Apposite Capital LLP

Sam Gray

Much is written in the mainstream press about the well-established trend towards personalised medicine. Scientific advances in fields such as genomics, epigenetics, proteomics and companion diagnostics increasingly enable precise characterisation of a patient and their disease; and drawing on sophisticated clinical trials and real-world data sets an optimal personalised drug or biologic therapy options can then be selected–possibly guided by AI decision support algorithms.

Despite all the (justified) hype and investment in these pharmaceutical and biologic technologies, in the majority of clinical practice, physical interventions such as surgery remain by far the most important treatment modality. Even in cancer treatment, surgery and radiation-based treatments still account for the vast majority of cancer cures and this is expected to remain the case for the foreseeable future.

However, by their very nature physical interventions such as surgery and anatomical characteristics of disease are more difficult to precisely characterise and define than genetic or biochemical markers. This makes it more difficult to precisely specify and control interventions, measure and map the outcomes and precisely establish best practices. There is also a much larger human element in the treatment pathway from the radiologist interpreting images to the surgeon performing the procedure. This leads to more subjectivity, more variation and inevitably also more human error.

Whilst the very best hospitals and physicians in the world can and do consistently deliver world-leading treatment; across hospital systems, even within departments and certainly internationally there is an urgent requirement to “raise the floor” such that less qualified or experienced practitioners can better learn and adopt best practices, whilst hospitals and payers can reduce and monitor variation in practice and performance ensuring fewer poor patient outcomes.

This is the reason we are seeing growing investor interest in fields that help address this area such as precision imaging and AI diagnostics, image-guided procedures, robotic surgery, and smart OR and Critical Care solutions providing intelligent, automated, real time interventions and workflows.

For example, this year Caresyntax raised $100m to advance their platform which uses proprietary software and AI to analyze large volumes of data in and around the OR to improve patient outcomes. AIDoc just raised $66 m to advance its vision of truly intelligent, data-driven hospital workflow in the diagnostic radiology sector.

However, there is equally an urgent need to “bridge the gap” that exists between diagnostic imaging and downstream physical interventions. These are currently often carried out at a different time by a different clinician - with much of the rich dataset captured by precision imaging “lost” in the summarized format of a traditional radiology report. In the future there will need to be not only increasing use of technologies such as precision imaging and real-time image guided procedures, but also intelligent and joined up workflows, AI treatment guidance and decision support, and critically, the curation and characterization of the physical imaging and radiomics data which is essential in order to map physical disease and treatment approach to outcomes.

An exemplar of this future approach is Mirada Medical. Mirada is an oncology treatment guidance company that bridges the gap between precision diagnosis and personalized, real-time treatment guidance. Mirada’s vendor-neutral technologies enable a deep characterization of the patient and disease through precision imaging to flow seamlessly into the development and delivery of a treatment plan and associated workflows.

For example, Mirada supplies the software that supports Therasphere, Boston Scientific’s radioactive microspheres for the treatment of liver cancer. Mirada’s Simplicity software uses patient specific images todevelop a personalised dose plan and workflows. A 2021 publication* showed that compared with standard dosimetry, Mirada’s personalised dosimetry significantly improved the objective response rate in patients with locally advanced hepatocellular carcinoma.

“Even in cancer treatment, surgery and radiation-based treatments still account for the vast majority of cancer cures and this is expected to remain the case for the foreseeable future.”

Mirada also works with leading global hospitals to support the delivery of a more precise and standardised approach to radiation oncology. Its AI based solutions allow best practices in radiation treatment planning to be standardised and shared across an organisation with significant benefits in terms of workflows, workforce efficiency and timesaving as well as reducing variation in clinical practice across care organisations. As radiation treatments become more sophisticated with a choice of modalities and a trend towards delivering fewer but higher dose treatments, precise real-time imaging, personalized adaptive planning and process control become ever more essential as does the curation of data linked to real world patient outcomes.

The benefits of using precision imaging, AI systems curated and validated to support delivery of the highest standards of care and workflows to standardize control and analyze interventions in this way are enormous across all participants in the system. Patients can be confident that they are receiving the intended treatment and benefiting from established best practices, doctors and clinicians can eliminate time consuming steps from their practice helping with burn out and staffing shortages but also with training and monitoring of junior team members - this is particularly important in emerging economies where the skills shortage is even more acute. Hospitals and payers can improve clinical governance and lower their risk, ensuring that high standards are maintained across a network or department irrespective of varied clinical skillsets.