Biotech Strategy Blog

Commentary on Science, Innovation & New Products with a focus on Oncology, Hematology & Cancer Immunotherapy

Posts tagged ‘Biomarkers Drug Development’

One of the most interesting sessions I attended at this year’s American Society of Clinical Oncology (ASCO) annual meeting in Chicago was the Clinical Science Symposium (CSS) on the next generation of EGFR inhibitors.

We’ve previously written on the blog about the data for AZD9291 and CO-1686 presented at ASCO, but the CSS also featured an informative discussion by Larry Schwartz, MD, Professor of Radiology at Columbia University Medical Center which raised questions about how we should evaluate new lung cancer drugs.

In a presentation entitled, “Getting the Right Drug to the Right Patient Faster,” Schwartz who is a diagnostic radiologist, discussed and critiqued abstract 8012 by Dr Gideon Michael Blumenthal and colleagues at the U.S. Food and Drug Administration (FDA).

Larry Schwartz ASCO 2014

A meta-analysis of fifteen trials involving 12,534 patients (median N = 698) from nine experimental agents (tyrosine kinase inhibitor = 5, chemotherapy = 2, monoclonal antibody = 2) submitted to the FDA for treatment of metastatic non-small cell lung cancer (NSCLC) cancer in initial or supplemental New Drug or Biologics License Applications since 2003 was performed by Blumenthal and colleagues.

Their analysis showed a strong correlation (R² of 0.89) between overall response rate (ORR) and progression-free-survival (PFS) but only a weak or no correlation between ORR and overall survival (OS) (R² of 0.07) or between PFS and OS (R² of 0.09).

Dr Blumenthal noted in his conclusion that further work is ongoing to corroborate these findings given the lack of correlation between OS and ORR could have been due to high cross-over, under-power and long post-progression survival.

He went on to note that what the findings do show is that “a drug with a large effect on ORR is likely to have a large effect on PFS, conversely a drug with a small ORR may have a small effect on PFS.

The debate around objective response and outcomes is a very interesting one, as is the drive to find better biomarkers of response to improve chances of clinical trial success.

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Drug development for neurodegenerative brain diseases such as Parkinson’s or dementia, of which Alzheimer’s is the most common form, needs to focus on patients early in the disease, not those where brain damage has already occurred.

Diagnosing and treating patients more effectively earlier will, even if you aren’t able to instigate a cure, offer the ability to modify the disease progression and slow or delay when brain damage occurs.  In the case of Alzheimer’s, once the amyloid plaques (tangles of misshapen proteins) have accumulated in nervous tissue, it has so far been impossible to untangle or remove them.

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Last year, I interviewed Dr Todd Sherer, (then the Chief Program Officer) and now the CEO of the Michael J. Fox Foundation, who told me that: “biomarkers are a real focus of the foundation.” Sherer went on to say that:

“Parkinson’s is a difficult disease to diagnose, there is no definitive diagnostic test, so it ends up a clinical diagnosis.  Getting a biomarker that could help better confirm the diagnosis would allow people to get the correct treatment earlier in their disease”

Which is why I was interested to see new research published earlier this week in the journal Archives of Neurology (online first, August 27, 2012), by Sara Hall and colleagues at Lund University, University of Gothenburg and Skåne University Hospital in Malmo, Sweden.

Hall and colleagues describe how a panel of five cerebrospinal fluid (CSF) biomarkers allowed the differential diagnosis of common dementia from Parkinsonian disorders:

  • Beta-amyloid 42
  • Total tau
  • Phosphorylated tau
  • Alpha-synuclein
  • Neurofilament light chain

Patients with early symptoms of neurodegenerative diseases can be hard to diagnose.  Misdiagnosis can occur, which means patients may not respond to treatment or they could be enrolled into a clinical trial, and end up skewing the results.

Ensuring that we have the right patients in clinical trials is important as we seek to alter disease progression.  In other words it’s important to see whether new drugs or treatments are impacting the disease course.  If you have a wrongly diagnosed patient in a trial, then the drug may show no effect, not because it’s not effective, but that patient’s disease is not responsive.

Multivariate analysis indicated that the panel of 5 CSF biomarkers could accurately differentiate Alzheimer’s disease (AD) from Parkinson disease with dementia (PDD), and dementia with Lewy bodies (DLB). The Neurofilament light chain biomarker alone could differentiate PD from atypical Parkinson disease, Hall and colleagues noted.

Whilst the panel was not able to distinguish all forms of dementia, in an accompanying editorial Richard J. Perrin MD, PhD from the University of Washington, stated that this research “represents a significant step forward.” Perrin concluded that:

“Implementation of CSF biomarker panels such as this one should improve the efficiency of clinical trials and accelerate the evaluation and discovery of new effective treatments for neurological diseases.”


Developing biomarkers that assist in the ability to diagnose Alzheimer’s, Parkinson and dementia patients correctly, and then be able to monitor their subsequent disease progression, should be a key focus of those biotechnology and pharmaceutical companies that want to do innovative and rational drug development.


ResearchBlogging.orgSara Hall, MD, Annika Ohrfelt, PhD, Radu Constantinescu, MD, Ulf Andreasson, PhD, Yulia Surova, MD, Fredrik Bostrom, MD, Christer Nilsson, MD, PhD, Hakan Widner, MD, PhD, Hilde Decraemer, Katarina Nagga, MD, PhD, Lennart Minthon, MD, PhD, Elisabet Londos, MD, PhD, Eugeen Vanmechelen, PhD, Bjorn Holmberg, MD, PhD, Henrik Zetterberg, MD, PhD, Kaj Blennow, MD, PhD, & Oskar Hansson, MD, PhD (2012). Accuracy of a Panel of 5 Cerebrospinal Fluid Biomarkers in the Differential Diagnosis of Patients With Dementia and/or Parkinsonian Disorders Arch Neurol. DOI: 10.1001/archneurol.2012.1654

Richard J. Perrin, MD, PhD (2012). Cerebrospinal Fluid Biomarkers for Clinical Trials Arch Neurol. (August 27 Online First) DOI: 10.1001/archneurol.2012.2353

What is a Biomarker?

According to the Biomarkers Definitions Working Group, a biomarker is:

“a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.”

An example of a common biomarker is blood pressure. High blood pressure is a surrogate for cardiovascular disease and risk of stroke.

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Why are Biomarkers important?

Biomarkers can be used for diagnosis and for monitoring the safety and effectiveness of treatments. They are increasingly becoming important in the selection of patients for clinical trials, and as potential surrogates for clinical endpoints that may take a long time to occur e.g. measuring how long someone will live in a cancer trial (overall survival).

Examples of the use of biomarkers include:

  • Diagnosis: high blood pressure is used as a biomarker for cardiovascular disease and risk of stroke.
  • Treatment Selection: CSF biomarkers that correlate with neurodegenerative diseases may help select the most appropriate treatment
  • Drug Effectiveness: biomarkers can be used to monitor treatment or drug effectiveness e.g. use of cholesterol levels as a measure of cardiovascular disease
  • Surrogate Clinical Endpoint: a biomarker based on scientific evidence that predicts or correlates with clinical benefit could be used as a surrogate for a clinical endpoint that may take a while to detect e.g. how long a patient lives or survives, and in the process speed up drug development. Recent prostate cancer trials sought to show that circulating tumor cell (CTC) counts correlated with the survival benefits seen. However, validation of a biomarker needs to take place before regulatory agencies will accept it as a surrogate endpoint in clinical trials.

Biomarkers can be divided into those which are prognostic and those that are predictive.

Prognostic Biomarker: a marker that provides information on the likely course of a disease in an untreated individual.

Prognostic biomarkers are used to identify high-risk cancer patients who should, therefore, receive adjuvant therapy.

Predictive Biomarker: a marker that provides information on how likely you are to respond to a particular therapy.

Predictive biomarkers are used to guide treatment choices i.e. selecting the therapy with the highest likelihood of success.

In breast cancer, estrogen and progesterone receptors are biomarkers that predict sensitivity to endocrine therapy, while HER2 levels predict response to Herceptin treatment. In colorectal cancer (CRC) patients, KRAS mutations have been shown to be a biomarker of resistance to EGFR targeting drugs such as cetuximab and panitumumab.

Predictive biomarkers allow expensive new cancer treatments to be given only to those patients who are likely to respond. As we move forward into the era of personalized medicine the aim is to develop more highly predictive biomarkers that will allow better detection, diagnosis and treatment of disease.

In addition, there’s also a need to develop biomarkers that can distinguish between subgroups of patients to separate those who might benefit from a therapy and those who have developed resistance. Biomarkers for resistance to cancer therapy is an increasingly important area of research.

For those readers interested in cancer biomarkers, the joint ASCO-EORTC-NCI “Markers in Cancer” 2012 meeting in Hollywood, FL (near Fort Lauderdale) from October 11-13 has an agenda that holds promise.

Some of the presentations that caught my attention and ones I particularly look forward to watching remotely via the “Virtual Meeting” include:

  • Biomarkers of Resistance to EGFR-Targeted Therapies in Lung Cancer
    Enriqueta Felip, MD, PhD – Vall d’Hebron University Hospital
  • Resistance Mechanisms to BRAF Inhibition in Melanoma
    Jeffrey Sosman, MD – Vanderbilt-Ingram Cancer Center
  • Complexities of Identifying Non-Mutational Biomarkers of Resistance:
    The VEGF Pathway Example
    Michael B. Atkins, MD – Georgetown University
  • Development of Biomarkers for PI3K Pathway Targeting
    Sherene Loi, MD, PhD – Jules Bordet Institute, Brussels
  • Emerging Functional Imaging Biomarkers
    Annick D. Van Den Abbeele, MD – Dana-Farber Cancer Institute

The next post in this mini-series will discuss new research that shows how a panel of 5 CSF biomarkers can be used to differentiate between neurodegenerative diseases that might otherwise be misdiagnosed. This is particularly important for clinical trial recruitment where early symptomatic patients could potentially be recruited in error if given the wrong diagnosis, and placed in trials that they will not respond to.

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