice (CoP) approach to problem-solve healthcare challenges.

We engage our network of clinicians, patients, academics, and policy makers to absorb constant feedback from the public. Meeting regularly online and face-to-face, this ecosystem evaluates our flagship research to ensure optimal translation of CHAI innovation towards clinical outcomes.

Scroll down to see what we are currently discussing.

Dementia risk factor discovery

Problem

Loosing cognitive function like thinking, remembering, and reasoning are symptoms of the complex disease – dementia.

Currently, AI models rely on simple models based on linear relationships. This overlooks the diseases’ underlying complexity.

Solution

Causal AI can analyse large, detailed brain imaging scans and electronic health records to understand how different factors like cerebrovascular disease, stroke, and other health issues work together to increase dementia risk.

This CoP launched in May 2025 with initial discussions on the challenges of leveraging large-scale data within neurodegenerative diseases. These discussions will continue via our online Slack collaboration space and through future events.

Cancer diagnosis, treatment & prevention

Problem

Cancer is not a one-size-fits-all disease. Each case can involve different causes, risk factors, and treatment responses.

We need more than just pattern recognition to understand what truly drives cancer. Especially with inconsistent data standards across hospitals.

Solution

Causal AI digs deeper into cancer’s mechanisms to improve screening accuracy and reliability, evaluate multi-step treatment plans, and to understand how to intervene earlier and more effectively.

This CoP is partnered with CRUK Scotland and will be launching in September 2025 with further in-person workshops in November 2025.

Supporting better guidelines for patients with multiple long-term conditions and polypharmacy

Problem

Many patients live with several long-term health conditions and take multiple medications (polypharmacy).

Clinical trials study samples of the global population which often don’t represent the wide variety of everyday people. They rely on general observational data which is not personalised.

Solution

Causal AI assesses the true benefits and risks of treatment across diverse real-world population data by shifting from a disease-focused approach to one that’s patient centred.

This CoP will be launching in October 2025.

We will be collaborating with guideline developers like NICE and SIGN, and regulators including MHRA and the European Medicines Agency to create new standards of evidence that work across different populations, treatments, and healthcare settings.