Landmark study demonstrates economic edge of precision medicine that we can’t afford to ignore.

Experts begin to unlock the commercial potential of precision medicine with the first ever side by side economic analysis

Landmark study demonstrates that precision oncology medicines could deliver a superior Return On Investment (ROI) for Pharma R&D vs their one size fits all counterparts but warns that more work needs to be done to fully unlock the commercial potential of precision medicine  

 A landmark study, titled "Delivering the precision oncology paradigm -reduced R&D costs and greater return on investment through a companion diagnostic informed precision oncology medicines approach," published in the peer-reviewed Journal of Pharmaceutical Policy and Practice, examines the economic impact of precision medicine oncology medicines compared to traditional oncology medicines and reveals compelling evidence of substantial cost benefits associated with precision medicine. 

This study, which was conducted by a team of precision healthcare economists and researchers, is the world’s first and most comprehensive study of the initial wave of precision oncology medicines in the marketplace. The results of the study strongly advocate that the industry should revisit the commercial model for precision medicines and their associated diagnostic/prognostic tests. 

Professor Mark Lawler, Professor of Digital Health at Queen’s University Belfast, co-lead of Health Data Research UK’s Big Data For Complex Disease Research Driver Programme and senior author on the paper notes: 

“This is a landmark study that highlights how precision medicine can deliver affordable care for cancer patients. Moving towards a precision oncology Companion Diagnostic (CDx) guided approach can deliver health benefits at a potentially affordable cost, including in the development phase, lowering expensive clinical trial attrition rates and sparing patients from those treatments that are ineffective and may have significant side effects. If we don’t deploy a CDx guided approach we are missing a huge opportunity to deliver the best, most affordable care to our patients.” 

Drug development is a major contributor to health costs – the average cost of getting a new oncology medicine into the market is estimated at US$4.4 billion. The study demonstrates that it costs over $1billion more in R&D spend to develop an oncology medicine that is not guided through clinical trials with a companion diagnostic (CDx), compared to a precision oncology approach. Thus, CDx-guided precision oncology approaches offer better value to the key stakeholders; payers, patients and the pharmaceutical industry. 

Professor Richard Sullivan, Director, Institute of Cancer Policy, Co-Director of the Centre for Conflict & Health Research, and a co-author on the paper emphasises the significance of precision medicine's economic impact: 

“This study has been a vital piece of research to shine a light on the economics of precision medicine as it represents the future. Already we can see significant R&D cost savings in this study and the potential to reach even more patients when that investment saving is directed to better testing and greater cost benefit to health systems.” 

Dr Raymond Henderson, Senior Health Technology Assessment Manager at Salutem Insights Ltd and lead author on the paper, said: 

“This study emphasises how a precise health economic approach can provide the evidence base to underpin the delivery of precision oncology for patients.” 

Historically, traditional oncology medicines have generated $3bn more revenue than precision medicines, however, the key reason for this difference was highlighted in a study carried out last year by Diaceutics and published in the Journal Clinical Oncology (JCO), which emphasised the clinical practice gaps in CDx testing. The study, found that nearly 64% of lung cancer patients did not receive access to the most effective precision medicines for them and their cancer type as a result of sub-optimal testing, and so the authors note that the precision medicine revenues are significantly constrained because of inefficiencies in the diagnostic pathway, resulting in less than 50% of eligible patients getting access.  

The precision medicine approach should allow pharmaceutical companies to adopt new business models that not only empower reinvestment in robust tumour testing to help serve the 64% of lung cancer patients not currently treated with a precision oncology approach, but also to ensure equity-based pricing systems, as well as developing precision oncology medicines that deliver significant, clinically meaningful benefit. 

Peter Keeling, CEO of Diaceutics and co-author of the study, highlights the importance of these findings for the Pharma Industry: 

“Utilising this same base line landmark financial analysis, we can for the first time postulate what might be the actual lifecycle dollar advantage of recovering patients lost to the diagnostic pathway with an investment in better testing.” 

This study hypothesises (based on evidence of commercial impact and previous published analysis) that a $50m timely investment in better testing would potentially gain significant lifecycle revenues per therapy; for every $1m invested in better testing could result in additional $100m+ in additional lifecycle revenues for that therapy. 

However, despite the mounting evidence that precision oncology approaches appear to offer better value to the key stakeholders; payers, patients and the pharmaceutical industry, there are still barriers to be overcome that require a new operating model which enables these cost effective treatments to reach all the target patients.

This work was supported by a grant from Health Data Research UK (HDR UK) and funding from the Queen’s University Belfast Foundation.

Paper can be viewed at:
https://link.springer.com/epdf/10.1186/s40545-023-00590-9?sharing_token=12LzrrKpMTu9CJtahavM-2_BpE1tBhCbnbw3BuzI2RP6aQrW1D3wgOMFVUaqkh3C1xU4bq2Rvb3qnPF3cqYhPUlYa-pviECyvXnNlj0qF7u7_berXpR80hWkaZ9mbsCVtGTW3Bk106KEGgJAxd-UyR5cYDGp7IGRJsFrJlrjH9g=

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