The Common Rule: Human Samples, Ethics, and the Future of Biomarker Research

The Common Rule is the regulation governing research involving human subjects (subpart A of 45 Code of Federal Regulation part 46).  The original Common Rule was adopted in 1991 at a time when research was predominantly conducted at universities, colleges, and medical institutions, and each study generally took place at only a single site.  The evolution of research involving human subjects over the past two decades has revealed ambiguities in the original regulations and has led to questions regarding the effectiveness of the current regulatory framework to meet the needs of the researchers and research subjects.  On July 22 2011, the department of Health and Human Services (HHS) released an Advanced Notice of Proposed Rulemaking (ANPRM) for Revisions of the Common Rule.  This noticed was officially published in the Federal Register on July 25^th 2011 under the title:”Human Subjects Research Protections: Enhancing Protections for Research Subjects and Reducing Burden, Delay, and Ambiguity for Investigators“.  Over the past 90 days, HHS has sought comment on seven key issues (link):

1. Revising the existing risk-based framework to more accurately calibrate the level of review to the level of risk.
2. Using a single Institutional Review Board review for all domestic sites of multi-site studies.
3. Updating the forms and processes used for informed consent.
4. Establishing mandatory data security and information protection standards for all studies involving identifiable or potentially identifiable data.
5. Implementing a systematic approach to the collection and analysis of data on unanticipated problems and adverse events across all trials to harmonize the complicated array of definitions and reporting requirements, and to make the collection of data more efficient.
6. Extending federal regulatory protections to apply to all research conducted at U.S. institutions receiving funding from the Common Rule agencies.
7. Providing uniform guidance on federal regulations.

As of October 26^th 2011, the 90-day period for public comment has been closed.

In the October 20^th 2011 of Nature (link), Krishanu Saha and J. Benjamin Hurlbut discuss these proposed changes to the Common Rule in the context of biobanking. The authors argue that the revision to the regulations does little, or even worsens, the current disconnect between research subjects and researchers.  Indeed, the proposed changes to the Common Rule encourage the use of blanket informed consent that in effect, ask donors to authorize all possible future research unless they opt out of specific research categories (see also previous post:  Enabling Retrospective Biomarker Studies: Resolving the Conflict between Short and Long Term Goals).  While this evolution of the informed consent removes the ambiguity associated with the original Common Rule (which resulted in legal disputes), according to the authors, it poses the risk of reducing the involvement of the public in sample donation by further distancing the research subjects from the research performed on their samples.  As a solution, the authors advocate for a model in which the research subjects are actively involved.  For example, disease advocacy groups have succeeded in mobilizing research subjects by making them active players in the prioritization of research activities.  Companies like PatientsLikeMe and 23andMe attract research subjects by providing feedback about and control over the research conducted with volunteer samples.

The idea of offering dynamic feedback about and control over research activities to research subjects using for example, interactive web portals seems attractive at first glance.  Research subject could decide in real-time to opt in or out of certain research activities.  Researchers could easily gather supplemental information about research subjects.  However, under this model, the rules of research subject anonymity imposed by the Health Insurance Portability and Accountability Act (HIPAA) would be substantially more difficult to maintain and would require considerably stronger security measures to prevent accidental and/or malicious identification of subjects.  Also, the possibility of providing to research subjects feedback about research activities would open the door to the thorny issue of revealing unverified medical finding to the subjects.  Even if such communication were to occur via the subject’s physician, the exploratory nature of the research precludes the use of those findings for medical decision making.  Actually, the company 23andMe has been under increased scrutiny from the FDA Center for Devices and Radiological Health (CDRH) for providing research-grade genetic information to their customers (see earlier post: Genetic biomarker: the power and risk of knowing), even though the company claims that this information is not for medical decision making.

The proposed changes the Common Rule provide a welcome clarification of the regulations governing the collection and use of samples from human subjects.  While one can argue that these changes are not ideal, it is also true that the original version of the Common Rule exposed researchers and research subjects to a significant level of ambiguity.  Ultimately, the changes to the Common Rule are designed serve the greater good for society by facilitating medical research while preserving the right of research subjects.  


Thierry Sornasse for Integrated Biomarker Strategy
(The views expressed in this post are my own and are not meant to reflect the opinion of any other party)

Enabling Retrospective Biomarker Studies: Resolving the Conflict between Short and Long Term Goals

In the field of clinical biomarker research, it is common to need to explore new hypotheses after the conclusion of a clinical study (i.e. retrospective studies).  However, if the proper samples are not available, even the best ideas are no more than fantasies.  While this statement might seem trivial, it is surprising to discover that many bio / pharmaceutical companies struggle to implement the proper strategic and tactical steps to enable retrospective biomarker studies. 

In my experience, the most common strategic issue facing bio / pharmaceutical companies in this area is in resolving the conflict between short term and long term corporate goals.  Specifically, in the context of the conduct of clinical studies, the need to meet recruitment quotas and deadlines often clashes with the proposal to acquire supplementary samples that, at the time, have only theoretical value (i.e. potential use in retrospective studies).  Indeed, there is a general consensus among the teams responsible for running clinical trials (i.e. clinical operation) that adding sample collection procedures can complicate approval of protocols by the Institutional Review Boards (responsible for clinical study protocol approval on behalf of the institution and their patients) and can impede patient recruitment.  Therefore, unless there is a strong concrete justification for collecting certain samples, additional sample collections tend to be excluded from clinical protocols.  The solution to this apparent conflict resides in a strong corporate policy in support of biomarker research in general and retrospective biomarker research in particular.  Without the assurance that the logistical constrains imposed by sample acquisition for biomarker research will be fully acknowledged as a factor affecting the conduct of clinical studies, clinical operation will favor the bottom line (i.e. completion of studies in the shortest possible time).

Beyond a biomarker-friendly corporate attitude, the scientists and clinicians responsible for biomarker research need to have a sound understanding of the logistical impact of additional sample collection on clinical studies.  Biomarker researchers need to be able to negotiate intelligently with their colleagues in clinical operation.  Reciprocally, clinical operation staff needs to be with the scientific questions explored by the biomarker researchers.  Therefore, cross-training of biomarker researchers and clinical operation staff is one of the key aspects of a successful clinical biomarker research program.

In some cases, clinical samples that were collected for one purpose (e.g. pharmacokinetics) can be repurposed for biomarker research.  However, if the proper informed consent was not put in place at the time of sample collection, using these samples for retrospective biomarker studies is not acceptable.  Indeed, current ethical and legal standards mandate that all individuals enrolled in a clinical study be fully informed about the use of the biological samples collected in course of the study.  The issue of drafting informed consent forms that adequately inform the patients about future biomarker research can be quite tricky.  While it is impossible to describe all potential future use of clinical samples for biomarker research, it is important to define the overall intent and the limit of this research.  Also, it is often desirable to draft the informed consent form with the option for the patient of opting in (or out) of future biomarker research. 

Finally, assuming that clinical samples exist and are properly consented, efficient retrospective biomarker research requires a solid sample management system.  Beyond the physical inventory of samples, such as system ideally needs to seamlessly integrate anonymized patient medical information, clinical study specific information, consent status (whether patient opted in or out of biomarker research), and prior data obtained from these samples.  Hence, an efficient patient sample management is as much about inventory management as it is about information management.

Thierry Sornasse for Integrated Biomarker Strategy 

Overhaul of the FDA Medical Device Pre-Market Approval Program: What Does It Means for Diagnostics

On October 19^th, the FDA Center for Devices and Radiation Health (CDRH) released its Medical Device Pre-Market Programs: An Overview of FDA Actions (link).  This document presents the center’s review of the processes of pre-market approval of all medical devices, and articulates solutions to the problems identified in this review.

First, CDRH wants to dispel the misperception that safety/effectiveness and innovation are incompatible.  Their solution is not to focus on whether more or less regulations are needed but rather to focus on smart regulation: effectively achieve both aspects of the center’s mission as a regulator and facilitator.

Second, the number one problem identified from discussions with key stakeholders (i.e. industry, academia, and payers) is insufficient predictability in the pre-market program.  This lack of clarity has resulted in inefficiencies, increased cost for both the industry and the FDA, and delays in bringing safe and effective innovative products to the market.  At the root of these problems, CDRH identified excessive staff turnover, insufficient training (FDA and industry), rapidly increasing workload associated with the growing complexity and number of submissions, inconsistent data requirements, insufficient guidance for the industry, and poor quality of industry submissions.

To address these issues, CDRH is proposing a set actions centered on three areas of emphasis:

1. Create a culture change toward greater transparency, interaction, collaboration, and the appropriate balancing of benefits and risks
1. Better engagement with industry
1. Improve Interactive Review (informal call to the submitter) to accelerate review time
2. Improve pre-submission meetings to specify consistent and stable submission expectations
2. Greater use of external experts
3. Implementing flexible, risk-based policies that appropriately balance benefits and risks and apply a more patient-centric approach
4. Establishing new ways of doing business that add value
1. Create an innovation pathway (an entirely novel approach) to enable the timely review of ground-breaking technologies
5. Setting clear expectations for CDRH staff
2. Assure predictable and consistent recommendations, decision making, and application of the least burdensome principle
1. Providing adequate management oversight and staffing
2. Enhancing training
3. Improving internal processes
4. Adopting smarter policies and issuing more guidance
5. Developing new communication tools
3. Implement efficient processes and use of resources
1. Making existing processes more efficient
2. Using our resources more effectively
3. Improving our ability to rely on data from outside the U.S. and actions by regulatory bodies of other countries

For regulatory purposes, diagnostics are medical devices.  Therefore, the changes proposed by CDRH will affect the submission and approval of novel diagnostics.  Specifically, the development and approval of diagnostics will most likely benefit from the improved review process with greater predictability and transparency.  The commitment of CDRH to actively interact with the sponsors will most likely provide greater efficiency and reduced review time.  The call for enrolling experts in the relevant fields should streamline the process of defining the requirements for successful submissions.

While these improvements are promising, CDRH makes no secret that a significant number of these solutions will require additional funding.  The ongoing negotiations of the reauthorization of user fees will therefore most likely result in higher cost for the sponsors.  In keeping with this move, CDRH emphasizes the concept of shared responsibilities by stating: “We must fully embrace the paradigm that assuring the safety and effectiveness of devices is everyone’s job and the responsibility resides as much with industry, practitioners and patients as with the Agency”.

The specific aspect of review of approval of companion diagnostics is not specifically addressed in this report.  The sometime chaotic relationship between CDRH and its drug reviewing counterpart CDER would certainly benefit from a similar review.

Thierry Sornasse for Integrated Biomarker Strategy

Volumetric MRI and Neuropathology in the Elderly: a Key Bridging Study

In the October 17^th issue of PLoS One, Robert Dawe and colleagues, from the Illinois Institute of Technology and the Rush Alzheimer’s Disease Center, present the results of a key bridging study of volumetric MRI correlation with normal aging, Alzheimer’s disease (AD), and additional neuropathologies frequently associated with aging (link).

As mentioned in an earlier post (Biomarker Qualification Consortia: The ADNI Success Story), in vivo volumetric MRI of specific region of the brain (i.e. medial temporal lobe à hippocampus) has been shown to be a valuable biomarker of disease progression in AD and mild cognitive impairment (MCI).  While the correlation between reduction in hippocampal volume and histopathologically confirmed AD has been conclusively demonstrated, the effect of other neuropathologies generally associated with aging on hippocampal volume remained ill-defined.

In order to address this gap in knowledge, the authors combined antemortem imaging studies, antemortem cognitive testing, postmortem MRI on isolated brain hemisphere, and histopathology on the brains of 100 elderly subjects from the Rush Memory and Aging Project, and the Religious Order Study (two longitudinal clinical-pathologic studies of aging).  The authors confirmed the strong association between reduced hippocampal volume and the diagnostic of AD (determined prior to death based on cognition test and determined postmortem based on histopathology).  In addition, hippocampal volume was related to multiple cognitive abilities assessed proximate to death, with its strongest association with episodic memory.  Other pathologies such as Lewy bodies, moderate amyloid angiopathy, gross infarcts, and micro infarcts were not significantly associated with reduced hippocampal volume.  In contrast, hippocampal sclerosis (HS) was strongly associated with significant reduction in hippocampal volume independently of the presence or absence of co-occurring AD pathology (of 13 individuals with HS, 9 had also AD pathology and 4 had not other pathology).  In fact, the association of HS and reduced hippocampal volume was more pronounced than that observed in AD.  Shape analysis of the hippocampal surface confirmed prior knowledge namely that hippocampal volume reduction in AD is more pronounced in the head and tail of the hippocampus, and that these changes tend to be more homogeneously distributed in HS.  The authors did not discuss whether shape analysis of the hippocampal surface could be used to distinguish between AD and HS.

Despite some minor limitations: the postmortem MRI performed on isolated brain hemispheres precluded the measurement of cranial volume, this study provides a highly valuable bridge between in vivo volumetric MRI measurements and underlying neuropathology.  


Thierry Sornasse for Integrated Biomarker Strategy

Magnetic Resonance Spectroscopy to Monitor Tumor Metabolism: Not a Biomarker Yet But a Promising Concept

In the October 12^th issue of PLos One, Alessia Lodi and Sabrina Ronen from UCSF published the results of their work on the use of Magnetic Resonance Spectroscopy (MRS) to monitor the metabolic activity of tumor cells (link).  Although this work was entirely conducted in vitro on cell lines, the concept presented in this paper offer a glimpse at a possible new approach to monitor drug effect early during treatment.  Indeed, there is ample evidence that anti-cancer drugs alter the metabolic profile of cancer cells before producing detectable effects on tumor size (detectable by CT scan or MRI) or even overall metabolic activity (detectable by FDG-PET).

The utility of MRS to monitor early metabolic changes induced by drugs in cancer cells has been demonstrated before.  However, these earlier studies focused on single metabolites which limited their observations to the specific drug – cell combination studied.  In this work, the authors expanded on earlier work MRS use for the monitoring of cancer cell metabolism by used an unbiased 1H MRS-based metabolomics approach to investigate the overall metabolic consequences of treatment with the phosphoinositide 3-kinase inhibitor LY294002 and the heat shock protein 90 inhibitor 17AAG in prostate and breast cancer cell lines.

Obviously, translating this concept to human patients, in which complexity will be several orders of magnitude greater, will not be easy but one can speculate that as MRS technology further progresses, tracking multiple metabolites in vivo will become trivial. 


Thierry Sornasse for Integrated Biomarker Strategy

An Old Diagnostic Gets the Boot: PSA Testing in Healthy Men is No Longer Recommended

This week, the United States Preventive Services Task Force is due to release its draft recommendation on the use of the Prostate-Specific Antigen (PSA) test in healthy men of all ages.  The PSA test has been a standard tool in urology to assist in the diagnosis of prostate cancer.

Essentially, this recommendation states that the PSA test in healthy men has no clinical benefit, does not save lives, and actually may lead to unnecessary follow up tests and procedures that can have deleterious effects on the patient’s health (see The New York Times article).

These conclusions are based on the results of five well-controlled clinical studies which confirm the general empirical consensus about the PSA test: its lack of specificity and sensitivity result in unacceptable numbers of false positive and false negative tests, respectively.  In particular, false positive tests are particularly troublesome since a positive test will usually lead to a biopsy and treatment that can lead to impotence and/or incontinence.  While those risks of complications are somewhat acceptable for actual prostate cancer patients, they are unacceptable for individual who have misdiagnosed.

This recommendation by the United States Preventive Services Task Force is already producing strong reactions from prostate cancer survivors and advocacy groups.  The idea of shelving the PSA test is unacceptable to those who feel that this diagnostic saved their live.  The truth is that neither the PSA test nor other currently available tests are particularly useful in detecting prostate cancer.  Hence, there is an urgent need to develop, clinically validate, and deploy effective tools for the early detection of prostate cancer in apparently healthy men.  Ironically, the dominance of the PSA test on the market has probably a substantial obstacle to the development of new diagnostic in this field.  Indeed, the protectionism from a segment of the diagnostic industry with financial interest in PSA testing, as well as the difficulty to change medical practices among physicians have probably contributed to the lack of alternative prostate cancer diagnostics.  One can speculate that the new recommendation about PSA testing will open a breach for innovative tools that will actually save lives.


Thierry Sornasse for Integrated Biomarker Strategy

A New RNA Biomarker for Huntington’s Disease: Going Beyond Nerve Pathology (bis)

In the early online issue of the Proceedings of the National Academy of Sciences of October 3^rd (link), Hu and colleagues reports on a new biomarker of disease activity for Huntington’s disease (HD) based on the differential expression level of the transcript for H2AFY gene in peripheral blood mononuclear cells (PBMC).  HD is an autosomal recessive genetic disorder in which nerve cells in certain parts of the brain waste away, or degenerate.

Similarly to the recent work on ALS biomarkers published in PLoS One this month (see earlier post: New Potential ALS Multiprotein Biomarker: Going Beyond Nerve Pathology), Hu et al. hypothesized that the key pathobiology affecting neurons in HD would be detectable in other cell types than neurons.  Indeed, the huntingtin protein, which has been shown to be at the center of HD pathobiology, is expressed in most tissues, including PBMC.

Using a standard transcriptomics approach, the authors surveyed the entire genome for differential RNA expression between the PBMC of HD patients, healthy controls, and other neurological disorders (Parkinson’s disease, Alzheimer’s disease, corticobasal degeneration, essential tremor, progressive supranuclear palsy, and multiple system atrophy).  Using stringent statistical criteria and pathobiological knowledge, the team selected the transcriptional modulator H2A histone family member Y (H2AFY) as the most relevant biomarker for HD.  This initial discovery was confirmed by two independent studies.  First, a cross-sectional case controlled study of an additional 36 HD patients, 9 carriers of the HD mutation with no clinical symptoms (the HD mutation has 100% penetrance and therefore all carriers will eventually develop the disease), 50 healthy controls, and one individual with spinocerebellar ataxia.  Second, a longitudinal case-control study where 25 HD patients and 21 healthy controls were followed for at least 2 years (37 subjects were followed for 3 years).

In order to link the transcriptional difference observed in PBMC of HD patients to the pathobiology of the disease, the authors analyzed the expression of the H2AFY-encoded protein MacroH2A1 in the frontal cortex of postmortem brains obtained from 12 HD patients.  While the expression of MacroH2A1 was clearly elevated in the brain of patients with grade 2 or 3 disease, this trend was not maintained in grade 4 patients.  This was most likely due to the fact that MacroH2A1 is expressed at high level in neurons and that this stage of the disease is characterized by a substantial loss of these cells.  Finally, the authors assessed the translational value of the H2AFY / MacroH2A1 biomarker in a mouse model of HD (knock-in of exon 1 fragment of the human huntingtin gene).  There again, the progression of the disease was associated with an elevation of the MacroH2A1 protein in relevant brain substructures and treatment with the experimental HDAC inhibitor sodium phenylbutyrate resulted in a decrease in the biomarker signal.

Altogether, if these observations are further confirmed, the availability of a disease progression and a disease modification biomarker for HD should constitute a major advance in the field.  Indeed, the development of drugs for the treatment of HD has been hampered by the lack of sensitivity and precision of standard clinical end points.  Similarly to other neurodegenerative diseases such Alzheimer’s and Parkinson’s disease, clinical progression in HD is slow, erratic, and relatively unpredictable at the individual level.

Beyond the direct impact of this work, the approach used by Hu and colleagues seems to signal a new trend in biomarker research: instead of limiting the scope of biomarker research to the specific anatomical compartment primarily affected by the disease, which in the case of the central nervous system is essentially inaccessible, the field may significantly benefit from considering accessible peripheral tissues which may display secondary pathobiology similar to that affecting the primary tissues.  Indeed, a similar approach was used by Nardo and colleagues to identify a potential new protein biomarker for Amyotrophic Lateral Sclerosis (PloS One October 5^th; see earlier post: New Potential ALS Multiprotein Biomarker: Going Beyond Nerve Pathology)


Thierry Sornasse for Integrated Biomarker Strategy

New Potential ALS Multiprotein Biomarker: Going Beyond Nerve Pathology

In the October 5^th issue of PLos One, Nardo and colleagues (link) present the results of their work on a new peripheral blood cell-bases biomarker for the diagnosis and monitoring of Amyotrophic Lateral Sclerosis (ALS: a disease of the nerve cells in the brain and spinal cord that control voluntary muscle movement).

Based on the assumption that ALS pathobiology is no restricted to the nervous system, the authors conducted a classic proteomics analysis (2D-DIGE) of pooled peripheral blood mononuclear cells (PBMC) collected from healthy controls and patients suffering from ALS (grouped into two disease severity cohorts based on the ALS functional rating scale revised [ALSFRS-R]).  The first set of 71 candidate biomarkers was first refined to a 14-protein biomarker panel by validation against healthy controls.  This subset was further refined to a 5-protein ALS-specific biomarker panel (table 1) by validation against other neurological disease controls that may clinically resemble ALS.  

Table 1

Out of this 5-protein panel, the combination of IRAK4 and CypA was the most associated with ALS versus other neurological disorders, yielding a discriminatory power of 91% at the appropriate cut-off value (Receiver Operator Curve AUC = 0.905).

From the original 14-protein biomarker panel, the authors also derived a 3-protein ALS severity biomarker panel (table 2) by comparing patient samples from moderate disease (ALSFRS-R > 24) to samples from patients with severe disease (ALSFRS ≤ 24).  Out of this 3-protein panel, ERp57 was the most associated with disease severity with 89% discriminatory power at the appropriate cut-off level (Receiver Operator Curve AUC = 0.893).

Table 2

Finally, the authors investigated the translational value of the 14-protein biomarker panel by analyzing those proteins in the PBMC and the spinal cord from a rat model of ALS (G93A SOD1-transgenic rats).

By showing that disease biomarkers for a neurological disease can be identified in easily obtainable PBMC, this work represents an important step in the evolution of biomarker research.  Instead of limiting the scope of biomarker research to the specific anatomical compartment primarily affected by the disease, which in the case of the central nervous system is essentially inaccessible, the field may significantly benefit from considering accessible peripheral tissues which may display secondary pathobiology similar to that affecting the primary tissues. 


Thierry Sornasse for Integrated Biomarker Strategy

Alternative Use of Neuroimaging: A Public Perception Survey

In the October 4^th issue of Plos One, Wardlaw and colleagues published the results of a survey about the public and the expert perception of neuroimaging use in society (link).  This fascinating societal insight in the current and future use of neuroimaging highlights an often overlook aspect of biomarker and diagnostic research: the potential adoption barrier caused by conflicting information propagated by the general media.  Indeed, the development of some new, or even established, technologies can be thwarted by excessive regulations stemming from unwarranted fears propagated by a media industry hungry for sensational sound bites.

In this case, the authors focused on assessing the opinions of the general public and of medical experts on the medical and non-medical use of neuroimaging in modern society.  In particular, the authors sought to gather opinions about the claim that modern neuroimaging can be used for detecting lies in a judicial context, preferences in a marketing context, and racial attitude in a social context.

While the public and the experts all agreed that conventional medical uses of neuroimaging (i.e. detection of brain pathology and certain mental illness) are trustworthy and well established, both groups showed little faith in uses of neuroimaging in non-medical applications.  However, the survey revealed that the experts had little awareness of the use of neuroimaging in US court, grossly underestimating the number of cases where neuroimaging have been used as evidence over the past few years.  Similarly, a third of the experts reported no familiarity with the use of neuroimaging in the fields of neuromarkerting and commercial lie-detection.  Interestingly, although the majority of experts felt that the actual state of neuroimaging was not accurately represented by the general media, few felt compelled to rectify the situation.

Looking ahead, the experts were generally more optimistic about the future of neuroimaging than the general public.  While the relative skepticism from the public may provide some degree of protection against the misrepresentation of neuroimaging capabilities by the general media, the relative enthusiasm of the experts means that there is no shortage of expert opinions that can be used out of context by the general media to promote sensational claims about neuroimaging capabilities.

Although this paper does not intend to address the entire field of biomarker and diagnostic development, these findings should serve as a lesson for the entire field.  Consistent communication about the true capabilities of a new biomarker / diagnostic technology should be an integral part of the final stage of diagnostic development.  Failing to do so could result in the public misperception of the advantage and/or risk of a new promising technology.

The Parkinson Progression Marker Initiative: An Emerging Success Story

In an earlier post Biomarker Qualification Consortia: The ADNI Success Story, I discussed the value of biomarker qualification consortia by highlighting the success of the NIH sponsored Alzheimer’s Disease Neuroimaging Initiative (ADNI).  Here, I would like to raise awareness to another biomarker qualification consortium in the field of neurodegenerative medicine: the Michael J. Fox Foundation sponsored Parkinson Progression Marker Initiative (PPMI).

PPMI is a consortium of academic, industrial, and non-profit organizations dedicated to the assessment and qualification of biomarkers of Parkinson’s disease (PD) through the longitudinal monitoring of early PD patients.  In contrast to ADNI, PPMI main sponsor is the Michael J. Fox Foundation: a non-profit organization dedicated to the advancement of PD treatment through scientific research and public awareness.  PPMI has assembled a total of 21 sites in the US and Europe which will recruit and follow 400 early PD patients and 200 age-matched controls volunteers over a 5-year period.  Similarly to ADNI, PPMI has defined a set of standardized protocols for the assessment of clinical (motor assessment, neuropsychiatric, olfaction) end points and imaging (DATScan, MRI, DTI), biochemical (alpha-synuclein, DJ-1, urate), and genetic biomarkers.  In keeping with the non-competitive spirit of the consortium, all data collected by PPMI will be made available to the scientific community through a centralized data repository.  PPMI also intends to facilitate access the biosamples collected from the study participants.

Although PPMI has only been active since June 2010 and not all sites have been active since the study start, the study has already enrolled 50% of the control participants (goal: 200 individuals) and 31% of the PD participants (goal: 400 individuals).

As it is common for studies of this magnitude, PPMI has encountered a few bumps in the road.  Although DATScan was approved by the FDA for US use on January 14^th 2011, this critical imaging biomarker technology has not been available since February 2011 (status may have changed since this information was released).

Thierry Sornasse for Integrated Biomarker Strategy

Siemens HX4: A New PET Marker of Tumor Hypoxia

On September 29^th, Siemens announced that the company had completed a phase II study of their new tumor hypoxia Positron Emission Tomography tracer HX4 (link).  The ability to identify hypoxic tumors through imaging is of great significance to the personalized management of a broad variety of cancers since hypoxic tumors tend to be more resistant to radiotherapy and chemotherapy.

HX4 is not the first PET tracer developed as a biomarker of tumor hypoxia.  For instance, F-MISO ([¹⁸F]‑Fluoromisonidazole) has been tested with some success in the clinic (reference) but its relatively slow rate of clearance from the body have limited the utility of this tracer (link).  In contrast, HX4 has demonstrated a faster clearance from the body while maintaining a reproducible uptake by hypoxic tumors, producing higher image contrast within a relatively short period post-injection (i.e. 145 minutes).

Of note, HX4 has not yet been approved but is intended for world-wide distribution by PETNET Solutions, a wholly owned Siemens subsidiary which already provides PET tracers such as [¹⁸F]FDG and Na[¹⁸F] for metabolic uptake and bone metastasis imaging, respectively.

The Forces Driving the Future of Personalized Medicine

Transport yourself 10 to 15 years from now and try to imagine what the future of personalized medicine will look like.  The vision of every drug prescription decisions being driven by a test aimed at tailoring the treatment to a particular individual is probably utopian.  Rather, I would argue that the realm of personalized medicine will still be limited to the treatment of severe and/or life-threatening diseases that require expensive medications.  Under this premise, what are the forces that will shape the future of personalized medicine?

In my mind, this question can be addressed by considering the field from a supply and demand perspective.  On the supply end, the pharmaceutical and diagnostics industries will remain the main forces driving the future of personalized medicine.  The imperative of improving the return on investment in drug development will dominate the future of the pharmaceutical industry.  With the era of relying mainly on “one-size-fit-all” drugs fading away, the focus will shift towards precision/personalized medicine where drugs are designed to address the need of smaller targeted patient populations.  Hence, the need to develop the tools that will identify the right patient population (for efficacy and/or safety reasons) will constitute a major theme in drug development.  This does not exclude the continuing effort of the pharmaceutical industry to develop and commercialize broadly applicable drugs for the management and/or treatment of conditions for which a personalized approach is not warranted (for cost-benefit and/or clinical utility reasons).  Still on the supply end but with an eye on the demand side, the regulatory authorities will continue to play a major role in the harmonization of the biomarker and companion diagnostic development process.  Beyond the current regulatory framework governing the regulatory approval of drugs and companion diagnostics, the regulators have been working on developing a new process for an integrated development of biomarkers intended to become companion diagnostics (see earlier posts: Harmonization of Biomarker Qualification Regulatory Submissions; Companion In Vitro Diagnostics (IVD) Development).

Probably the most significant force that will shape the future of personalized medicine will be on the demand side, represented by the patients, the medical practitioners, and most importantly the health insurance/payers.  For all three entities, the adoption of a new companion diagnostic will require proof of clinical utility (Ref1, Ref2, & Ref3).  In a nutshell, clinical utility for a molecular diagnostics is the third level of a three-tiered evaluation framework that includes “analytical validity”, “clinical validity/qualification”, and “clinical utility” (Ref2).  Hence, clinical utility encompasses the overall medical impact of a diagnostic.  A diagnostic is considered clinically useful if it provides a real and substantial advantage to the patients, positively alters the practice of medicine, and/or improves the cost / benefit equation for a given treatment.  Although clinical utility is a distinct concept from analytical and clinical validity, it cannot be established without first establishing the latter.  The reciprocal is however not true: establishing analytical and clinical validity does not imply proof of clinical utility.

While the pharmaceutical industry and the regulators are currently focusing most of their efforts on defining and implementing the rules of diagnostics analytical and clinical validation, I would argue that the next decade will be dedicated to the third part of the equation: defining and implementing the rules of diagnostics clinical utility evaluation.

Thierry Sornasse for Integrated Biomarker Strategy

A Clinically Qualified Biomarker of Response to anti-CD20 Therapy in Rheumatoid Arthritis

In the September 21^st issue of Science Translational Medicine (link), scientists at Genentech reveal their findings about a new, clinically qualified biomarker of non-response to antibody therapy to CD20 in rheumatoid arthritis (RA).  B cell depleting therapy using the anti-CD20 mAb rituximab in RA (link) is reserved for patients who have failed standard disease-modifying antirheumatic drugs (specifically methotrexate) and/or with inadequate response to anti-TNF antibody therapy.  Considering the cost, complexity, and relative risk associates with anti-CD20 therapy and considering that about 50% of RA patients do not respond to rituximab, there is a strong impetus to target this therapy to patients who are most likely to respond favorably.

Hypothesizing that RA patients with high frequency of antibody producing plasma B cells are less likely to respond to rituximab (plasma cells do not express CD20), the team at Genentech surveyed a set of B cell and plasma cell specific RNA transcripts in blood samples from a subgroup of patients who had been treated with rituximab (REFLEX study).  Using the American College of Rheumatology 50% improvement criteria (ACR50), they identified a clear association between failure to meet ACR50 and elevated levels of RNA for the immunoglobulin J chain (IgJ) at baseline.  They confirmed this observation using blood samples from patients enrolled in two additional independent rituximab studies (DANCER and SERENE), and one study of ocrelizumab (a second generation anti-CD20 mAb) in RA (SCRIPT).  When all four trials were combined, the ACR50 response rate in the active arms was 28% for the IgJ^lo group (n = 471) and 12% for the IgJ^hi group (n = 122) (Odd ratio: 2.7; 95% confidence interval: 1.5 to 5.3).  The predictive power of the IgJ RNA level was further refined by combining this parameter with the RNA levels for the B cell specific splice variant of Fc Receptor-like 5 (FCRL5).  Together, elevated levels of IgJ RNA and low levels of FCRL5 at baseline (biomarker positive: IgJ^lo / FCRL5^hi) were strongly associated with low probability of positive response to anti-CD20 mAbs therapy (figure 1).  Indeed, in the combined 4 clinical studies, 28% of biomarker-negative patients responded to treatment while only 9% of biomarker positive patients responded under the same conditions (Odd ratio: 3.6; 95% confidence interval: 1.8 to 8.4).  Of note, this combination biomarker does not appear to be an indicator of more severe diseases since it was not associated with different response rate in the placebo groups from those clinical studies.

Fig. 1

Beyond representing a major advance in the area of treatment decision in RA patients, this work represents a remarkable example of the power of well-planned, well-executed prospective retrospective studies for the discovery and clinical qualification of novel biomarkers

Thierry Sornasse for Integrated Biomarker Strategy

New Biomarker to Guide Antibiotic Prescription Decisions: Procalcitonin as Barometer of Infection

In the early online issue of September 22^nd of BMC Medicine (link; provisional paper), Philip Schuetz, Werner Albrich, and Beat Mueller review the present and the future promises of procalcitonin (PCT) as a potential generalized biomarker of infection and potential guide to antibiotic prescription in clinical settings.  As the authors point out, the field currently lacks reliable biomarkers of bacterial infection that can be assessed rapidly from easily accessible samples, resulting in suboptimal management of antibiotics administration.  Therefore, beyond the direct benefit of expediting the diagnosis of bacterial infection, PCT could be used to develop an antibiotic prescription algorithm that would potentially optimize antibiotics usage by eliminating their use in circumstances where they are not needed (fig. 1)

While strong evidences from randomized clinical trials support the use of PCT to guide the prescription of antibiotics for the treatment of lower respiratory tract infections (upper respiratory tract infection, pneumonia, COPD exacerbation, and acute bronchitis), and severe sepsis, more work needs to be done to establish PCT as a clinically relevant tool in the management of infections such as bacteremia, abdominal infection, neutropenia, and postoperative fever.

Thierry Sornasse for Integrated Biomarker Strategy

Catching Metabolic Pathways in the Act: Navigating the Heavy Water World

A press release on September 16^th on Market Watch about KineMed caught my attention (link).  KineMed, based in Emeryville CA, has developed new proteomics and metabolomics tools that enable the monitoring of metabolic flux through complex biological pathways by exploiting the power of deuterated water (or heavy water: ²H₂O) labeling.  By monitoring the kinetic of predictable mass shift of molecules of interest by mass spectrometry, the scientists at KineMed have been able to ascertain complex dynamic processes such as blood clotting, complement cascade activation, epidermal turnover in psoriasis patients, anterograde neuronal transport in ALS and PD patients, and DNA turnover rate in leukemia and breast cancer (see a video presentation by Marc K. Hellerstein, M.D., Ph.D.; co-founder of KineMed)

Because of its non-radioactive nature and ease of deployment (deuterated water is simply administered as a glass of water), this technique offers the prospect of identifying new biomarkers related to disease processes, drug mechanism of action, and drug toxicities.  It is important to remember though that this technique does not allow for in situ metabolism monitoring and thus still requires sample collection.  Therefore, the usual limitations associated with the collection of biosamples do apply to this new technique.

Thierry Sornasse for Integrated Biomarker Strategy

From Biomarker to Companion Diagnostic: of Analytical and Clinical Validation, Regulatory Affairs, and Intellectual Property

In the August 24^th early online issue of Drug Discovery Today (reference), Michael Nohaile from Novartis Pharma AG discusses the key factors required to translate a promising biomarkers into an effective companion diagnostic (CDx).  Based on a pragmatic staging scheme of drug – CDx co-development (figure 1), the author dissects the complex cross-functional interactions between of analytical and clinical validation, regulatory affairs, and intellectual property management.

Fig.1

On the analytical validation front, the author stresses the importance of timely assay platform selection, the need for proper consideration of pre-analytical parameters (see my earlier post: Biomarker Research: The Pre-analytical Puzzle), and the critical issue of the synchronization of the assay validation process to meet clinical development milestones.  Failure to complete assay validation before the initiation of pivotal clinical will require the conduct of complex and expensive bridging studies to satisfy the regulatory requirement for CDx.

On the clinical validation front, the author discusses the issue of adequate sample ascertainment rate from clinical studies in the context of prospective-retrospective (predefined analysis of samples from a completed study) CDx clinical validation strategies, and the issue of the statistical power for purely prospective CDx clinical validation studies.  In particular, serious consideration should be given to the decision of including or excluding marker negative patients in such studies.  On the one hand, inclusion of marker-negative patients is required to determine the positive and negative predictive value of the candidate CDx.  On the other hand, beyond being less expensive and potentially faster, studies that exclude marker-negative patients may also present an ethical advantage in cases where the potential treatment benefit is expected to be negligible in marker-negative individuals.

From a regulatory affairs perspective, the fact that CDx are regulated by the Center for Devices and Radiological Health (CDRH) implies that specific regulatory expertise is required for the successful prosecution of CDx (see also my earlier post about recent FDA guidance: Companion In Vitro Diagnostics (IVD) Development: some clarity at last).  In particular, the fact that the risk / benefit analysis for CDx is entirely tied to the risk / benefit profile of the associated drug implies a close collaboration between the drug reviewing authorities (CDER/ CBER) and the device reviewing authorities (CDRH).

Finally, from an intellectual property, the author discusses the issue of the timing of patent filing and the more global issue of patentability of biomarkers.

Thierry Sornasse for Integrated Biomarker Strategy

System Biology-Based Prognostic Biomarkers of Clinical Complications in Acutely Injured Patients

In the September 13^th issue of PLoS One (link), John D. Storey and colleagues report on inflammation-related gene expression signatures associated with differential clinical outcome in acute trauma patients.  Specifically, the authors analyzed the expression of inflammation-related genes in 168 blunt-force trauma patients over a 28-day period.  The genes and gene pathways that clustered differently between patients’ clinical outcome subgroups (based on Marshall multiple organ failure clinical score) were assembled into predictive modules of clinical outcomes.  Of particularly interest, the down-regulation of MHC II expression within 48 hours of trauma and up-regulation of p38-MAPK within 100 hours of trauma were particularly robust independent predictors of negative clinical outcome in this patient sample.

Considering that up to 60% of late trauma mortality is caused by infections, sepsis, and multiple organ failure multiple organ, the management of these inflammation-related complications remains a major unmet medical need.  In particular, the ability to predict the individual patient clinical trajectory early during trauma treatment remains a significant challenge for the medical community.  Therefore, the prospect of using gene expression as a prognostic biomarker to manage the care of trauma patients is of particular significance.

Thierry Sornasse for Integrated Biomarker Strategy

Brain Imaging Biomarker of Pain: I see how you feel

Our perception of biomarkers tends to be limited to the realm of measures that provide information about disease and drug activity.  In fact, biomarkers can provide a means to assess additional biological processes relevant to patient well being such as anxiety and pain.  In paper published in the September 13^th issue of PLoS One (link), a team of the Department of Anesthesia, Stanford University describes a new functional MRI-based (fMRI) biomarker for the identification of pain.  Because the sensation of pain can be subjective and can occur in the absence of detectable injury, the standard for assessing pain is based on patient self report.  While this traditional measure is readily assessable, it does not differentiate between the sensory and the psychological components of pain perception.  In addition, patient self reported pain assessment is impossible in individuals who are not able to communicate.  Therefore, development of an objective biomarker of pain is of great interest to the medical community. 

The team at Stanford performed a pilot study involving 24 individuals who were monitored by fMRI while being subjected to painful and non-painful thermal stimuli.  Using the results from the first 8 volunteers, the team used Support Vector Machine learning to develop a predictive model that then validated on the remaining 16 individual volunteers.  In this setting, the model accurately identified the type of stimulus with 81 % accuracy.

While the size of this study is not sufficient to draw definitive conclusions, it is tempting to speculate that the future of pain management in patients who are unable to communicate may improve dramatically

Thierry Sornasse for Integrated Biomarker Strategy

Prognosis of conversion from MCI to AD: of verbal memory, brain volume, and CSF biomarkers

In the September 2011 issue of the Archives of General Psychiatry (reference), Dr. Goldberg and colleagues report the results of the first study that examined the respective predictive values of cognitive measures, brain imaging, and cerebrospinal fluid (CSF) biomarkers in determining the risk of conversion from Mild Cognitive Impairment (MCI) to Alzheimer’s disease (AD).

In contrast with the multiple recent publications derived from the Alzheimer’s Disease Neuroimaging Initiative about biomarkers in AD (ADNI; see earlier post), this work identified measures of delayed verbal memory (Logical Memory delayed recall and Auditory Verbal Learning Test delayed recall) as the most reliable predictors of progression from MCI to AD.  While brain volume assessed by MRI (Left middle temporal lobe thickness) was identified as an additional predictive factor, the levels of Ab42 and Tau in the CSF did not add significant predictive value to their model (systematic stepwise logistic regression).

In commentary provided to Medscape (link), the lead author urged caution in interpreting this finding by stating that “Biomarkers unarguably work. However, cognitive markers, which are less expensive and less invasive, also work and provide strong complementary information”.

In my mind, the question is not so much whether cognitive assessment tools work better than CSF biomarkers but more about the applicability of these findings to the general practice of medicine.  Indeed, while CSF biomarkers are objective measures, the results of even the best cognitive tests are partially subjective: the skills of the person administering the test can have an influence on the results.  Therefore, one can wonder if, in the hands of the average neurologist or neuropsychiatrist, the verbal memory testing would perform as well and would outperform the objective measure provided by CSF biomarkers.

Thierry Sornasse for Integrated Biomarker Strategy

FDA Pharmacogenomic Biomarkers in Drug Labels

The list of pharmacogenomic biomarkers included the labels of FDA approved drugs has grown substantially over the last 10 years.  The most recent update from the FDA (Table of Pharmacogenomic Biomarkers in Drug Labels; 08/25/2011) lists 109 pharmacogenomic biomarkers included in the labels of 97 drugs (the labels of some drugs such as Imatinib and Warfarin include more than one pharmacogenomic biomarkers).

From a regulatory perspective, these biomarkers can be included in different sections of the drug labels (e.g. box warning, contraindication, clinical pharmacology), informing the prescribing physicians and the patients about identification of responders / non-responders, avoiding adverse events, and optimizing drug dosage.  The label information about pharmacogenomic biomarker can describe:

• Drug exposure and clinical response variability
• Risk for adverse events
• Genotype-specific dosing
• Mechanisms of drug action
• Polymorphic drug target and disposition genes

Functionally, the majority of the pharmacogenomic biomarkers currently included in the label of approved drug fall into the category of safety and efficacy markers related to drug exposure due to altered drug metabolism.  Indeed, 60 of the 109 pharmacogenomic biomarkers belong to the liver cytochrome P450 enzymes (CYP) which play a critical role in drug metabolism.  Other functional variants of enzymes involved in drug metabolism such as dihydropyrimidine dehydrogenase (DPD) and thiopurine S-methyltransferase (TPMT) also fall into this category. 

Although still representing a minority of cases, the number of drug efficacy pharmacogenomic biomarkers included in cancer drug labels has been growing (i.e. response biomarkers, predictive biomarkers).  In general, these biomarkers are designed to assist in the prescription decision by testing for the presence of the drug target. 

Examples:

• Imatinib: C-kit, BCR-Abl, PDGFR
• Trastuzumab: Her2/neu
• Vemurafenib: BRAF
• Tositumomab: CD20

As the field of biomarker development in support of drug development evolves, it is expected that this list of pharmacogenomic biomarkers included in drug labels will grow substantially, making the promise of personalized medicine a reality.

Thierry Sornasse for Integrated Biomarker Strategy

Diagnostic On-the-Go: Cell phone, microchip, ELISA, and ovarian cancer

In the September 1^st issue of Lab on a Chip, Wang and colleagues report a proof-of-concept for an easily deployable, point-of-care diagnostic system for the detection of the ovarian cancer HE4 biomarker (reference).  The team combined a simple microchip-based ELISA platform with the imaging capability of modern portable phones.  Interestingly, the performances (sensitivity and specificity) of the portable phone camera appeared to be superior to a stand-alone CCD camera.

Although this work may seem anecdotal at first glance, it constitutes a valuable step towards increased diagnostic accessibility through the translation of a standard “high-tech” laboratory method to a “low-tech” broadly deployable platform.

Thierry Sornasse for Integrated Biomarker Strategy

Low Cost Blood Protein Detection System: Of Aptamers, Gold, and Resonance

In the September 1^st issue of Biomedical Optics Express (reference), Zheng and colleagues present a proof of concept study for a novel type of biosensor for the detection of proteins in blood.  Briefly, the team immobilized amine-terminated aptamers – artificial oligonucleotides engineered to bind specific ligands – onto a gold modified surface and used Surface Plasmon Resonance (SPR) to detect the binding of the ligand; in this case thrombin.  This prototype sensor showed good performances (sensitivity, linearity, and reversibility) for the intended ligand (thrombin), in the presence or absence of high levels (400 nM) of BSA, suggesting that this technology could be applied to direct detection of reasonably abundant factors in blood.

Considering the relative inexpensive nature of the manufacturing process of this new biosensor and the relative simplicity of SPR detection, it is tempting to speculate that this technology could solve the issue of cost for current and new blood diagnostics.  Time will tell if the reported performance of this prototype biosensor will be reproduced for other blood proteins.

Thierry Sornasse for Integrated Biomarker Strategy

Pairing GWAS with in-depth metabolomics: assigning functions to genetic variants

In the September 1^st issue of Nature (reference), scientists from the Helmholtz Zentrum Munchen Institute in Munich, Germany, the Wellcome Trust/Sanger Centre, King’s College, and Metabolon, Inc. present the most comprehensive Genome Wide Association Study (GWAS) aimed at identifying relationship between individual genetic variations and specific metabolic pathways.  Using ultra-high performance LC-MS and GC-MS, the levels of over 250 metabolites, representing over 60 metabolic pathways, were analyzed in serum samples from volunteers enrolled in the German KORA F4 study (n= 1768) and in the British TwinsUK study (n= 1052).  From these measures, over 37,000 metabolic traits (concentrations or ratios of metabolite pairs) were derived and their association with about 600,000 SNPs was assessed.  The team identified 37 independent genetic loci with genome-wide significant associations with metabolic traits, 23 of which represented novel associations.  Moreover, among these 37 genetic loci, 15 overlapped with known disease-associated genetic loci, shedding new light on possible new pathobiological mechanisms of diseases such as diabetes, kidney failure, venous thromboembolism, and coronary artery disease. 

This remarkable work represents a major evolution in the field of GWAS by providing a means to place genetic information within a functional biological context.  Indeed, despite identifying thousands of disease risk loci, most GWAS are cataloging exercises offering little or no information about the biological processes potentially associated with the identified genetic variants.  

Thierry Sornasse for Integrated Biomarker Strategy