**5. Acknowledgements**

The authors are indebted to our many colleagues at the Covance Genomics Laboratory (formally the Rosetta Gene Expression Laboratory) for years of dedication and collaboration. We also give thanks to our clients, who have continued to challenge the norm and helped us develop new and novel approaches for biomarker development.

### **6. References**


Technology has finally caught up with science fiction. The idea of a pin prick to divine ones' future is fast becoming a reality. Science is moving medicine in a direction where patient care will be predicted and prevented, and not watched from afar. Data-rich and highly sensitive techniques like microarray profiling, quantitative PCR, and Next Generation Sequencing are the genomics tools that are helping to drive these changes. However, to extract the greatest utility, tests need to be simple to complete, cost effective and as noninvasive as possible. Clinical impact is directly related to the availability and cost of a test. Consider the case of standard tumor biopsy. Depending on the disease and tumor location, a biopsy can be minor surgery involving a team of doctors, nurses, radiologists, and specialists. Recovery from a biopsy is often brief, but in some cases can lead to a costly overnight hospital stay. In the end, the actual cost of obtaining material for a test can be in the thousands of dollars, while the test itself, may only be a couple of hundred of dollars. For many biomarkers, there is more cost associated with the acquisition of sample, than the test itself. It is for this reason it makes both clinical and financial sense to find ways to make

By studying often overlooked sample types, we may identify a treasure trove of clinically useful biomarkers. While not every surrogate tissue will yield a disease or response-specific biomarker, there is substantial data to justify the investigation. There is undeniable value in the use of biomarkers in drug development and patient care, but this value is tempered with the cost of sample acquisition. Developing methods for the acquisition of clinically useful and easily obtainable samples is important as we move from a drug discovery process that

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**14** 

*1Denmark 2Norway* 

**Computer Simulation Model** 

**Patients by Use of Serial Serum** 

**Concentrations of Biomarkers** 

**in the Follow-Up After Surgical** 

**– A Computer Simulation Model** 

**Breast Cancer Biomarker TPA** 

*Section for General Practice, University of Bergen, Bergen,* 

**System Based on the** 

Flemming Lund1, György Sölétormos1,

 **Procedures and Other Treatments** 

Merete Frejstrup Pedersen1 and Per Hyltoft Petersen1,2

*1Department of Clinical Biochemistry, Hillerød Hospital, University of Copenhagen,* 

Concentrations of biomarkers for cancers (tumour markers) in plasma vary over time, and the ideal biomarker is a component which reflects the size of the tumour. Optimal interpretation of serial data on biomarkers during monitoring of patients following treatment of malignant disease is therefore vital for early prediction of reappearance of the tumour or metastases. Consequently, an ideal tumour biomarker will signal such reappearance before being detected by other relevant methods. On the other hand any false positive signals which can lead to superfluous investigations and unnecessary anxiety for the patient must be avoided. Because the biomarkers are produced in small amounts and released to plasma during healthy conditions, and because concentrations in plasma vary over time, it is necessary to be able to distinguish between true and false signals when serial measurements after treatment are to be interpreted. Here, different algorithms are proposed in literature, and this chapter deals with validation of some of these algorithms designed for the biomarker TPA (tissue polypeptide antigen) used in follow-up in treated breast

**1. Introduction** 

tumours.

*2Norwegian Quality Improvement of Primary Care Laboratories (NOKLUS),* 

**System for Interpretation and Validation** 

**of Algorithms for Monitoring of Cancer** 

