The Radiation Planning Assistant (RPA) – a Web-based AI-powered platform developed at the University of Texas MD Anderson Cancer Centre (MDACC), in the US, has seen clinical integration at the Universitas Academic Hospital, in Bloemfontein, South Africa.

This is the first clinical site outside the US to integrate this AI-powered platform into cancer treatment planning. University of the Free State (UFS) Department of Medical Physics and the Department of Oncology, together with Universitas Academic Hospital, are conducting this initiative to help in the creation of radiotherapy treatment plans, the university says.

UFS Department of Medical Physics deputy manager and senior lecturer Dr William Shaw has built a long-standing academic partnership with MDACC Department of Radiation Physics Radiation Oncology division Professor Laurence Court and his team at the MDACC and this collaboration is now yielding transformative results.

The RPA was initially implemented at Universitas Hospital for the treatment of cervical cancer, which represents the largest proportion of patients receiving radiotherapy at the institution.

However, it has since been applied and tested for other types of cancer across a broader range of clinical indications, including breast, head and neck cancers, as well as primary brain tumours.

“With ongoing institutional input, including from the teams at Universitas Hospital and the UFS, the system holds significant promise for broader application across nearly all major tumour types treated with external beam radiotherapy,” says Shaw.

The RPA has been designed to support clinical teams in both high- and low-resource settings, and helps streamline one of the most time-consuming steps in cancer care, namely the formulation of patient-specific radiation treatment plans.

The RPA is a cloud-based software platform designed to support radiotherapy services by automating key components of the treatment planning process. It enables the consistent production of high-quality radiotherapy plans while reducing the demand on highly specialised clinical staff.

The process starts with the acquisition of a planning computed tomography (CT) scan, which serves as the sole imaging input to the RPA. Once the CT dataset has been captured, it is uploaded to the RPA platform via a secure Web interface. The user then completes a short digital form, providing basic administrative details and selecting the treatment site, he says.

No additional imaging modalities are required, but important information on treatment plan specifications detailing the individual patients’ characteristics are specified by specialised clinical staff, Shaw says.

After this process, the RPA uses advanced machine learning algorithms to automatically identify and delineate both tumour volumes and critical normal tissues, or organs-at-risk.

The system automatically generates a full radiotherapy treatment plan after completing the contouring process.

“Our aim is to use AI as a tool to standardise, scale and improve cancer care in places where the need is greatest.”

The RPA enhances the quality, consistency and timeliness of cancer treatment in radiotherapy settings, particularly in environments where clinical capacity is limited, by automating the most labour-intensive components of the treatment planning process, says Shaw.

“These benefits translate into improved tumour control, fewer complications and a more efficient and responsive treatment experience for patients across a range of clinical settings.”

The impact is immediate and meaningful for cancer patients as the technology enables faster access to well-constructed, evidence-based treatment plans that are reviewed and refined by experts.

This translates to more timely care, fewer unplanned treatment interruptions and improved protection of normal tissues, thereby resulting in fewer side effects and better overall outcomes, he notes.

Further, by providing standardised treatment plans, the platform has the potential to reduce inter-institutional variability, helping to establish consistent radiotherapy protocols across clinical trials.

This consistency is critical for reliable multi-centre research and paves the way for improved global benchmarking in cancer care, Shaw says.

Encouraged by these successes, the UFS Department of Oncology, under Professor Alicia Sherriff, has joined the initiative as an active clinical partner. This multi-disciplinary collaboration has laid the foundation for further research and innovation at the interface of medical physics, oncology and data science.

Meanwhile, Court has also extended access to the RPA to other radiotherapy centres in South Africa, with expansion to other countries planned for the near future. This decision was informed in part by the positive outcomes and implementation expertise of the Bloemfontein teams, Shaw highlights.

“The introduction and clinical integration of the RPA represents a major advancement for oncology services regionally and nationally. It signifies the transition from research collaboration to real-world application, where artificial intelligence is being used to improve access to safe, high-quality cancer care.

“The early clinical implementation of the technology includes the treatment of nearly 50 patients to date,” says Shaw.

This is a significant advancement for cancer care in South Africa. This technology not only improves efficiency and access, but also raises the standard of care for cancer patients across the province and beyond.

Additionally, Shaw’s team has played a central role in developing safe, reliable clinical processes to integrate AI tools like the RPA into daily practice, thereby ensuring that automation enhances, rather than replaces, professional expertise.

The experience gained through this implementation provides a foundation for the safe, phased rollout of similar systems in other provinces, he adds.

Meanwhile, cancer incidences are rising across low- and middle-income countries, and the innovation offers a compelling model for how academic medical centres can respond with agility, scientific rigour and global solidarity.

It demonstrates how international partnerships can bring cutting-edge technologies to the frontlines of healthcare, and make them work, in real clinics, for real patients, says Shaw.

“The future we are heading towards is one where human innovation and digital technologies work together to elevate the standard of care, rather than replace humanity in medicine,” says UFS deputy vice-chancellor for research and internationalisation Professor Vasu Reddy.

Separately, and in addition to their work in external beam radiotherapy, the UFS and Universitas teams are also advancing the use of interstitial brachytherapy for cervical cancer.

While not the first globally to implement this specialised technique, the Bloemfontein team is among the earliest adopters on the African continent, which is helping to expand access to this advanced modality in settings where it is most needed.

The team is now focused on optimising the integration of external beam radiotherapy and brachytherapy, which is a well-established combination in the treatment of cervical cancer, to enhance treatment outcomes and adapt protocols to meet local clinical realities more effectively, Shaw notes.

The RPA work was supported by the Nuclear Technologies in Medicine and the Biosciences Initiative, which is a national technology platform that was developed and is managed by the South African Nuclear Energy Corporation and funded by the Technology Innovation Agency.