New Diagnostics Generate Better Information
Better Information Creates Value
New targeted therapies have tremendous potential for the treatment of disease but often have serious side effects and high price tags.
Physicians now have advanced diagnostic tools to identify which patients are more likely to benefit and under what conditions, information that is essential for the efficient use of targeted therapies. These advanced diagnostics generate treatment-guiding information (TGI), and are a foundational element of Precision Medicine 3.0—the use of genomics, proteomics, metabolomics, and microbiomics in the patient journey.
By integrating our core capabilities—a deep understanding of advanced diagnostics and expert health economic analytical skills—we provide our biopharmaceutical clients with an understanding of the value of targeted therapies and a strategy to maximize that value through the use of TGI.
LET US SHOW YOU THE VALUE OF TGI
Using health economics analytic methods, we are able to calculate the benefit of a diagnostics strategy to our biopharmaceutical clients, quantifying the incremental value at the drug, franchise, or enterprise level
We consider value on both an individual patient basis and for a relevant population, a quantitative assessment that our client can use as a cornerstone of drug development and commercialization strategies.
We work with internal reimbursement and payment groups to demonstrate the increment of therapeutic price that can be attributed to an advanced diagnostic
Our analyses are particularly important to pharma companies considering an “at risk” pricing strategy
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WE CAN OPTIMIZE YOUR TGI STRATEGY
We identify all relevant diagnostics assays, algorithms, signatures, and images, whether or not commercially available, and assess the utility of each when used in combination with a specific therapeutic
We take a comprehensive view of the information generation process from the pre-analytical step (sample collection and preparation) through analysis and post-analytical data interpretation
We take a broad view of the potential utility of information, considering screening/selection, early detection/diagnosis, monitoring, prediction and prognosis
We assess the potential role of this information (biomarker/diagnostic) along the drug development continuum and, as appropriate, into routine clinical use
Our team will calculate the value of various diagnostic scenarios to facilitate selection of the optimal assay (information source) for use as part of the therapeutic regimen
Using a reverse engineering approach, we can determine the value-maximizing performance characteristics of the ideal diagnostic
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EXECUTION PLANNING OF A TGI STRATEGY
Conduct primary research with relevant stakeholders to identify issues likely to impact adoption of Dx/Rx combination
Map patient journeys to identify points of maximum impact for use of the diagnostic as part of patient management in combination with the therapeutic
It is well accepted that imaging, immunohistochemistry, and certain circulating markers are part of the routine work-up and management of patients receiving immuno-oncology drugs for their solid tumors. There is an emerging literature on the role of the microbiome in these patients and evidence that a favorable microbiome profile is associated with significantly improved progression-free survival. Given the high cost of therapy, the side effect profile, the limited response and the ultimate potential to modify a patient’s gut microbiome we examined the economic impact of including microbiome analysis into routine work-up of these patients.
Using a case study of metastatic melanoma, our work demonstrates that integration of microbiome analysis with treatment options for metastatic melanoma leads to cost-effective outcomes for patients. In fact, combining a microbiome analysis with treatment lowers long-term treatment costs and improves clinical effectiveness (i.e. QALYs) when compared to providing treatment blindly without knowing comprehensive details about the patient’s microbiome. This conclusion was deduced using an economic modeling approach, and was found to be robust across a range of assumptions and scenarios. Further, in the specific case of the information gleaned from microbiome analysis (the microbiome TGI) we note that, unlike is the case with other biomarkers, this can be optimized with relative ease (diet, probiotics, fecal transplants), further improving the therapeutic outcome.