Turning oncology data into action: A cloud-first leap toward smarter care and faster research with AI

Where better data leads to better decisions — across care, research and strategy

What sparked the need for change?

Oncology teams had the data but not the full picture. Insights were buried in siloed systems and slowed by manual processes. Even after modernizing their platforms, critical data points — from pathology reports and biomarker results to treatment histories and social determinants of health — remained scattered in unstructured notes, making timely analysis nearly impossible. Without that foundation, the teams couldn’t create reliable data tools, speed up research or give doctors the insights they needed to personalize care — slowing progress for both providers and patients.

What solution did the teams unlock by working together?

Together, PwC and the client built a scalable, AI-ready data foundation on Google Cloud. Using PwC’s cloud solution— a prebuilt set of data pipelines, frameworks and tools designed to speed deployment — the teams streamlined how oncology data was brought in, cleaned, organized and made usable. That included everything from lab results and treatment patterns to clinical notes, all made easily searchable for teams across the organization.

The result: a clearer view across health records, claims and third-party data, helping drive faster research, smarter care decisions and real-world evidence generation. Providers can now spend less time chasing down information and more time with patients. Patients experience faster trial matching, more tailored treatment options and their physicians get quicker access to insights that could shape enhanced care. And behind it all, built-in tools monitored data quality, turning complex unstructured data into trusted, usable insights.

Where did tech innovation meet human ingenuity?

PwC brought together healthcare specialists and engineers to focus on a common goal: turning complex oncology data into practical tools. The team used AI to do things that would be impossible to scale manually — like scanning through patient histories to flag those who might qualify for clinical trials, or spotting patterns in treatment outcomes to help personalize care. AI also helped convert unstructured data into structured formats that could be analyzed and acted on. Google Cloud Vertex AI powered the predictive models, while Google Cloud Looker — a cloud-based analytics tool — turned those insights into easy-to-use dashboards for doctors and analysts.

But it wasn’t just the technology; it was the day-to-day teamwork between client clinicians, data specialists and PwC strategists that made the difference. They met regularly to review real data, adjust models based on provider feedback and align the tools with the realities of frontline care. Together, they didn’t just build smart tools. They built tools that fit naturally into the way people work.

What was the real-world impact of approaching things differently?

Business and clinical teams came together to rethink how oncology data could tangibly improve care, not just sit in reports. That pivot — from building infrastructure to creating tools that solve real problems — unlocked faster care decisions and accelerated research. Today, care teams can identify patients who may benefit from more affordable treatments — or who need extra assistance to stay on track with their care plan — without compromising outcomes. Researchers can now identify more targeted trial groups faster. And the data backbone? It’s built to safely share privacy-protected health insights with life sciences partners and fuel new treatments and studies with projected value exceeding $50 million annually.