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Improve diagnosis and develop a more personalized treatment approach thanks to Radiomics

The Alcimed healthcare team is continuously supporting healthcare players to get understanding of future technologies that will impact the cancer care pathway. One of these technologies is radiomics. We here explore questions around quality of life, earlier and better diagnosis, the prediction of treatment options and their success as well as the development of new biomarkers.

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radiomics consulting firm experts specialistsTHE Challenges related to Radiomics

  • What is radiomics and what can it be used for?

Radiomics is a field of medical imaging that uses advanced mathematical algorithms to extract quantitative features from medical images such as computed tomography (CT), magnetic resonance (MR), or positron emission tomography (PET) images. The extracted data can then be analyzed to identify or model patterns and features that may not be visible to the human eye.

Radiomics can develop a predictive clinical model for diagnosis, treatment planning, and patient outcomes based on these quantitative features. Medical imaging data can also be used to identify new biomarkers for disease and to better understand the underlying biology of a cancer and other diseases, hence enabling personalized treatment approaches. It can be used in patients segmentation for clinical trials or treatment options or can be used as companion diagnostics too.

Radiomic is a rapidly growing field that has the potential to transform the field of medical imaging in many fields. Radiomics in oncology can provide a more personalized approach to diagnosis and treatment planning. However, the field is still in its early stages and much research is needed to fully understand its potential and limitations.

  • What are current and future issues in further developing radiomics in oncology?

Overall, radiomic has the potential to transform the pharmaceutical industry by providing new insights into disease biology and enabling the development of more targeted and personalized therapies. Artificial intelligence, deep learning or machine learning algorithms are based on medical images and are developed to detect the smallest incoherences in abnormal tumor cells. Which in turn allows not only for the clinical development of new biomarkers or drugs, but also enables better patient segmentation into clinical trials, or choose the correct treatment predicting success. Yet the technology is still an early one and we see several roadblocks ahead at least in complex diagnostic environments with high data variability. Some of these roadblocks can link to concerns regarding data sharing, the (often) heterogeneity of available features to develop and then integrate tools into practice and to make it applicable for all patients. In the same line a lack of multi-centric trials could negatively impact on reimbursement options later on.

Often radiomics development is based only on a very specific and small patient segmentation with a very distinct disease pattern in order not to overwhelm the algorithm and allow to develop the radiomic tool in due time. The issue with this is that only small patient populations then benefit from radiomics and applying it to more patients would require novel developments.

How can we develop radiomic tools that allow a broader utilization across indications? How can we identify cross-disease patterns?
Radiomics requires high-quality medical imaging feature, which may not always be available or of sufficient quality, for example being truncated. Reproducibility also is a major concern in radiomics, as there may be variability in the way feature is collected, processed, and analyzed. This often results in a lengthy process to develop radiomics for some indications like cancer where treatment choice is crucial and often difficult to take.

How can we ensure high quality real world medical imaging data as a base for radiomics development? What are the key success factors of a shared and collaborative health data lake?
There is currently no standardization of radiomics methods, which can lead to variability in results between different studies and institutions. Efforts are underway to develop standardized protocols for radiomic analysis. Often only small-scale studies are organized that can make it difficult to draw conclusions. Until this situation improves companies face the issue of less good reimbursement options in case of missing multi centered clinical trials.

How can we ensure high reimbursement of our radiomic tools? What are the alternative funding options for radiomics?

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Radiomic is quite a new topic in healthcare, and we have seen new questions around radiomics for 5 years, in Oncology and outside Oncology. Interestingly, the field is simultaneously explored by public institutions, big pharmas, and some biotechs from healthtech. Our proximity and projects with all these players allow us to stay at the top-edge of the current developments, and to have a global and in-depth understanding of the issues addressed in the field of radiomic.

Our projects cover topics as diverse as new technologies, preparation of new clinical developments, the understanding of disease management and patients care pathways, identifying and studying potential partners to develop solutions around radiomics, launches of new assets, or the understanding of how real-life data can be collected and analyzed as well as to understand how patients data can be used to develop personalized cancer treatment offers.

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One of our clients, a leader in the medical device industry, was searching for a competent partner in programming artificial intelligence applications for digital pathology, with the objective of extending its product offering. To do so, our team conducted a global scouting of innovative AI providers, with an analysis in terms of technological maturity, business maturity and their network strength. Based on our study, a selection of prioritized providers was approached to explore opportunities for collaboration with our client.
We supported one of our clients, a leader in the healthcare sector, who wanted to explore the opportunity to diversify its activities through the integration and use of digital solutions for the generation and collection of medical imaging data. For this study, our teams evaluated the different data capture technologies available on the market and conducted an analysis of their features, their advantages and their limits, as well as the existing approaches for their use in several countries. Following our analysis, we defined 4 approaches enabling our client to integrate and to set up these new selected digital data services and established an operational action plan to carry out pilot projects. In the end, the pilot was successful and our client was able to launch a new differentiating offer.
Alcimed supported a top pharma player in defining the strategy of a new radiomic tool specifically targeting rare cancer diagnosis. We helped our client to understand the current diagnosis pathways in addition to needs and challenges linked to it, identified trends in the indication, and aimed to understand how these trends and underlying future technologies will impact the current pathway and shape it in the future. We then conducted an analysis of the key features and expected level of proof to ensure a successful launch. Our study allowed our client to optimally design the last development stages of the tool and prepare for its launch.

Founded in 1993, Alcimed is an innovation and new business consulting firm, specializing in innovation driven sectors: life sciences (healthcare, biotech, agrifood), energy, environment, mobility, chemicals, materials, cosmetics, aeronautics, space and defence.

Our purpose? Helping both private and public decision-makers explore and develop their uncharted territories: new technologies, new offers, new geographies, possible futures, and new ways to innovate.

Located across eight offices around the world (France, Europe, Singapore and the United States), our team is made up of 220 highly-qualified, multicultural and passionate explorers, with a blended science/technology and business culture.

Our dream? To build a team of 1,000 explorers, to design tomorrow's world hand in hand with our clients.


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