Download Imaging Biomarkers in Oncology Drug Development

Regulatory
Imaging Biomarkers in
Oncology Drug Development
Introduction
Biomarkers are defined as measurements or characteristics
that are evaluated as indicators of normal biological
or pathogenic processes, or responses to therapeutic
interventions. Biomarkers have become increasingly
important to physicians, medical product developers (both
drugs and devices), and regulatory agencies, impacting
treatment decisions as well as drug approvals in their ability
to define both efficacy (therapeutic benefit) and safety (the
likelihood and extent of undesirable off-target responses).
This article focuses on imaging biomarkers as employed in
efficacy assessments in oncology drug development.
Background
Cancer remains one of the world’s leading public health
concerns. Approximately 12.7 million cancer cases and 7.6
million cancer deaths are estimated to have occurred in
2008; of these, 56% of the cases and 64% of the deaths
occurred in the economically developing world. 1 For females,
breast is the leading cancer site and accounts for 23% of the
total cancer cases and 14% of the cancer deaths. For males,
lung is the leading cancer site, comprising 17% of the total
new cancer cases and 23% of the total cancer deaths. While
greater international education and prevention campaigns
are clearly desirable, the development, availability, and use
of new pharmacotherapies are critical.
Kelloff and Sigman2 discussed the use of biomarkers
in the context of drug development, citing those that are
expressed as a consequence of cancer development and
progression. Two categories of such biomarkers, those that
are most relevant for identifying patients who are likely to
respond to a given therapy and those that are most effective
for measuring patient response to therapy, are of particular
interest. The authors also discussed “innovative designs of
clinical trials and methodologies that are used to validate
and qualify biomarkers for use in specific contexts.”
Imaging Biomarkers
Imaging biomarkers play a key role in evaluating the
efficacy of new candidate drugs and/or innovative
therapeutic regimens (and can cost between 10% -15%
of the total budget of clinical trials). However, their
employment during clinical trials requires several issues to
be addressed satisfactorily. First, image interpretation must
be standardised to the greatest degree possible, meaning
that reduced inter- and intra-reader variability is essential
to minimise bias. Second, the volume of data generated
by state-of-the-art imaging modalities requires computing
facilities capable of storing, managing, and analysing the
data: streamlining data management workflow, therefore,
is a practical necessity. Web-based cloud computing
technology that is made available at all participating sites
22 Journal for Clinical Studies
JCS Volume 4 Issue 3 IFC-OBC.indd 24
facilitates state-of-the-art image interpretation directly
at investigator sites in an automated and standardised
process, thereby reducing inter-reader variability.
Traditionally, in many cases where data from many
investigator sites need to be interpreted, assessed, and
analysed, employment of a central (core) laboratory has
been considered the ‘gold standard.’ However, the time
taken to respond by central labs and discrepancies with
investigator site assessments leading to bias (e.g., wrong
decisions on including, treating, or excluding subjects/
censoring bias) have been critical issues. In the future, this
may change in this field as individual sites and readers
increase in expertise and standardisation. This would allow
sponsors to access imaging biomarker data in near real
time. This would therefore enable sponsors conducting
Phase II trials to make go/no-go decisions more quickly,
while implementing adaptive designs to collect data more
efficiently and consistently employing the same imaging
biomarker for Phase III trials.
Tumour Characteristics of Interest
While evaluation of tumour characteristics via singledimensional measurement criteria such as the Response
Evaluation Criteria in Solid Tumors (RECIST) criteria, 3-5
and bi-dimensional measurements (e.g., using WHO
criteria6) have proved informative,7,8 newer characteristics
of interest include quantitative lesion parameters such as
volume9-11 and density. 12 As new drugs are developed, the
effects of alternative mechanisms of action (e.g., drugs
that are antiangiogenic vs. cytotoxic) need to be assessed.
Some effects may not be observed by size measurements
alone, requiring instead assessments of changes in other
characteristics such as density, pattern, and perfusion.
Use of Automation
In the analysis of many types of data collected in clinical
trials, the putative advantages of computer-aided and
standardised systems include speed and reliability.
Here, automated detections of lesions, organ and lesion
segmentation, and assisted extraction of the parameters
mentioned earlier (volume, density, and others) are of great
interest. However, such systems must not only be reliable in
consistently providing the same reading and interpretation
of data, they must be reliable and correct. Demonstrating
such characteristics is at the moment a hot topic for the
medical imaging community. Several initiatives are currently
promoting such systems and paradigms, and gathering
academic, regulatory, and industry contributions to confirm
their performances and perform validation. Attention is
focusing not only on drug development activities but also
on routine clinical practice.13-14
Volume 4 Issue 3
24/5/12 19:33:03
Regulatory
Partnerships and Alliances in Contemporary Drug
Development
Partnerships and alliances between different stakeholders in
integrated pharmaceutical medicine 15 are becoming more
common, given the increasing demands and pressures of
bringing new drugs to market.16,17 These include partnerships
and alliances between biopharmaceutical companies
and companies manufacturing companion diagnostics,
and between biopharmaceutical companies and contract
research organisations (CROs).
The need to incorporate companion diagnostics into
development efforts is a growing demand, and one that
requires companies to plan ahead to ensure that relevant
companion diagnostics are brought to the marketplace
along with the respective drugs and their (new) indications. 16
An informative example is provided by crizotinib, which
was approved by the US Food and Drug Administration
(FDA) to treat patients with late-stage (locally advanced
or metastatic), non-small cell lung cancers expressing an
abnormal variant anaplastic lymphoma kinase (ALK) gene.
It required approval along with a companion diagnostic
test that determines if a patient’s tumour expresses this
abnormal gene, and is therefore a suitable candidate for
crizotinib therapy.
With regard to imaging biomarkers, a three-way
partnership or alliance between a biopharmaceutical
sponsor, a CRO, and an imaging company can prove fruitful.
As Smith et al 16 noted, “Involvement of a CRO or central
laboratory as a facilitator between biopharmaceutical and
diagnostic companies can have many benefits as these
organizations have an intimate understanding of the
drug development process and have significant practical
experience with developing and deploying biomarker tests
in a real-world setting.”
An alliance between the authors’ companies provides
an instructive case study. Thanks to its experience in
enabling novel imaging biomarkers, and to its system
being adopted by radiology departments around the world
for not only clinical trials but also routine clinical practice,
MEDIAN leverages its approved software medical device,
differentiated clinical trial imaging services offering, and
biomarker development capabilities that are essential to
such collaborative initiatives. Quintiles, in turn, leverages
its comprehensive understanding of the biopharmaceutical
industry in general and its expertise and experience in
conducting multi-site and multi-regional clinical trials.
Biomarker Technologies and Challenges
While there is considerable diversity in biomarker research
and development, each faces the same set of challenges:
qualification, clinical validation, and hence the requirement
of analysis platforms for biomarker evaluation. Various
approaches may be used for these purposes. Some insight
is provided by ICH Guideline E16 18 which focuses on
genomic biomarkers. The guideline comments as follows:
“Qualification is a conclusion that, within the stated context
of use, the results of assessment with a biomarker can be relied
upon to adequately reflect a biological process, response
or event, and support use of the biomarker during drug or
biotechnology product development, ranging from discovery
24 Journal for Clinical Studies
JCS Volume 4 Issue 3 IFC-OBC.indd 26
through post-approval.” The extent of the difficulties of
validation led Smith et al16 to comment, “The challenges
of incorporating biomarkers into clinical development
programs…are nearly as great as the enormous potential
that such technology affords.” It will be of considerable
interest to all stakeholders in pharmaceutical medicine, and
also clinical practice, to see how imaging biomarkers, and
biomarkers in general, continue to evolve.
Additional references are provided to guide further
reading.19-30.
References
1. J emal A, Bray F, Center MM, et al. Global cancer statistics.
CA: A Cancer Journal for Clinicians. 2011;61(2):69-90.
2. K
elloff GJ, Sigman CC. Cancer biomarkers: selecting the
right drug for the right patient. Nature Reviews: Drug
Discovery. 2012;11(3):201-214.
3. E isenhauer EA, Therasse P, Bogaerts J, et al. New response
evaluation criteria in solid tumours: revised RECIST
guideline (version 1.1) European Journal of Cancer.
2009;45(2):228–247.
4. R iaz A, Memon K, Miller FH, et al. Role of the EASL, RECIST,
and WHO response guidelines alone or in combination
for hepatocellular carcinoma: radiologic-pathologic
correlation. Journal of Hepatology. 2011;54(4):695-704.
5. T
sao AS, Garland L, Redman M, et al. A practical guide of the
Southwest Oncology Group to measure malignant pleural
mesothelioma tumors by RECIST and modified RECIST
criteria. Journal of Thoracic Oncology. 2011;6(3):598601.
6. W HO. WHO Handbook for Reporting Results of Cancer
Treatment. 48th WHO offset publication; Geneva,
Switzerland, WHO: 1979.
7. T herasse P, Arbuck SG, Eisenhauer EA, et al. New guidelines
to evaluate the response to treatment in solid tumors.
European Organization for Research and Treatment of
Cancer, National Cancer Institute of the United States,
National Cancer Institute of Canada. Journal of the
National Cancer Institute. 2000;92(3):205–216.
8. C
hoi H, Charnsangavej C, Faria SC, et al. Correlation of
computed tomography and positron emission tomography
in patients with metastatic gastrointestinal stromal tumor
treated at a single institution with imatinib mesylate:
proposal of new computed tomography response criteria.
Journal of Clinical Oncology. 2007;25(13):1753–1759.
9. F ollwell MJ, Khu KJ, Cheng L, et al. Volume specific response
criteria for brain metastases following salvage stereotactic
radiosurgery and associated predictors of response. Acta
Oncologia. 2012, April 26 [Epublication ahead of print].
10. B
uckler AJ, Miulshine JL, Gottlieb R, et al. The use of
volumetric CT as an imaging biomarker in lung cancer.
Academic Radiology. 2010;17(1):100-106.
11. B uckler AJ, Schwartz LH, Petrick N, et al. Data sets for
the qualification of volumetric CT as a quantitative
imaging biomarker in lung cancer. Optics Express.
2010;18(14):15267-15282.
12. Faivre S, Zappa M, Vilgrain V, et al. Changes in tumor
density in patients with advanced hepatocellular
carcinoma treated with sunitinib. Clinical Cancer Research.
2011;17(13):4504-4512.
Volume 4 Issue 3
24/5/12 19:33:21
Regulatory
13. Quantitative Imaging Biomarker Alliance (QIBA) /
Radiology Society of North America (RSNA). http://www.
rsna.org/QIBA_.aspx
14. Quantitative Imaging Network (QIN) / National Cancer
Institue (NCI) https://wiki.nci.nih.gov/display/CIP/QIN
15. Turner JR. Drug safety, medication safety, patient safety:
an overview of recent FDA guidances and initiatives.
Regulatory Rapporteur. 2009; 6(4):4-8.
16. Smith B, Stocum M, Verst C, Cohen O. Building value
through biomarkers: the “Smarter Development” initiative
[published online ahead of print April 12, 2012]. Drug
Information Journal. doi: 10.1177/0092861512441392.
17. Turner JR. New Drug Development: An Introduction to
Clinical Trials, 2nd Edition. New York: Springer.
18. ICH. Guideline E16. Biomarkers related to drug or
biotechnology product development: context, structure
and format of qualification submissions. http://www.ich.
org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/
Efficacy/E16/Step4/E16_Step_4.pdf
19. B ednar B, Ntziachristos V. Opto-acoustic imaging of
drug discovery biomarkers. Current Pharmaceutical
Biotechnology. 2012 Feb 15. [Epub ahead of print].
20. Cortez MA, Welsh JW, Calin GA. Circulating MicroRNAs as
non-invasive Biomarkers in Breast Cancer. Recent Results
in Cancer Research. 2012;195:151-161.
21. James ML, Gambhir SS. A molecular imaging primer:
modalities,
imaging agents, and applications.
Physiological Reviews. 2012;92(2):897-965.
22. Jones T, Price P. Development and experimental medicine
applications of PET in oncology: a historical perspective.
Lancet Oncology. 2012;13(3):e116-125.
23. Kircher MF, Hricak H, Larson SM. Molecular imaging for
personalized cancer care. Molecular Oncology. 2012;
March 10th. [Epublication ahead of print].
24. M atheis K, Laurie D, Andriamandroso C, et al. A generic
operational strategy to qualify translational safety
biomarkers. Drug Discovery Today. 2011;16(13-14):600608.
25. Punnoose EA, Lackner MR. Challenges and Opportunities in
the Use of CTCs for Companion Diagnostic Development.
Recent Results in Cancer Research. 2012;195:241-253.
26. Townsend DW. Combined positron emission tomographycomputed tomography: the historical perspective.
Seminars in Ultrasound, CT, and MR. 29(4):232-235.
27. Tatsch K. Standardisation and harmonisation boost the
credibility of nuclear medicine procedures. European
Journal of Nuclear Medicine and Molecular Imaging.
2012: 39(1):186-187.
28. M ozley PD, Schwartz LH, Bendtsen C, et al. Change in lung
tumor volume as a biomarker of treatment response: a
critical review of the evidence. Annals of Oncology. 2010:
21(9):1751-1755.
29. B uckler AJ, Bresolin L, Dunnick NR, et al. Quantitative
imaging test approval and biomarker qualification:
interrelated but distinct activities. Radiology. 2011:
259(3):875-284.
30. Sistare FD, DeGeorge JJ. Promise of new translational
safety biomarkers in drug development and challenges
to regulatory qualification. Biomarkers in Medicine.
2011;5:497-514.
www.jforcs.com
JCS Volume 4 Issue 3 IFC-OBC.indd 27
Sandra Silberman, MD, PhD, is Vice
President,
Translational
Medicine,
Quintiles. She has worked for
pharmaceutical companies, including
Pfizer and Novartis, developed the
Oncology Clinical group at Eisai, and
has been an independent industry
consultant to Bristol-Myers Squibb, AstraZeneca, ImClone,
Roche, and several biotechnology companies in their various
oncology programmes. She has over 50 publications and is
named on several patents in the cancer drug development
field. She is board certified in Internal Medicine and
Hematology/Oncology, and is an attending physician at the
VAMC in Durham, NC.
Email: [email protected]
Philip Breitfeld, MD, is Vice President and
Therapeutic Strategy Head, Oncology
Therapeutic Area, Quintiles. He has over
25 years of work experience in oncology,
including 20 years of experience in
academic medical institutions in the
US, and seven years of experience in
the pharma industry focused exclusively on oncology drug
development and execution of clinical programmes. Prior to
joining Quintiles he held senior oncology clinical development
positions at BioCryst and Merck Serono. He has around 50
peer-reviewed publications in the scientific literature, and was
a Visiting Scientist at the Whitehead Institute at MIT.
Email: [email protected]
Arnaud Butzbach, MS, is Vice-President
Operations and Chief Technology
Officer, MEDIAN Technologies, which
he co-founded back in 2002. He has
been contributing to the medical device
and imaging services industries with
pioneering companies (such as Deemed,
Focus Imaging, Healthcenter, and MEDIAN Technologies) for
more than twenty years, focusing on computer aided detection
and diagnosis (CAD/CADx) and quantitative imaging for
oncology. His scientific education and background in computer
sciences and applied mathematics (INPG/ENSIMAG) makes
him deeply involved with technology, software engineering,
delivery of clinical trial imaging services, and development of
imaging companion/monitoring tests.
Email: [email protected]
Acknowledgements
The authors wish to thank Hubert Beaumont, PhD, Estanislao
Oubel, PhD, MEDIAN Technologies, and J. Rick Turner, PhD,
Quintiles, for assistance in the preparation of this paper.
Journal for Clinical Studies 25
24/5/12 19:33:27