Artificial Intelligence is creating an impact in many sectors and some of the most important areas it’s likely to contribute significantly are life sciences and health. It is already enabling and is likely to further accelerate drug discovery, better diagnostics, patient treatment and care amongst a host of other use cases within these sectors.

One therapeutic area which will immensely benefit from the application of AI is Oncology. In a recent paper published by British Journal of Cancer on Nature.com¹, the authors point out how AI and high-performance computing is already helping handle large amounts of data for multi-omics analyses and enabling new approaches to cancer detection, treatment and management. 

Over the last year, the Deloitte AI Institute has been collaborating with Arjuna Therapeutics, an emerging biotechnology company to build an AI-driven engine on Cloud for accelerating Biomarker (Drug target) discovery in Solid Cancers². As part of our initiate towards driving Precision Medicine for similar life sciences companies, we have been developing an integrated multi-omics infrastructure for running AI/ML pipelines on merged drug sensitivity, genetics, genomics and proteomics datasets; specifically, towards use-cases around Biomarker target discovery for various therapies including Nanomedicine. Many similar initiatives across the life sciences space show us that the applications of AI within Oncology are developing at perhaps a much faster rate than initially thought. 

As this trend becomes a concrete reality for the life sciences and health sectors, it is imperative for leaders and decision makers to have a good understanding of how AI can be applied in the context of oncology.

This brief dossier has been borne out of the above understanding and need and is our little attempt to shed light on how AI can be applied to this therapeutic area, provide some examples of technology providers and summarise key challenges to watch out for life sciences and health companies as they decide to utilize AI.

References

¹Artificial intelligence in oncology: current applications and future perspectives (nature.com)

²Cloud AI enabled analysis for cancer treatment development | Deloitte UK