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 DOI: 10.1177/2168479013498386

2013 47: 632 originally published online 8 August 2013Therapeutic Innovation & Regulatory ScienceJanet Woodcock, George Vradenburg and Maria Isaac

Timothy Nicholas, Dan Polhamus, B. Steven Angersbach, Nandini Raghavan, Gary Romano, Klaus Romero, Leslie Shaw,Brian Corrigan, Mark Forrest Gordon, Clifford R. Jack, Jr, Russell Katz, Veronika Logovinsky, Andrew Satlin, Ken Marek, Diane Stephenson, Enrique Aviles, Lisa J. Bain, Martha Brumfield, Maria Carrillo, Thomas A. Comery, Carolyn Compton,

Drug Development for Neurodegenerative DiseasesCoalition Against Major Diseases: Precompetitive Collaborations and Regulatory Paths to Accelerating

  

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Therapeutic and Regulatory Innovation

Coalition Against Major Diseases:

Precompetitive Collaborations

and Regulatory Paths to Accelerating

Drug Development for

Neurodegenerative Diseases

Diane Stephenson, PhD1, Enrique Aviles, BS1, Lisa J. Bain2,

Martha Brumfield, PhD1, Maria Carrillo, PhD3,

Thomas A. Comery, MS4, Carolyn Compton, MD, PhD5,

Brian Corrigan, PhD4, Mark Forrest Gordon, MD6,

Clifford R. Jack Jr, MD7, Russell Katz, MD8,

Veronika Logovinsky, MD, PhD9, Andrew Satlin, MD9,

Ken Marek, MD10, Timothy Nicholas, PhD4, Dan Polhamus, PhD11,

B. Steven Angersbach, MBA1,*, Nandini Raghavan, PhD12,

Gary Romano, MD, PhD12, Klaus Romero, MD, MS1, Leslie Shaw, PhD13,

Janet Woodcock, MD14, George Vradenburg, JD15, and

Maria Isaac, MD, PhD16

1 Critical Path Institute, Coalition Against Major Diseases, Tucson, AZ, USA2 Independent science writer, Elverson, PA, USA3 Alzheimer’s Association, Chicago, IL, USA4 Pfizer Inc, New London, CT, USA5 Arizona State University, Phoenix, AZ, USA6 Boehringer Ingelheim Pharmaceuticals Inc, Ridgefield, CT, USA7 Mayo Clinic, Rochester, MN, USA8 Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA9 Eisai Inc, Woodcliff Lake, NJ, USA

10 Institute for Neurodegenerative Disorders, New Haven, CT, USA11 Metrum Research Group, Tariffville, CT, USA12 Johnson & Johnson, Raritan, NJ, USA13 Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA14 US Food and Drug Administration, Silver Spring, MD, USA15 USAgainst Alzheimer’s, Washington, DC, USA16 European Medicines Agency (EMA), London, UK

*Current affiliation: Synergia Consulting, MI, USA

The views expressed in this article are the personal views of the author(s) and may not be understood nor quoted as being made on behalf of or reflecting the

position of EMA or one of its committees or working parties or any of the national agencies; the views presented in this article do not necessarily reflect those of

the US Food and Drug Administration.

Submitted 29-Apr-2013; accepted 21-Jun-2013

Corresponding Author:

Diane Stephenson, Coalition Against Major Diseases (CAMD), Critical Path Institute, 1730 East River Road, Tucson, AZ 85718, USA.

Email: DStephenson@c-path.org

Therapeutic Innovation& Regulatory Science47(6) 632-638ª The Author(s) 2013Reprints and permission:sagepub.com/journalsPermissions.navDOI: 10.1177/2168479013498386tirs.sagepub.com

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Abstract

Precompetitive collaborations have been successful in several disease areas and industries. Such collaborations are critical to address

the gaps and challenges in therapeutic development for chronic neurodegenerative diseases. On November 5, 2012, members of the

scientific community, advocates, regulators, industry, and government officials met at the US Food and Drug Administration to

develop tools to expedite drug development and maximize the potential for success in future drug trials for Alzheimer disease and

Parkinson disease. The meeting established that multiple collaborative approaches are essential for accelerating drug development.

Such approaches include precompetitive data sharing, regulatory qualification of biomarkers and clinical outcome assessments,

implementation of data standards, and development of quantitative drug disease trial models. While challenges to collaboration

among industry partners are formidable, they are not insurmountable. The Coalition Against Major Diseases (CAMD) has several

positive examples to highlight. This review represents proceedings from CAMD’s annual conference and discusses the key themes

that are being advanced by the Critical Path Institute.

Keywords

Alzheimer disease, Parkinson disease, disease modeling, regulatory qualification, biomarkers

Introduction

The Coalition Against Major Diseases (CAMD) is 1 of 7 pre-

competitive consortia of the Critical Path Institute (C-Path),

which was formed several years ago as part of the US Food and

Drug Administration’s (FDA’s) Critical Path Initiative.1

CAMD is focused on accelerating drug development for

patients with chronic neurodegenerative disease, namely, Alz-

heimer disease (AD) and Parkinson disease (PD), by advancing

drug development tools for evaluating drug efficacy, conduct-

ing clinical trials, and streamlining the process of regulatory

review.2 CAMD has 4 major areas of focus: (1) qualification

of biomarkers, (2) development of common data standards,

(3) creation of integrated databases for clinical trials data, and

(4) development of quantitative drug-disease trial models.

The year 2012 was one of both exciting advances and disap-

pointments for AD and PD drug development in general and for

C-Path/CAMD in particular. Although results from the highly

anticipated AD clinical trials of bapineuzumab and solanezu-

mab were disappointing, there was good news in the form of

a pledge of US$130 million for AD research from the Obama

administration; the regulatory approval of florbetapir (Amyvid;

Eli Lilly, Indianapolis, Indiana) for brain imaging of individu-

als being evaluated for AD; research indicating that a single

mutation in the gene for the amyloid precursor protein could

confer lifetime protection against AD by affecting the activity

of BACE (b-secretase)3; continued brisk enrollment of subjects

in the Parkinson’s Progression Markers Initiative (PPMI);

progress in the development of treatments for late stage PD;

and the development of an induced pluripotent stem cell model

to screen for novel therapies in the future.4

At CAMD, the Biomarker Group met with the Biomarker

Qualification Review Team (BQRT) at the FDA in February

2012. In June, C-Path entered a partnership with the Clinical

Data Interchange Standards Consortium (CDISC) to establish

the Coalition for Accelerating Standards and Therapies

(CFAST). This program is timely because the FDA has man-

dated the use of clinical data standards by 2017. The model for

creating and maintaining data standards was established by

CAMD in 2011 with the creation of the first and largest open

database of CDISC aggregated clinical trial data for AD.

C-Path is also working with CDISC to develop standards for

PD and other diseases. Also in 2012, the Modeling and Simula-

tion Team finalized a submission to FDA that represents the

first clinical drug disease trial model submitted for a regulatory

decision.

On November 5, 2012, the CAMD annual workshop at the

FDA’s White Oak Campus brought together experts from

industry and regulatory agencies to review the accomplish-

ments of CAMD and explore how the tools being developed

at CAMD will be used to accelerate drug development in the

future.i

Disease Modeling

Disappointing results in recent trials point to the need for better

modeling of the disease to maximize the likelihood of success-

ful trials in the future. By applying model-based approaches

using historical data, investigators have been able to illuminate

factors, such as selection bias, that may help explain recent trial

failures. For example, in post hoc analyses of phase 2 data from

a recently evaluated candidate immunotherapy, an abnormal

placebo response in APOEe4 noncarriers resulted in an appar-

ent treatment effect.5 However, when historical placebo data

are overlaid on these data, the placebo response in noncarriers

appears to be an outlier. Had modeling using historical data

been available at the time, it might have tempered enthusiasm

to move to the phase 3 study, which eventually cost over half a

billion dollars but failed to meet its primary end point.

Stephenson et al 633

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In contrast, the development of another anti-amyloid mono-

clonal antibody was terminated after phase 2 when a probabil-

ity of success approach, combined with modeling of interim

data, failed to establish confidence that the drug had a signifi-

cant treatment effect.6

Establishing a historical perspective for modeling of this

type requires a structure for integrating the data as well as the

creation of standardized data. Both of these projects were

undertaken by CAMD through the development of two tools:

the CAMD AD trial simulation tool (TST) and the CAMD

Database, which includes control arm (placebo) data from

about 6500 subjects enrolled in 24 clinical trials from 9 CAMD

member companies.

TST is a disease-drug-trial model for AD using patient data

from 2223 patients with mild and moderate AD whose data

were available in the CAMD AD trial database, data from the

Alzheimer’s Disease Neuroimaging Initiative (ADNI), and

summary data reported in the literature.7 These data were

remapped to conform to the standards established by the

CDISC and then pooled, leading to the creation of an in silico

modeling tool currently under review by the FDA. The model

was built using the Alzheimer’s Disease Assessment Scale cog-

nitive subscale (ADAScog) data from mild to moderately ill

patients, enabling characterization of the longitudinal progres-

sion of the disease, particularly the nonlinear behavior of the

ADAScog. The model allows the user to specify hypothesized

drug effects, trial designs, and various model components,

simulating different trial designs (eg, parallel, crossover,

delayed start), patient populations, drug effects, dropout prob-

abilities, and statistical tests. For example, in designing a trial

of a disease-modifying therapy, the user can simulate parallel

and delayed-start designs and adjust the sample size and dura-

tion to optimize the design of the trial. The TST package is

designed to be comprehensive, flexible, and user-friendly, and

it is available online.8

Clinical disease progression models such as TST are useful

for mid- to late-phase drug development. For early phase mod-

eling, a systems pharmacology model that is more biologically

focused can be used for hypothesis generation, target identifi-

cation, and better understanding of the appropriate study pop-

ulation, magnitude of effect necessary, dosing regimen (dose,

timing, and duration), and quantification of an early effect

(eg, with biomarkers). Systems pharmacology models provide

sponsors with increased confidence for decision making at an

early stage of development before large investments have been

made. For example, using this approach to model a trial that

would test the amyloid cascade hypothesis in a reasonable

amount of time would provide a quantitatively defined estimate

of how strong a treatment effect would be needed and whether

drug candidates in development have sufficient potency to jus-

tify a clinical trial.

Through programs such as the FDA’s drug development

tool qualification, the regulatory community has signaled

readiness to use models and simulations in the review of prod-

ucts for market approval. The FDA’s and the European Medi-

cines Agency’s (EMA’s) guidance will be particularly

important in establishing whether the field needs to settle on

a single model or whether multiple models are acceptable.

Finding convergence among the different models would be

helpful, as would development of models that more seamlessly

enable translation of findings from the preclinical to late-stage

clinical phases. Coalitions, such as those built by C-Path, are

instrumental in this effort.

Merging biomarkers into these models could substantially

increase the models’ usefulness, particularly with multiple bio-

markers that reflect different aspects of the disease process;

however, this effort will require more data. As the field moves

increasingly toward treating earlier stages of disease, the use of

biomarkers as end points may become more important, since

the currently used clinical end points (ie, ADAScog) are insuf-

ficiently sensitive to change in the early stages.

Biomarker Qualification and Regulatory Strategy

The application of biomarkers as tools to better understand the

pathophysiological characteristics of AD and develop new

treatments for this disease has greatly increased since the

1980s, when studies first suggested that certain proteins in the

cerebrospinal fluid (CSF) might be reliable indicators of AD.9

Thanks largely to ADNI, the field has now coalesced around

the idea that several biofluid and imaging biomarkers may

serve as a proxies for AD and correlate with neuropathological

diagnoses at autopsy. In 2010, Jack et al10 proposed a hypothe-

tical model describing the temporal ordering of AD biomar-

kers. Since then, the model has been validated with empirical

data from numerous studies.11-15 All of these studies point to

the fact that amyloid biomarkers (CSF Ab42, and amyloid posi-

tron emission tomography [PET] imaging) become abnormal

first; these are followed by hypometabolism (fluorodeoxyglu-

cose-PET) and markers of neurodegeneration (CSF total-tau

and phosphorylated-tau and magnetic resonance imaging

[MRI] measures of hippocampal atrophy) and finally by cogni-

tive symptoms. These data further suggest that a biomarker

profile consisting of multiple measures may be used to predict

disease progression. Either individually or in combination, bio-

markers are already being used for patient selection in clinical

trials. In the future, biomarkers may also represent outcome

measures. To realize the promise of biomarkers, however,

requires more data from heterogeneous populations, standardi-

zation and harmonization of assays, and determination of vali-

dated cut points.

634 Therapeutic Innovation & Regulatory Science 47(6)

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Biomarkers have largely been used to guide decision mak-

ing on lead candidate prioritization and dose selection; how-

ever, more recently, regulatory agencies in Europe and the

US have introduced the process of qualification to streamline

drug approval by prespecifying that a biomarker has demon-

strated adequate reliability, sensitivity, and specificity for a

specific context of use. The context of use could be (1) enrich-

ment, both prognostic and predictive (although if the biomarker

is proximal to disease biology and is part of the biological cas-

cade, it may be difficult to separate the two); (2) naturalistic

progression of the disease and how drugs might affect that pro-

gression; and (3) linkage to clinical end points. Thus, the qua-

lification of a biomarker means not only that there is a reliable

way of measuring the entity but also that an algorithm has been

developed for applying that measurement in the decision-

making process. Qualification is different from validating a

surrogate biomarker. Qualification denotes that a biomarker

has been approved to perform a certain task, such as identifying

a subject with AD, while validation indicates that an interven-

tion’s effect on a surrogate reflects a clinical effect.

Regulatory agencies evaluate a biomarker for qualification

based on multiple studies rather than a single drug trial. Once

a biomarker has received regulatory qualification, sponsors

using this biomarker in a drug trial will not be required to pres-

ent data validating the biomarker. Qualification thus reduces

the cost and length of drug trials and spreads the burden of col-

lecting data across multiple stakeholders. Collaborations and

partnerships are encouraged in the qualification process and

further limit individual risk and expense. For example, CAMD

submitted a dossier to the EMA requesting a qualification opin-

ion on the use of hippocampal volume as a biomarker for

enriching clinical trials in subjects with mild cognitive impair-

ment,16 and the qualification opinion was released in Novem-

ber 2011.17

The steps required to qualify a biomarker vary among differ-

ent regulatory agencies.16,18 For both EMA and the FDA,

although literature reviews are an important component of the

submission package, qualification requires more than a meta-

analysis of literature data. Frequently, de novo data analyses

are also requested—for example, if the regulatory agency

deems that selection bias has not been accounted for in the pub-

lished literature. The FDA and EMA differ with respect to the

precision of data required and the process of updating qualifi-

cation opinions. For example, the EMA has been open to qua-

lifying a biomarker for certain contexts of use even in the

absence of consensus in the field on important aspects such

as standardization and cut points, with the understanding that

the guidance can be updated as new data are acquired. CAMD

is working to align the qualification process to ensure that data

submitted to one regulatory body would also meet the require-

ments of another agency.

At the time of the workshop, EMA had qualified CSF bio-

markers for drugs affecting amyloid burden in the predementia

stage of AD,19 low hippocampal volume by MRI for regulatory

clinical trials in predementia AD,7 PET amyloid imaging for

enrichment in predementia AD trials,20 and CSF Ab42 and

t-tau, and/or amyloid PET imaging for enrichment in trials for

mild to moderate AD. The FDA had not yet qualified any AD

biomarkers.

Developing a Clinical/Cognitive Composite Score toIdentify Predementia AD

As the field moves toward conducting trials in earlier stages of

disease, there is a need for a clinical outcome measure sensitive

to disease progression and treatment effect in individuals with

predementia AD. Thus, pharmaceutical companies have been

working collaboratively in precompetitive space to identify key

items that could be combined in a composite outcome measure

for clinical trials. At a data mining session organized by the

ADNI Private Partner Scientific Board, 5 companies using dif-

ferent approaches and methods presented data suggesting con-

vergence on a set of measures. Subsequently, this effort was

carried forward by CAMD with the collection of additional

data aimed at deriving a composite clinical outcome tool.

One of the companies involved in this effort, Eisai Inc, pre-

sented its findings at the Clinical Trials in Alzheimer’s Disease

meeting21 and at the CAMD annual meeting. To represent the

heterogeneity of individuals with MCI, the company combined

placebo data from 4 studies to build the composite tool and then

assessed the behavior of the tool in multiple data sets from

patients with mild AD. The new composite combines items

from the ADAScog, the Mini-Mental State Exam (MMSE), and

the Clinical Dementia Rating scale Sum of Boxes (CDR-SB)

and is scaled to 100 for convenience. The composite showed

improved sensitivity to decline and responsiveness to current

treatments. Thus, it allows for substantially smaller sample

sizes per arm in clinical trials. Because this tool combines glo-

bal and cognitive items, it may be useful as a single clinical

outcome.

Participants at the annual meeting discussed whether

CAMD should lead the next phase of development of this com-

posite by initiating a formal qualification process, preferably

with both FDA and EMA concurrently. Having this tool named

in a guidance would give existing sponsors a path forward and

new tool developers a target for developing improved mea-

sures. The FDA recently issued a draft guidance on approaches

to advance therapies for early AD and indicated that CDR-SB

and/or composite score approaches may be relevant to consider

as primary end points in early symptomatic AD.22 Although

CDR-SB combines cognitive and functional assessments, there

is concern that on its own it may lack sufficient sensitivity to

Stephenson et al 635

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assess the early stages of disease or to detect the effects of drug

intervention.

Accelerating Drug Development for Parkinson’s Disease

Like AD, PD is a heterogeneous disease characterized by slow,

progressive neurodegeneration affecting multiple domains.

There is no approved disease-modifying therapy for PD or

AD. Possible reasons for lack of success in drug development

for PD mirror those in AD: a lack of well-validated drug targets

and an uncertainty regarding target populations, drug dose,

duration of treatment, and trial design. For research in PD and

AD, there are similar needs to advance biomarkers that reflect

pathophysiological characteristics of the central nervous sys-

tem compartment (eg, CSF, imaging).

In comparison to drug development for AD, that for PD has

benefitted from a better understanding of the pathophysiologic

mechanisms underlying the disease as well as the availability

of a clearer set of targets. Single photon emission computed

tomography (SPECT) and PET neuroimaging, in particular,

have proven useful in detecting the degeneration of dopaminer-

gic neurons in the brain.23 Three different measurements—

DAT (dopamine transporter) by PET or SPECT, VMAT2

(vesicular monoamine transporter 2) by PET, and dopamine

by fluorodopa PET—show robust reduction in the number of

these neurons at the time of diagnosis but are insufficient to

assess progression over time. Thus, there is an urgent need for

other biomarkers, such as markers of a-synuclein, tau, and

leucine-rich repeat kinase 2 (LRRK2). Biomarkers could

improve diagnostic accuracy, assessment of disease progres-

sion, identification of patients in the earliest stages of disease,

and enrichment of clinical trials with likely responders.24 Sev-

eral clinical biomarkers have shown promise, including rapid

eye movement behavior disorder, bowel dysfunction, olfactory

deficits, and mood disorders,25 although all of these markers

lack specificity for PD. Haas et al26 have developed an algo-

rithm to search for biomarkers in patients with premotor PD;

the algorithm starts with genetic and clinical markers and then

proceeds to imaging and biochemical biomarkers. CAMD is

advancing through FDA’s biomarker qualification program the

use of DAT imaging as a biomarker to enrich clinical trials in

patients with early-onset PD.27 In addition, the PPMI, a public-

private partnership that aims to develop progression biomar-

kers, has begun enrolling subjects in the prodromal, premotor

stages of disease using a positive DAT scan as an inclusion

criterion.

As clinical trials for PD treatments move toward early dis-

ease, the need for a revision to the Unified Parkinson Disease

Rating Scale (UPDRS) has become more apparent. The Move-

ment Disorders Society (MDS) has undertaken a project to

revise the scale, incorporating nonmotor experiences of daily

living (eg, cognitive impairment, hallucinations and psychosis,

depressed mood, anxious mood, apathy, features of dopamine

dysregulation syndrome, nighttime sleep problems, daytime

sleepiness, pain and other sensations, urinary problems, consti-

pation problems, lightheadedness on standing, and fatigue) and

motor experiences of daily living (eg, speech, salivation and

drooling, chewing and swallowing, eating, dressing, hygiene,

handwriting, hobbies, turning in bed, tremor, walking and bal-

ance, freezing, and getting out of bed, car, or deep chair). The

new scale, called MDS-UPDRS, has undergone clinimetric

assessment and validation28,29 and is now poised to be sub-

mitted for qualification to regulatory agencies. PPMI has

already incorporated the MDS-UPDRS into its studies, which

should expedite acceptance of the revised scale by other spon-

sors and clinicians, although there are risks to sponsors who

adopt the new scale prior to qualification. Participants at the

CAMD annual meeting suggested forming a partnership

between MDS and CAMD to accelerate the process of prepar-

ing and advancing a formal qualification of MDS-UPDRS

through the FDA and EMA clinical outcome assessment tool

qualification program (http://www.fda.gov/Drugs/Develop-

mentApprovalProcess/DrugDevelopmentToolsQualification-

Program/ucm284077.htm).

In addition to making efforts to qualify a DAT imaging bio-

marker for patient enrichment in PD clinical trials,27 CAMD

has collaborated with CDISC on the release of PD therapeutic

area specific data standards (http://www.cdisc.org/therapeutic)

and is considering development of a quantitative drug-disease

trial model for PD, similar to that developed for AD.

Conclusions

With concerns building throughout the AD and PD research

communities about the failure to develop and deliver disease-

modifying therapies, as well as the paucity of new drugs for

symptomatic benefit, CAMD has successfully facilitated colla-

borative efforts between industry, academia, and the regulatory

community to develop tools aimed at expediting drug develop-

ment and maximizing the potential for success in future drug

trials. Already, these efforts have led to the submission and

acceptance of a qualification opinion by the EMA on the use

of hippocampal volume as a biomarker for enriching MCI

clinical trials with appropriate subjects, the establishment of

a database incorporating placebo data from 6500 subjects, and

the development and submission to the FDA of a disease-drug-

trial model for AD. The success of these projects builds on and

complements the work of other public-private partnerships

such as ADNI and PPMI, further demonstrating that stake-

holders from across the drug development spectrum are capa-

ble of working in the precompetitive space to share data and

align on strategies that may benefit not only their individual

636 Therapeutic Innovation & Regulatory Science 47(6)

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companies and organizations but, more important, the growing

number of patients affected by these devastating neurodegen-

erative diseases.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to

the research, authorship, and/or publication of this article.

Funding

Critical Path Institute’s Coalition Against Major Diseases is supported

by the US Food and Drug Administration (grant U01FD003865) and

Science Foundation Arizona (grant SRG 0335-08).

Note

i Meeting panelists: Brian Corrigan (Pfizer Inc), Yaning Wang (FDA),

Marc Walton (FDA), Issam Zineh (FDA), Rusty Katz (FDA), Mahesh

Samtani (Johnson & Johnson), Cristina Sampaio (CHDI Foundation

Inc), Maria Isaac (European Medicines Agency), Maria Carrillo

(Alzheimer’s Association), Anne Fagan (Washington University),

Bob Dean (Eli Lilly & Company), Les Shaw (University of Pennsyl-

vania), Derek Hill (Ixico), Clifford R. Jack Jr (Mayo Clinic), Susie

McCune (FDA), Abe Tzou (FDA), Andy Satlin (Eisai Inc), Veronika

Logovinsky (Eisai Inc), Laurie Burke (FDA), Kristin Hannesdottir

(AstraZeneca), Paul Maruff (Cogstate Ltd), Richard Meibach

(Novartis Pharmaceuticals), Amy Rick (Parkinson’s Action Net-

work), Marg Sutherland (National Institute of Neurological Disor-

ders and Stroke), Ken Marek (Molecular NeuroImaging, LLC),

Mark Gordon (Boerhinger Ingelheim), Christian Graff (FDA).

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