A tool for the development of companion diagnostics in clinical trials of oncology therapeutics for pharmaceutical industry

• Improve efficacy of clinical trials by incorporating gene expression profiling
  • Find new gene expression profiles for drug response and resistance
  • Help to confirm the patient population most likely to respond to the new drug
• Reduce length of clinical trials
  • Pre select high risk patients with early relapses to enrich the trial for early events
• Decrease development costs
  • Increased trial efficacy, fewer patients and shorter trial times all contribute to lowered clinical development costs

The importance of running focused, time- and cost-efficient clinical trials is crucial if potential new drugs are to be given the best possible chance of reaching the market. One of the biggest challenges in drug development, particularly in targeted oncology therapeutics, is to understand the differences in patient response rates. There have been many instances where novel therapeutics elicited a favorable response in some patients, while others showed no response.

In undifferentiated patient pools, the percentage of individuals that respond to a particular treatment is often too small to satisfy the trial's criteria. As a result, the drug is classified as a failure, potentially depriving others from beneficial treatment and resulting in significant financial implications for the company.

But how will regulatory bodies look upon companion diagnostics? The development of companion diagnostics should not impair the launch of the therapeutic agent. It is crucial that the companion diagnostic test is developed to the highest scientific and regulatory requirements in a clinical laboratory setting and that the test is clinically available and approved at time of drug launch.

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Including patient stratification in clinical trials

The DiscoverPrint service offers companies the opportunity to include patient stratification based on reliable identification and validation of gene expression profiles to differentiate between responders and non-responders. By taking into account how an individual’s genetic make-up impacts his or her response to a drug, this ‘pharmacogenomics’ approach, included in the start-up of a clinical trial, enables patient selection on the basis of an appropriate gene expression profile. Non-responders can be excluded, increasing the percentage of potential responders and thus improving the chances of meeting the trial’s criteria.

A case in point

The importance of patient stratification in today’s clinical development has been clearly demonstrated in a paper (Journal of Clinical Oncology, Vol 22, No.5 [March 1] 2004: pp759-761) by Jose Baselga from the Vall d’Hebron University Hospital, Barcelona, Spain in which he wrote about the failure of the Iressa (gefinitib) phase III trial to add clinical benefit to conventional chemotherapy in non-small-cell lung cancer (NSCLC) despite promising phase II trial results. Dr. Baselga compared this to the successful phase III trial for Herceptin (trastuzumab) on breast cancer and concluded:

Why consider Agendia?

• Proven track record in discovery, identification and validation of new gene expression profiles in the field of cancer
• Agendia understands the regulatory requirements of developing companion diagnostics being the first company in the world with a FDA IVDMIA cleared test
• Excellent, fully accredited (CLIA, FDA and ISO) laboratory resources for research, development and routine delivery of results
• Making sure newly developed test will be available for patients. existing test on the market
  • MammaPrint for breast cancer prognosis
  • CupPrint for cancer classification

For more information on the DiscoverPrint service to support clinical trials, please contact: This e-mail address is being protected from spam bots, you need JavaScript enabled to view it

* A gene-expression signature as a predictor of survival in breast cancer. M.van de Vijver et al., New England Journal of Medicine, vol 347, no 25, 19 December 2002
* Gene expression profiling predicts clinical outcome of breast cancer. L. van 't Veer et al., Nature, vol 415, 31 January 2002, 530-535

New profiles, new collaborations

Agendia is constantly working towards establishing new and improved gene expression profiles. In addition to in-house findings, the company is always interested in collaborating with others active in the oncology field. Research groups or commercial parties who have identified gene expression profiles, but do not wish to develop them further, are welcome to discuss the possibilities of in-licensing, or others means of collaboration.

To discuss possible collaboration or in-licensing, please contact: This e-mail address is being protected from spam bots, you need JavaScript enabled to view it