Editorial
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
Public--private partnerships to revitalize psychiatric drug discovery 1.
Introduction
2.
Selected case examples
3.
Expert opinion
Linda S Brady† & William Z Potter †
National Institute of Mental Health, Division of Neuroscience and Basic Behavioral Science, Bethesda, MD, USA
Introduction: Precompetitive public--private partnerships (PPPs) have the potential to improve psychiatric drug discovery by addressing gaps in the research and development pipeline such as the identification and validation of new targets, models, biomarkers and disease phenotyping. PPPs are a model to strategically bring together expertise, in-kind support and funding from multiple public and private sector partners. Areas covered: This editorial describes selected case examples of established and emerging public--private consortia in the United States and Europe that provide tools, methods or resources to accelerate central nervous system (CNS) drug discovery. The authors provides a listing of public--private consortia projects that focus on the CNS, the stage of the drug discovery pipeline that they address, diseases, deliverables provided and current consortia partners. Expert opinion: Some of the projects undertaken by PPPs in the area of CNS drug discovery and development are beginning to make tools, resources and data publicly available. Only a few PPPs have delivered enough to extract lessons learned. These include building alignment across a wide group of stakeholders, engaging advocacy groups and funding commitments for a minimum of 5 years. Keywords: Alzheimer’s Disease Neuroimaging Initiative, autism spectrum disorder, biomarkers, Biomarkers Consortium, cellular models, consortia, disease phenotyping, major depressive disorder, psychiatric drug discovery, psychiatric genetics, public--private partnerships, schizophrenia Expert Opin. Drug Discov. (2014) 9(1):1-8
1.
Introduction
Psychiatric disorders are the leading causes of disability worldwide [1]. There is an urgent need for new treatments to reduce the severity of symptoms, improve functional outcomes and preempt the developmental trajectory of disease, especially for schizophrenia and autism spectrum disorders (ASD). Despite the unmet medical need and market potential, many large pharmaceutical companies have recently reduced or terminated their programs in psychiatric drug development. The lack of new validated targets, generally applicable translatable animal models and biomarkers of disease, coupled with an increased failure rate of clinical trials, have contributed to industry’s decreased investment in psychiatric drug discovery [2,3] while stimulating the creation of public--private partnerships (PPPs) or consortia to address these challenges. PPPs can support precompetitive research to increase the rate of validating or rejecting novel mechanisms and potentially share the risk of developing novel therapies. There is no single model for PPPs, made clear in the following case examples of efforts to generate tools, methods and resources to address challenges in psychiatric and, more broadly, central nervous system (CNS) drug
10.1517/17460441.2014.867944 © 2014 Informa UK, Ltd. ISSN 1746-0441, e-ISSN 1746-045X All rights reserved: reproduction in whole or in part not permitted
1
L. S. Brady & W. Z. Potter
discovery (see Table 1 for a listing of public--private consortia relevant to CNS drug discovery).
2.
Selected case examples
2.1
Established consortia Alzheimer’s Disease Neuroimaging Initiative
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
2.1.1
The National Institute of Aging (NIA) established the Alzheimer’s Disease Neuroimaging Initiative (ADNI) [4] consortium to identify biomarkers for the early detection and tracking of Alzheimer’s disease (AD), with funding provided by government (NIA), 13 pharmaceutical companies, and 2 foundations, and with involvement of the Food and Drug Administration (FDA) and other regulatory agencies (Table 1). The Foundation for NIH (FNIH) [5], a nonprofit organization, coordinates the private funding that is combined with the roughly 60% from NIA which sponsors ADNI operating through a funded academic network. Through its steering committees, ADNI has developed optimized, standardized methods for collection of plasma and cerebrospinal fluid (CSF) samples, imaging, clinical and neuropsychological data that link to a multisite, worldwide effort initially coordinated through the Alzheimer’s Association [6]. Of note and more broadly, ADNI has benefitted from the active involvement of advocacy groups that have strong scientific arms, substantial resources and deep commitment to development of novel pharmacological treatments. All data are publicly accessible, and hundreds of papers have resulted.
Biomarkers Consortium, Neuroscience Steering Committee
2.1.2
The Biomarkers Consortium [7] is a PPP that uniquely resides within the FNIH with an executive committee with representatives from government (NIH and FDA), industry, academia and nonprofit organizations. The Neuroscience Steering Committee [8] solicits and develops proposals to discover, develop and qualify biomarkers to support drug development in the neuroscience therapeutic area. With approval by its executive committee, the FNIH raises funds from non-government sources and actively manages funded projects. To date, the majority of funded neuroscience projects have focused on AD, leveraging the infrastructure and samples generated by ADNI [9-11]. It has been much more difficult to attract the interest of industry and nonprofit partners for funding of biomarker projects that focus on psychiatric diseases or on biomarker technologies that are not directly relevant to CNS projects in the pharma discovery pipeline. Examples of projects for which funding could not be raised include multimodal markers to predict response to antidepressants, development of signal processing strategies for analysis of arterial spin labeling MRI data and longitudinal test-retest performance of FDG-PET in multicenter studies. 2
NIH-Industry Program, discovering new therapeutic uses for existing molecules
2.1.3
The new therapeutics uses [12] program is an example of a PPP to de-risk targets and identify new indications through drug repositioning with NIH solicitation and funding of proposals for new clinical trials. It is a model in which pharma identifies compounds for inclusion in the program and provides expertise, access to regulatory documents and clinical supply of compound and NIH oversees funded studies [13,14]. Innovative Medicines Initiative, NewMeds Consortium
2.1.4
NewMeds [15] (Novel Methods Leading to New Medications in Depression and Schizophrenia) is a joint effort between the European Union, which provides direct funding to academic centers, and the European Federation of Pharmaceutical Industries and Associations (EFPIA), which provides ‘in-kind’ contributions without funding. The consortium includes 13 pharmaceutical companies, 7 academic teams and 3 small businesses [16]. It has, for instance, created a large database of schizophrenia clinical trial data contributed by industry (> 20,000 patients in > 25 countries) and analyzed by academia, with findings on the impact of operational criteria for negative symptom change that should prove very useful in designing future trials [17]. Psychiatric Genomics Consortium, genetic risk architecture
2.1.5
The Psychiatric Genomics Consortium (PGC) [18] was initiated by a small group of investigators (academic and NIMH), in 2007, to address the challenge in psychiatric genetics of detecting risk gene variants of small effect [19]. The PGC quickly expanded to a large, international confederation of scientists focused on five serious mental illnesses. The group is conducting meta-analyses of PGC genome-wide association (GWA) data from 170,000 cases and controls [20]. Core analyses, infrastructure and genotyping are supported by public and private partners from multiple sectors (Table 1). The PGC is developing a ‘PsychChip’ that will be used to genotype 90,000 individuals and be available from Illumina by the end of 2013. Emerging consortia Induced pluripotent stem cell technologies for modeling human diseases
2.2
2.2.1
Following a workshop in April 2012, NIMH issued a funding announcement to initiate the National Cooperative Reprogrammed Cell Research Groups (NCRCRG) [21] to study mental illness, to establish academic--industry partnerships, to facilitate the use of patient-derived reprogrammed cells (e.g., induced pluripotent stem cells [iPSCs] and induced neuronal cells to study the molecular and cellular basis of mental illness), to identify novel targets for drug discovery and to assess candidate drugs in iPSC assays [22].
Expert Opin. Drug Discov. (2014) 9(1)
Expert Opin. Drug Discov. (2014) 9(1)
ASD
AD, anxiety, cancer and various disorders
Assays, disease models, biomarkers, phenotyping and target identification
Disease models and drug repositioning Assays, cross-species phenotyping and target identification
European Autism Interventions -- A Multicentre Study for Developing New Medications (EU-AIMS) [30] and IMI [31]
Medical Research Council (MRC)/AstraZeneca Mechanisms of Disease Initiative [32]
NewMeds [15] and IMI
Models, biomarkers, genetic predictors of drug response and standardized methods for brain imaging
Disease models, preclinical and clinical proof of concept of selected mechanisms in new disease areas
Cellular assays, animal models, biomarkers and risk genes
Biomarkers, disease models, nonclinical and clinical safety biomarkers, patient-reported outcomes measures
Validated biomarkers, testing of biomarker tools and technologies and standardized methods for brain imaging
CSF, plasma samples, standardized methods for brain imaging, cognitive testing and LONI database
Deliverables
Academia, advocacy groups, EFPIA, EMA, EU
Academia, AstraZeneca, MRC
Academia, biotech, Autism Speaks, EFPIA, EMA, EU
Academia, FDA, EMA, PMDA, foundations and pharma
Academia, BIO, CMS, FDA, foundations, NIH, PhRMA
Academia, Alzheimer’s Association, Alzheimer’s Drug Discovery Foundation, CIHR, FDA, GE Healthcare, NIA/NIH, pharma
Current consortia partners (funding, programmatic or strategic partners or sectors)
BIO: Biotechnology Industry Organization; CIHR: Canadian Institute for Health Research; CMS: Centers for Medicare and Medicaid Services; EC: European Commission; EFPIA: European Federation of Pharmaceutical Industries and Associations; EMA: European Medicines Agency; EU: European Union; iPSCs: Induced pluripotent stem cells; NCATS: National Center for Advancing Translational Sciences; NIA: National Institute on Aging; NIMH: National Institute of Mental Health; PhRMA: Pharmaceutical Research and Manufacturers of America; PMDA: Pharmaceutical and Medical Devices Agency Japan.
Depression and schizophrenia
AD, major depressive disorder (MDD), PD, multiple sclerosis (MS) and other diseases
CNS disorders
Biomarkers
Disease models, biomarkers, drug safety and outcome measures
AD
Disease(s)
Biomarkers
Stage(s) of pipeline
Critical Path Institute (C-Path) [26] consortia: Coalition Against Major Diseases (CAMD) [27]; Patient-Reported Outcome (PRO) [28]; Predictive Safety Testing Consortium (PSTC) [29]
Biomarkers Consortium [7], Neuroscience Steering Committee [8] and FNIH
Established consortia Alzheimer’s Disease Neuroimaging Initiative [4] and FNIH [5]
Public--private consortia
Table 1. Examples of precompetitive public--private consortia that provide tools, methods or resources for enabling CNS drug discovery and development pipeline.
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
PPPs to revitalize psychiatric drug discovery
3
4
Expert Opin. Drug Discov. (2014) 9(1)
PD
AD and MCI
Attention-deficit/hyperactivity disorder (ADHD), ASD, bipolar disorder, MDD and schizophrenia
Animal models and biomarkers Biomarkers
Target identification and validation
Parkinson’s Progression Markers Initiative (PPMI) [35] and MJFF
PharmaCog [36] and IMI
PGC [18]
Risk genes, meta-analyses of genotypes from 170,000 cases and controls, open source philosophy and ‘PsychChip’
Matrix of biomarker tools to predict cognitive properties of new drug candidates, for use in disease models and in clinical trials
Animal models, biomarkers, CSF, plasma samples and standardized methods for brain imaging
Disease models, preclinical and clinical proof of concept of selected mechanisms in new disease areas
Assays, disease models and preclinical proof of concept of selected compounds
Deliverables
Academia, Hersenstichting Netherland, Netherlands Genetic Cluster Computer, NIMH, One Mind for Research, pharma (core analyses and infrastructure); Broad/ Stanley Center, deCODE Genetics, EU, Genome Canada, NIMH, pharma, Wellcome Trust Case Control Consortium and others (GWA genotyping)
Academia, Alzheimer Europe, EFPIA, EMA, EU
Academia, advocacy groups, GE Healthcare, MJFF, pharma
Academia, NCATS/NIH, pharma
Academia, NIMH/NIH, biotechnology, pharma
Current consortia partners (funding, programmatic or strategic partners or sectors)
BIO: Biotechnology Industry Organization; CIHR: Canadian Institute for Health Research; CMS: Centers for Medicare and Medicaid Services; EC: European Commission; EFPIA: European Federation of Pharmaceutical Industries and Associations; EMA: European Medicines Agency; EU: European Union; iPSCs: Induced pluripotent stem cells; NCATS: National Center for Advancing Translational Sciences; NIA: National Institute on Aging; NIMH: National Institute of Mental Health; PhRMA: Pharmaceutical Research and Manufacturers of America; PMDA: Pharmaceutical and Medical Devices Agency Japan.
AD, Duchenne muscular dystrophy, schizophrenia and various disorders
Psychiatric disorders, drug addiction and alcohol addiction
Disease(s)
Drug repositioning
Assays, disease models, target identification and drug discovery
Stage(s) of pipeline
New Therapeutic Uses [12]
National Cooperative Drug Discovery/Development Group (NCDDG) [33] for the Treatment of Mental Disorders, Drug or Alcohol Addiction: Functional Selectivity: A Novel Approach for CNS Drug discovery [34]
Public--private consortia
Table 1. Examples of precompetitive public--private consortia that provide tools, methods or resources for enabling CNS drug discovery and development pipeline (continued).
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
L. S. Brady & W. Z. Potter
Expert Opin. Drug Discov. (2014) 9(1)
AD, rheumatoid arthritis, schizophrenia prodrome and type 2 diabetes
Biomarkers and target validation Diagnosis and Biomarkers
NIH-Industry Target Validation Consortium (workshop [40])
TRIMAGE [41]
Disease signatures using PET/MR, fMRI/EEG, PET/MR/EEG and trimodality imaging hardware
Biomarkers, biosamples, genetic risk factors and target validation in human subjects
Assays, biosamples, disease models, methods and technologies to differentiate iPSCs into neuronal or glial cells
Clinical validation of new disease mechanisms or targets and open access data model
Assays, protein structures, epigenetic targets, chemical and biological probes and open access data model
Biomarkers, biosamples, disease models, open access data model and patient registries
Deliverables
Academia, biotech, EC/EU, pharma
Academia, NIH, pharma
Academia, biotech, NIMH/NIH, pharma
Academia, CIHR, Sage Bionetworks, pharma
Academia, Canada Foundation for Innovation, CIHR, Genome Canada, Ontario Ministry of Economic Development and Innovation, pharma, Wellcome Trust
Academia, Brain Canada, CIHR, foundations, Guardian Angels, Orion Bionetworks, patient advocacy, pharma
Current consortia partners (funding, programmatic or strategic partners or sectors)
BIO: Biotechnology Industry Organization; CIHR: Canadian Institute for Health Research; CMS: Centers for Medicare and Medicaid Services; EC: European Commission; EFPIA: European Federation of Pharmaceutical Industries and Associations; EMA: European Medicines Agency; EU: European Union; iPSCs: Induced pluripotent stem cells; NCATS: National Center for Advancing Translational Sciences; NIA: National Institute on Aging; NIMH: National Institute of Mental Health; PhRMA: Pharmaceutical Research and Manufacturers of America; PMDA: Pharmaceutical and Medical Devices Agency Japan.
Schizophrenia
ADHD, ASD, anxiety disorders, mood disorders and schizophrenia
Assays, disease models
AD, ASD and schizophrenia
NCRCRG [21] to Study Mental Illness
Phase II proof of concept studies
Human proteins of biomedical relevance
Assays, target identification
Structural Genomics Consortium (SGC) [38]
Emerging consortia Archipelago to Proof of Concept in Medicine (Arch2POCM) [39]
AD, multiple sclerosis, post-traumatic stress syndrome and traumatic brain injury
Disease(s)
Biomarkers
Stage(s) of pipeline
One Mind for Research [37]
Public--private consortia
Table 1. Examples of precompetitive public--private consortia that provide tools, methods or resources for enabling CNS drug discovery and development pipeline (continued).
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
PPPs to revitalize psychiatric drug discovery
5
L. S. Brady & W. Z. Potter
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
3.
Expert opinion
Several public--private consortia have the potential to directly or indirectly accelerate CNS drug discovery and development in the United States and Europe. Some PPPs focus on development of tools to facilitate psychiatric pathophysiology discovery, and others focus on tools that can be directly applied to areas in which there is more active investment in drug development by industry (e.g., AD and Parkinson’s disease [PD]; Table 1). To date, only a few PPPs have delivered results that have a documented impact and selected examples follow. First, the risk alleles revealed by meta-analyses of GWA across disorders by the PGC are informing important areas of future research supported by NIMH. New data analytic approaches coupled with genetic findings by the PGC and similar efforts have the potential to reinvigorate target identification and validation in drug discovery. A decade ago much of the industry was so enthusiastic about the promise of genetic approaches that substantial internal expertise and resources were established only to be followed by major reductions of such efforts in the absence of clear deliverables within the timeframe of commitment. PPPs will play an important role in determining how to move from genetic findings to targets. Second, the utilization of biomarkers explored in mild cognitive impairment (MCI) and AD trials by ADNI are now routinely being incorporated into industry-sponsored clinical trials. Findings from NewMeds mining of data from trials of negative symptoms in schizophrenia may be utilized by industry to improve trial design and signal detection for testing novel therapeutics, but to date the degree of uptake remains to be determined. Third, there has been considerable stimulation of biomarker research in PD by the Michael J. Fox Foundation (MJFF) [23], but exactly when any findings can be expected to influence trials may be several years away. In general, one should not expect to see impact until at least 5 years after initiation of a PPP and perhaps not before 10 years. Thus, sustained commitment and duration of funding may be essential for PPPs to have real impact. Independent of near-term impact, PPPs are investing in tools that address gap areas such as deeper phenotypic characterization of subjects to enable identification of new pathophysiological targets and more homogeneous subgroups for clinical studies. Ideally, biomarker tools will stratify subjects in trials and human experimental medicine paradigms in ways that enable translation and prediction of promising drug candidates from preclinical models to human testing. In addition to PPPs, the latter goal is addressed in at least one private consortium -- P1vital [24]. Building on the theme of discovery technologies, areas that public--private consortia could embrace include: the use of genetics, iPSCs and network analyses to generate disease-related targets; deeper phenotyping using a standard set of functional multimodal measures; common data elements in clinical research to enable comparison and combination of data from multiple
6
studies; and expanded ability to merge and analyze complex datasets. Some common principles apply to the most successful PPPs whether they start small and expand (e.g., PGC) or make a large commitment up front (e.g., ADNI) with government funding. Most of the mature CNS PPP projects in Table 1, with the exception of those in the MJFF portfolio began with the bulk of funding provided through federal government agencies. Even within the FNIH Biomarkers Consortium, which is funded primarily through industry, the most extensive CNS-related projects utilize subjects and samples from ADNI and not de novo clinical phases of study. Thus, although it may be possible for a foundation to attract private contributions and participation of relevant stakeholders to develop and pursue major projects, government sponsorship with input from academic, advocacy and industry advisors provides a clearer path. It will be interesting, in this respect, to see how the private consortia model followed by P1vital fares. Since government practices and budgets, especially those at the NIH, demand more transparency than required by other structures, providing a neutral setting to explore how combining efforts and putting aside individual competitive research or business agendas is likely to accelerate the rate of discovery and development of new treatments. Scientific alignment of the stakeholders on projects and their deliverables in a specified timeframe is essential, but often difficult to obtain, especially with regard to methods that are evolving at a rapid rate and judged ‘not ready for prime time’. The incentives and risk--benefit need to be aligned to attract academics (who are used to an independent investigator model) and support from the public (usually represented by advocacy groups and foundations). The latter can play a very large role by generating the sustained commitment required for longer-term consortia efforts as well as driving more rapid adjustments to ongoing efforts. The mix of funding sources (i.e., in-kind contributions, public and private funds) needs to be taken into account by the consortium in terms of preventing, for instance, acquisition of subjects, archived measures and stored fluid and tissue samples that are inadequately utilized. The scope of precompetitive projects within the consortium and criteria for success needs to be clear in terms of having everything in place to support sample acquisition, assays, analyses and dissemination of results. Within the consortium, projects size and scope, and the mix and number of partners should be flexible and, to the extent possible, adjust to new findings and technologies (e.g., inclusion of [11]C-Pittsburgh compound B amyloid-beta imaging in subsequent ADNI subjects after beginning accrual [25]). Projects are more attractive to the stakeholders when they build on a public investment, existing infrastructure, datasets, biomaterials and/or resources. Plans for timely sharing of know-how, data, tools and methods generated by the project are essential and should be well articulated. To date, only
Expert Opin. Drug Discov. (2014) 9(1)
PPPs to revitalize psychiatric drug discovery
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
ADNI has operated with a policy of open sourcing of all raw data and has funded an infrastructure to support the enterprise. Plans for dealing with newly generated intellectual property (even if none is anticipated) should be included where there is not an open sourcing of data. It is important to involve the FDA and other regulatory agencies in the development and monitoring of projects to facilitate their potential application (e.g., AD diagnostic markers and regulatory guidance for AD). To build the depth of support required for a large consortia effort extending over years, conveners should be prepared for at least a year of stakeholder discussions to agree on scope and goals followed by another year of Bibliography
Whiteford HA, Degenhardt L, Rehm J, et al. Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010. Lancet 2013;382(9904):1575-86
2.
Hyman SE. Revolution stalled. Sci Transl Med 2012;4(155):155cm11
3.
Insel TR. Next-generation treatments for mental disorders. Sci Transl Med 2012;4(155):155ps19
4.
Alzheimer’s Disease Neuroimaging Initiative (ADNI). Available from: http://www.adni-info.org/
5.
Foundation for the National Institutes of Health (FNIH). Available from: http://www.fnih.org/work/nih
6.
Weiner MW, Veitch DP, Aisen PS, et al. The Alzheimer’s Disease Neuroimaging Initiative: a review of papers published since its inception. Alzheimers Dement 2013;9(5):e111-94 Review article providing a detailed summary of published research finding of ADNI since the inception of the program.
..
7.
Biomarkers Consortium. Available from: http://www.biomarkersconsortium.org/
8.
Biomarkers Consortium, Neuroscience Steering Committee. Available from: http://www.biomarkersconsortium.org/ steering_neuro.php
9.
Potter WZ, Pickering EH, Immerman F, et al. Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Foundation for NIH Biomarkers Consortium CSF Proteomics Project Team. Cerebrospinal fluid (CSF) vs. plasma-based biomarkers in Alzheimer’s disease (AD), mild
Declaration of interest Both authors declare support from the NIMH. WZ Potter acts as a senior consultant for the NIMH and has served on the advisory boards for AgeneBio, Amgen, Ironwood, Eli Lilly & Co., MedAvante, Taisho Pharmaceuticals, Takeda and Theravance. WZ Potter also has personal financial holdings from their previous employment at Merck & Co.
cognitive impaired (MCI) and agematched healthy controls (HC) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Alzheimers Dement 2012;8(4):P217
Papers of special note have been highlighted as either of interest () or of considerable interest () to readers. 1.
generating and reviewing specific proposals for funding by all relevant sources.
10.
11.
12.
Siuciak JA, Pickering EH, Immermann F, et al. Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Foundation for NIH Biomarkers Consortium CSF Proteomics Project Team. Cerebrospinal fluid (CSF) biomarkers in Alzheimer’s disease (AD), mild cognitively impaired (MCI) and age-matched healthy controls (HC) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Alzheimers Dement 2012;8(4):P216-P17 Soares HD, Potter WZ, Pickering E, et al. Plasma biomarkers associated with the apolipoprotein E genotype and Alzheimer disease. Arch Neurol 2012;69(10):1310-17 NIH-Industry Pilot, Discovering New Therapeutic Uses for Existing Molecules (New Therapeutic Uses). Available from: http://www.ncats.nih.gov/research/ reengineering/rescue-repurpose/ therapeutic-uses/therapeutic-uses.html
..
17.
.
innovation challenge. Clin Pharmacol Ther 2012;91(3):418-25 An overview of the IMI and the projects conducted by the IMI consortia. Rabinowitz J, Werbeloff N, Caers I, et al. Negative symptoms in schizophrenia - the remarkable impact of inclusion definitions in clinical trials and their consequences. Schizophr Res 2013;150(2-3):334-8 An analysis of data from the NewMeds repository examining the impact of operational criteria for negative symptoms on patient inclusion and outcome in schizophrenia trials.
18.
Psychiatric Genomics Consortium. Available from: https://pgc.unc.edu/
19.
Psychiatric GWAS Consortium Steering Committee. A framework for interpreting genome-wide association studies of psychiatric disorders. Mol Psychiatry 2009;14(1):10-17
20.
Lee SH, Ripke S, Neale BM, et al. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat Genet 2013;45(9):984-94 A meta-analysis of genome-wide genotype data for cases and controls in schizophrenia, bipolar disorder, MDD, ASDs and ADHD conducted by the Cross-Disorder Group of the PGC.
..
13.
Colvis CM, Devaney S, Brady LS, Hudson KL. Partnering for therapeutics discovery. Clin Pharmacol Ther 2013;93(1):24-5
14.
Wadman M. NIH gambles on recycled drugs. Nature 2013;499(7458):263-4
21.
15.
Novel Methods Leading to New Medications in Depression and Schizophrenia (New Meds). Available from: http://www.newmeds-europe.com/ en/news.php
National Cooperative Reprogrammed Cell Research Groups (NCRCRG) to Study Mental Illness. Available from: http://grants.nih.gov/grants/guide/pa-files/ PAR-13-225.html
22.
Panchision DM. Meeting report: using stem cells for biological and therapeutics discovery in mental illness. Stem Cells Transl Med 2013;2(3):217-22
16.
Goldman M. The innovative medicines initiative: a European response to the
Expert Opin. Drug Discov. (2014) 9(1)
7
L. S. Brady & W. Z. Potter
23.
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
..
The Parkinson Progression Marker Initiative. The Parkinson Progression Marker Initiative (PPMI). Prog Neurobiol 2011;95(4):629-35 An overview of the goals and objectives of the PPMI, an international, multicenter study to identify PD progression biomarkers.
24.
P1vital. Available from: http://www. p1vital.com/
25.
Landau SM, Breault C, Joshi AD, et al. Amyloid-beta imaging with Pittsburgh compound B and florbetapir: comparing radiotracers and quantification methods. J Nucl Med 2013;54(1):70-7
26.
Critical Path Institute (C-Path). Available from: http://c-path.org/
27.
Coalition Against Major Diseases (CAMD). Available from: http://c-path. org/programs/camd/
28.
29.
30.
8
www.alzheimer-europe.org/Research/ PharmaCog
from: http://www.eu-aims.eu/ http:// www.imi.europa.eu/content/eu-aims 31.
Innovative Medicines Initiative (IMI). Available from: http://www.imi.europa.eu/
37.
One Mind for Research. Available from: http://1mind4research.org/
32.
Medical Research Council (MRC)/ AstraZeneca Mechanisms of Disease Initiative. Available from: http://www. mrc.ac.uk/Fundingopportunities/Calls/ MoD/MRC008389 http://www. astrazeneca.com/Media/Press-releases/ Article/20121131--astrazeneca-MRCcollaboration-disease-research
38.
Structural Genomics Consortium (SGC). Available from: http://www.thesgc.org/
39.
Norman TC, Bountra C, Edwards AM, et al. Leveraging crowdsourcing to facilitate the discovery of new medicines. Sci Transl Med 2011;3(88):88mr1
40.
NIH-Industry Target Validation Consortium. Available from: http://www. ncats.nih.gov/research/reengineering/drugtargets/drug-targets.html
41.
TRIMAGE. Available from: http://ec. europa.eu/research/health/medicalresearch/brain-research/projects/ trimage_en.html
33.
34.
Patient-Reported Outcome (PRO). Available from: http://c-path.org/ programs/pro/
National Cooperative Drug Discovery/ Development Groups (NCDDG) for the Treatment of Mental Disorders, Drug or Alcohol Addiction (U19). Available from: http://grants.nih.gov/grants/guide/ pa-files/PAR-13-086.html Functional Selectivity: a Novel Approach for CNS Drug Discovery. Available from: http://projectreporter.nih.gov/ project_info_description.cfm? aid =8527845&icde=18333422 &ddparam=&ddvalue=&ddsub= &cr=3&csb=default&cs=ASC
Predictive Safety Testing Consortium (PSTC). Available from: http://c-path. org/programs/pstc/
35.
European Autism Interventions A Multicentre Study for Developing New Medications (EU-AIMS). Available
Parkinson’s Progression Markers Initiative (PPMI). Available from: http://www.ppmi-info.org/
36.
PharmaCog. Available from: http://www. imi.europa.eu/content/pharma-cog http://
Expert Opin. Drug Discov. (2014) 9(1)
Affiliation
Linda S Brady†1 & William Z Potter2 Author for correspondence 1 National Institute of Mental Health, Division of Neuroscience and Basic Behavioral Science, 6001 Executive Blvd., Bethesda, MD, USA E-mail: [email protected] 2 Senior Advisor to the Director, National Institute of Mental Health, Bethesda, MD, USA †
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
Public--private partnerships to revitalize psychiatric drug discovery 1.
Introduction
2.
Selected case examples
3.
Expert opinion
Linda S Brady† & William Z Potter †
National Institute of Mental Health, Division of Neuroscience and Basic Behavioral Science, Bethesda, MD, USA
Introduction: Precompetitive public--private partnerships (PPPs) have the potential to improve psychiatric drug discovery by addressing gaps in the research and development pipeline such as the identification and validation of new targets, models, biomarkers and disease phenotyping. PPPs are a model to strategically bring together expertise, in-kind support and funding from multiple public and private sector partners. Areas covered: This editorial describes selected case examples of established and emerging public--private consortia in the United States and Europe that provide tools, methods or resources to accelerate central nervous system (CNS) drug discovery. The authors provides a listing of public--private consortia projects that focus on the CNS, the stage of the drug discovery pipeline that they address, diseases, deliverables provided and current consortia partners. Expert opinion: Some of the projects undertaken by PPPs in the area of CNS drug discovery and development are beginning to make tools, resources and data publicly available. Only a few PPPs have delivered enough to extract lessons learned. These include building alignment across a wide group of stakeholders, engaging advocacy groups and funding commitments for a minimum of 5 years. Keywords: Alzheimer’s Disease Neuroimaging Initiative, autism spectrum disorder, biomarkers, Biomarkers Consortium, cellular models, consortia, disease phenotyping, major depressive disorder, psychiatric drug discovery, psychiatric genetics, public--private partnerships, schizophrenia Expert Opin. Drug Discov. (2014) 9(1):1-8
1.
Introduction
Psychiatric disorders are the leading causes of disability worldwide [1]. There is an urgent need for new treatments to reduce the severity of symptoms, improve functional outcomes and preempt the developmental trajectory of disease, especially for schizophrenia and autism spectrum disorders (ASD). Despite the unmet medical need and market potential, many large pharmaceutical companies have recently reduced or terminated their programs in psychiatric drug development. The lack of new validated targets, generally applicable translatable animal models and biomarkers of disease, coupled with an increased failure rate of clinical trials, have contributed to industry’s decreased investment in psychiatric drug discovery [2,3] while stimulating the creation of public--private partnerships (PPPs) or consortia to address these challenges. PPPs can support precompetitive research to increase the rate of validating or rejecting novel mechanisms and potentially share the risk of developing novel therapies. There is no single model for PPPs, made clear in the following case examples of efforts to generate tools, methods and resources to address challenges in psychiatric and, more broadly, central nervous system (CNS) drug
10.1517/17460441.2014.867944 © 2014 Informa UK, Ltd. ISSN 1746-0441, e-ISSN 1746-045X All rights reserved: reproduction in whole or in part not permitted
1
L. S. Brady & W. Z. Potter
discovery (see Table 1 for a listing of public--private consortia relevant to CNS drug discovery).
2.
Selected case examples
2.1
Established consortia Alzheimer’s Disease Neuroimaging Initiative
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
2.1.1
The National Institute of Aging (NIA) established the Alzheimer’s Disease Neuroimaging Initiative (ADNI) [4] consortium to identify biomarkers for the early detection and tracking of Alzheimer’s disease (AD), with funding provided by government (NIA), 13 pharmaceutical companies, and 2 foundations, and with involvement of the Food and Drug Administration (FDA) and other regulatory agencies (Table 1). The Foundation for NIH (FNIH) [5], a nonprofit organization, coordinates the private funding that is combined with the roughly 60% from NIA which sponsors ADNI operating through a funded academic network. Through its steering committees, ADNI has developed optimized, standardized methods for collection of plasma and cerebrospinal fluid (CSF) samples, imaging, clinical and neuropsychological data that link to a multisite, worldwide effort initially coordinated through the Alzheimer’s Association [6]. Of note and more broadly, ADNI has benefitted from the active involvement of advocacy groups that have strong scientific arms, substantial resources and deep commitment to development of novel pharmacological treatments. All data are publicly accessible, and hundreds of papers have resulted.
Biomarkers Consortium, Neuroscience Steering Committee
2.1.2
The Biomarkers Consortium [7] is a PPP that uniquely resides within the FNIH with an executive committee with representatives from government (NIH and FDA), industry, academia and nonprofit organizations. The Neuroscience Steering Committee [8] solicits and develops proposals to discover, develop and qualify biomarkers to support drug development in the neuroscience therapeutic area. With approval by its executive committee, the FNIH raises funds from non-government sources and actively manages funded projects. To date, the majority of funded neuroscience projects have focused on AD, leveraging the infrastructure and samples generated by ADNI [9-11]. It has been much more difficult to attract the interest of industry and nonprofit partners for funding of biomarker projects that focus on psychiatric diseases or on biomarker technologies that are not directly relevant to CNS projects in the pharma discovery pipeline. Examples of projects for which funding could not be raised include multimodal markers to predict response to antidepressants, development of signal processing strategies for analysis of arterial spin labeling MRI data and longitudinal test-retest performance of FDG-PET in multicenter studies. 2
NIH-Industry Program, discovering new therapeutic uses for existing molecules
2.1.3
The new therapeutics uses [12] program is an example of a PPP to de-risk targets and identify new indications through drug repositioning with NIH solicitation and funding of proposals for new clinical trials. It is a model in which pharma identifies compounds for inclusion in the program and provides expertise, access to regulatory documents and clinical supply of compound and NIH oversees funded studies [13,14]. Innovative Medicines Initiative, NewMeds Consortium
2.1.4
NewMeds [15] (Novel Methods Leading to New Medications in Depression and Schizophrenia) is a joint effort between the European Union, which provides direct funding to academic centers, and the European Federation of Pharmaceutical Industries and Associations (EFPIA), which provides ‘in-kind’ contributions without funding. The consortium includes 13 pharmaceutical companies, 7 academic teams and 3 small businesses [16]. It has, for instance, created a large database of schizophrenia clinical trial data contributed by industry (> 20,000 patients in > 25 countries) and analyzed by academia, with findings on the impact of operational criteria for negative symptom change that should prove very useful in designing future trials [17]. Psychiatric Genomics Consortium, genetic risk architecture
2.1.5
The Psychiatric Genomics Consortium (PGC) [18] was initiated by a small group of investigators (academic and NIMH), in 2007, to address the challenge in psychiatric genetics of detecting risk gene variants of small effect [19]. The PGC quickly expanded to a large, international confederation of scientists focused on five serious mental illnesses. The group is conducting meta-analyses of PGC genome-wide association (GWA) data from 170,000 cases and controls [20]. Core analyses, infrastructure and genotyping are supported by public and private partners from multiple sectors (Table 1). The PGC is developing a ‘PsychChip’ that will be used to genotype 90,000 individuals and be available from Illumina by the end of 2013. Emerging consortia Induced pluripotent stem cell technologies for modeling human diseases
2.2
2.2.1
Following a workshop in April 2012, NIMH issued a funding announcement to initiate the National Cooperative Reprogrammed Cell Research Groups (NCRCRG) [21] to study mental illness, to establish academic--industry partnerships, to facilitate the use of patient-derived reprogrammed cells (e.g., induced pluripotent stem cells [iPSCs] and induced neuronal cells to study the molecular and cellular basis of mental illness), to identify novel targets for drug discovery and to assess candidate drugs in iPSC assays [22].
Expert Opin. Drug Discov. (2014) 9(1)
Expert Opin. Drug Discov. (2014) 9(1)
ASD
AD, anxiety, cancer and various disorders
Assays, disease models, biomarkers, phenotyping and target identification
Disease models and drug repositioning Assays, cross-species phenotyping and target identification
European Autism Interventions -- A Multicentre Study for Developing New Medications (EU-AIMS) [30] and IMI [31]
Medical Research Council (MRC)/AstraZeneca Mechanisms of Disease Initiative [32]
NewMeds [15] and IMI
Models, biomarkers, genetic predictors of drug response and standardized methods for brain imaging
Disease models, preclinical and clinical proof of concept of selected mechanisms in new disease areas
Cellular assays, animal models, biomarkers and risk genes
Biomarkers, disease models, nonclinical and clinical safety biomarkers, patient-reported outcomes measures
Validated biomarkers, testing of biomarker tools and technologies and standardized methods for brain imaging
CSF, plasma samples, standardized methods for brain imaging, cognitive testing and LONI database
Deliverables
Academia, advocacy groups, EFPIA, EMA, EU
Academia, AstraZeneca, MRC
Academia, biotech, Autism Speaks, EFPIA, EMA, EU
Academia, FDA, EMA, PMDA, foundations and pharma
Academia, BIO, CMS, FDA, foundations, NIH, PhRMA
Academia, Alzheimer’s Association, Alzheimer’s Drug Discovery Foundation, CIHR, FDA, GE Healthcare, NIA/NIH, pharma
Current consortia partners (funding, programmatic or strategic partners or sectors)
BIO: Biotechnology Industry Organization; CIHR: Canadian Institute for Health Research; CMS: Centers for Medicare and Medicaid Services; EC: European Commission; EFPIA: European Federation of Pharmaceutical Industries and Associations; EMA: European Medicines Agency; EU: European Union; iPSCs: Induced pluripotent stem cells; NCATS: National Center for Advancing Translational Sciences; NIA: National Institute on Aging; NIMH: National Institute of Mental Health; PhRMA: Pharmaceutical Research and Manufacturers of America; PMDA: Pharmaceutical and Medical Devices Agency Japan.
Depression and schizophrenia
AD, major depressive disorder (MDD), PD, multiple sclerosis (MS) and other diseases
CNS disorders
Biomarkers
Disease models, biomarkers, drug safety and outcome measures
AD
Disease(s)
Biomarkers
Stage(s) of pipeline
Critical Path Institute (C-Path) [26] consortia: Coalition Against Major Diseases (CAMD) [27]; Patient-Reported Outcome (PRO) [28]; Predictive Safety Testing Consortium (PSTC) [29]
Biomarkers Consortium [7], Neuroscience Steering Committee [8] and FNIH
Established consortia Alzheimer’s Disease Neuroimaging Initiative [4] and FNIH [5]
Public--private consortia
Table 1. Examples of precompetitive public--private consortia that provide tools, methods or resources for enabling CNS drug discovery and development pipeline.
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
PPPs to revitalize psychiatric drug discovery
3
4
Expert Opin. Drug Discov. (2014) 9(1)
PD
AD and MCI
Attention-deficit/hyperactivity disorder (ADHD), ASD, bipolar disorder, MDD and schizophrenia
Animal models and biomarkers Biomarkers
Target identification and validation
Parkinson’s Progression Markers Initiative (PPMI) [35] and MJFF
PharmaCog [36] and IMI
PGC [18]
Risk genes, meta-analyses of genotypes from 170,000 cases and controls, open source philosophy and ‘PsychChip’
Matrix of biomarker tools to predict cognitive properties of new drug candidates, for use in disease models and in clinical trials
Animal models, biomarkers, CSF, plasma samples and standardized methods for brain imaging
Disease models, preclinical and clinical proof of concept of selected mechanisms in new disease areas
Assays, disease models and preclinical proof of concept of selected compounds
Deliverables
Academia, Hersenstichting Netherland, Netherlands Genetic Cluster Computer, NIMH, One Mind for Research, pharma (core analyses and infrastructure); Broad/ Stanley Center, deCODE Genetics, EU, Genome Canada, NIMH, pharma, Wellcome Trust Case Control Consortium and others (GWA genotyping)
Academia, Alzheimer Europe, EFPIA, EMA, EU
Academia, advocacy groups, GE Healthcare, MJFF, pharma
Academia, NCATS/NIH, pharma
Academia, NIMH/NIH, biotechnology, pharma
Current consortia partners (funding, programmatic or strategic partners or sectors)
BIO: Biotechnology Industry Organization; CIHR: Canadian Institute for Health Research; CMS: Centers for Medicare and Medicaid Services; EC: European Commission; EFPIA: European Federation of Pharmaceutical Industries and Associations; EMA: European Medicines Agency; EU: European Union; iPSCs: Induced pluripotent stem cells; NCATS: National Center for Advancing Translational Sciences; NIA: National Institute on Aging; NIMH: National Institute of Mental Health; PhRMA: Pharmaceutical Research and Manufacturers of America; PMDA: Pharmaceutical and Medical Devices Agency Japan.
AD, Duchenne muscular dystrophy, schizophrenia and various disorders
Psychiatric disorders, drug addiction and alcohol addiction
Disease(s)
Drug repositioning
Assays, disease models, target identification and drug discovery
Stage(s) of pipeline
New Therapeutic Uses [12]
National Cooperative Drug Discovery/Development Group (NCDDG) [33] for the Treatment of Mental Disorders, Drug or Alcohol Addiction: Functional Selectivity: A Novel Approach for CNS Drug discovery [34]
Public--private consortia
Table 1. Examples of precompetitive public--private consortia that provide tools, methods or resources for enabling CNS drug discovery and development pipeline (continued).
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
L. S. Brady & W. Z. Potter
Expert Opin. Drug Discov. (2014) 9(1)
AD, rheumatoid arthritis, schizophrenia prodrome and type 2 diabetes
Biomarkers and target validation Diagnosis and Biomarkers
NIH-Industry Target Validation Consortium (workshop [40])
TRIMAGE [41]
Disease signatures using PET/MR, fMRI/EEG, PET/MR/EEG and trimodality imaging hardware
Biomarkers, biosamples, genetic risk factors and target validation in human subjects
Assays, biosamples, disease models, methods and technologies to differentiate iPSCs into neuronal or glial cells
Clinical validation of new disease mechanisms or targets and open access data model
Assays, protein structures, epigenetic targets, chemical and biological probes and open access data model
Biomarkers, biosamples, disease models, open access data model and patient registries
Deliverables
Academia, biotech, EC/EU, pharma
Academia, NIH, pharma
Academia, biotech, NIMH/NIH, pharma
Academia, CIHR, Sage Bionetworks, pharma
Academia, Canada Foundation for Innovation, CIHR, Genome Canada, Ontario Ministry of Economic Development and Innovation, pharma, Wellcome Trust
Academia, Brain Canada, CIHR, foundations, Guardian Angels, Orion Bionetworks, patient advocacy, pharma
Current consortia partners (funding, programmatic or strategic partners or sectors)
BIO: Biotechnology Industry Organization; CIHR: Canadian Institute for Health Research; CMS: Centers for Medicare and Medicaid Services; EC: European Commission; EFPIA: European Federation of Pharmaceutical Industries and Associations; EMA: European Medicines Agency; EU: European Union; iPSCs: Induced pluripotent stem cells; NCATS: National Center for Advancing Translational Sciences; NIA: National Institute on Aging; NIMH: National Institute of Mental Health; PhRMA: Pharmaceutical Research and Manufacturers of America; PMDA: Pharmaceutical and Medical Devices Agency Japan.
Schizophrenia
ADHD, ASD, anxiety disorders, mood disorders and schizophrenia
Assays, disease models
AD, ASD and schizophrenia
NCRCRG [21] to Study Mental Illness
Phase II proof of concept studies
Human proteins of biomedical relevance
Assays, target identification
Structural Genomics Consortium (SGC) [38]
Emerging consortia Archipelago to Proof of Concept in Medicine (Arch2POCM) [39]
AD, multiple sclerosis, post-traumatic stress syndrome and traumatic brain injury
Disease(s)
Biomarkers
Stage(s) of pipeline
One Mind for Research [37]
Public--private consortia
Table 1. Examples of precompetitive public--private consortia that provide tools, methods or resources for enabling CNS drug discovery and development pipeline (continued).
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
PPPs to revitalize psychiatric drug discovery
5
L. S. Brady & W. Z. Potter
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
3.
Expert opinion
Several public--private consortia have the potential to directly or indirectly accelerate CNS drug discovery and development in the United States and Europe. Some PPPs focus on development of tools to facilitate psychiatric pathophysiology discovery, and others focus on tools that can be directly applied to areas in which there is more active investment in drug development by industry (e.g., AD and Parkinson’s disease [PD]; Table 1). To date, only a few PPPs have delivered results that have a documented impact and selected examples follow. First, the risk alleles revealed by meta-analyses of GWA across disorders by the PGC are informing important areas of future research supported by NIMH. New data analytic approaches coupled with genetic findings by the PGC and similar efforts have the potential to reinvigorate target identification and validation in drug discovery. A decade ago much of the industry was so enthusiastic about the promise of genetic approaches that substantial internal expertise and resources were established only to be followed by major reductions of such efforts in the absence of clear deliverables within the timeframe of commitment. PPPs will play an important role in determining how to move from genetic findings to targets. Second, the utilization of biomarkers explored in mild cognitive impairment (MCI) and AD trials by ADNI are now routinely being incorporated into industry-sponsored clinical trials. Findings from NewMeds mining of data from trials of negative symptoms in schizophrenia may be utilized by industry to improve trial design and signal detection for testing novel therapeutics, but to date the degree of uptake remains to be determined. Third, there has been considerable stimulation of biomarker research in PD by the Michael J. Fox Foundation (MJFF) [23], but exactly when any findings can be expected to influence trials may be several years away. In general, one should not expect to see impact until at least 5 years after initiation of a PPP and perhaps not before 10 years. Thus, sustained commitment and duration of funding may be essential for PPPs to have real impact. Independent of near-term impact, PPPs are investing in tools that address gap areas such as deeper phenotypic characterization of subjects to enable identification of new pathophysiological targets and more homogeneous subgroups for clinical studies. Ideally, biomarker tools will stratify subjects in trials and human experimental medicine paradigms in ways that enable translation and prediction of promising drug candidates from preclinical models to human testing. In addition to PPPs, the latter goal is addressed in at least one private consortium -- P1vital [24]. Building on the theme of discovery technologies, areas that public--private consortia could embrace include: the use of genetics, iPSCs and network analyses to generate disease-related targets; deeper phenotyping using a standard set of functional multimodal measures; common data elements in clinical research to enable comparison and combination of data from multiple
6
studies; and expanded ability to merge and analyze complex datasets. Some common principles apply to the most successful PPPs whether they start small and expand (e.g., PGC) or make a large commitment up front (e.g., ADNI) with government funding. Most of the mature CNS PPP projects in Table 1, with the exception of those in the MJFF portfolio began with the bulk of funding provided through federal government agencies. Even within the FNIH Biomarkers Consortium, which is funded primarily through industry, the most extensive CNS-related projects utilize subjects and samples from ADNI and not de novo clinical phases of study. Thus, although it may be possible for a foundation to attract private contributions and participation of relevant stakeholders to develop and pursue major projects, government sponsorship with input from academic, advocacy and industry advisors provides a clearer path. It will be interesting, in this respect, to see how the private consortia model followed by P1vital fares. Since government practices and budgets, especially those at the NIH, demand more transparency than required by other structures, providing a neutral setting to explore how combining efforts and putting aside individual competitive research or business agendas is likely to accelerate the rate of discovery and development of new treatments. Scientific alignment of the stakeholders on projects and their deliverables in a specified timeframe is essential, but often difficult to obtain, especially with regard to methods that are evolving at a rapid rate and judged ‘not ready for prime time’. The incentives and risk--benefit need to be aligned to attract academics (who are used to an independent investigator model) and support from the public (usually represented by advocacy groups and foundations). The latter can play a very large role by generating the sustained commitment required for longer-term consortia efforts as well as driving more rapid adjustments to ongoing efforts. The mix of funding sources (i.e., in-kind contributions, public and private funds) needs to be taken into account by the consortium in terms of preventing, for instance, acquisition of subjects, archived measures and stored fluid and tissue samples that are inadequately utilized. The scope of precompetitive projects within the consortium and criteria for success needs to be clear in terms of having everything in place to support sample acquisition, assays, analyses and dissemination of results. Within the consortium, projects size and scope, and the mix and number of partners should be flexible and, to the extent possible, adjust to new findings and technologies (e.g., inclusion of [11]C-Pittsburgh compound B amyloid-beta imaging in subsequent ADNI subjects after beginning accrual [25]). Projects are more attractive to the stakeholders when they build on a public investment, existing infrastructure, datasets, biomaterials and/or resources. Plans for timely sharing of know-how, data, tools and methods generated by the project are essential and should be well articulated. To date, only
Expert Opin. Drug Discov. (2014) 9(1)
PPPs to revitalize psychiatric drug discovery
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
ADNI has operated with a policy of open sourcing of all raw data and has funded an infrastructure to support the enterprise. Plans for dealing with newly generated intellectual property (even if none is anticipated) should be included where there is not an open sourcing of data. It is important to involve the FDA and other regulatory agencies in the development and monitoring of projects to facilitate their potential application (e.g., AD diagnostic markers and regulatory guidance for AD). To build the depth of support required for a large consortia effort extending over years, conveners should be prepared for at least a year of stakeholder discussions to agree on scope and goals followed by another year of Bibliography
Whiteford HA, Degenhardt L, Rehm J, et al. Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010. Lancet 2013;382(9904):1575-86
2.
Hyman SE. Revolution stalled. Sci Transl Med 2012;4(155):155cm11
3.
Insel TR. Next-generation treatments for mental disorders. Sci Transl Med 2012;4(155):155ps19
4.
Alzheimer’s Disease Neuroimaging Initiative (ADNI). Available from: http://www.adni-info.org/
5.
Foundation for the National Institutes of Health (FNIH). Available from: http://www.fnih.org/work/nih
6.
Weiner MW, Veitch DP, Aisen PS, et al. The Alzheimer’s Disease Neuroimaging Initiative: a review of papers published since its inception. Alzheimers Dement 2013;9(5):e111-94 Review article providing a detailed summary of published research finding of ADNI since the inception of the program.
..
7.
Biomarkers Consortium. Available from: http://www.biomarkersconsortium.org/
8.
Biomarkers Consortium, Neuroscience Steering Committee. Available from: http://www.biomarkersconsortium.org/ steering_neuro.php
9.
Potter WZ, Pickering EH, Immerman F, et al. Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Foundation for NIH Biomarkers Consortium CSF Proteomics Project Team. Cerebrospinal fluid (CSF) vs. plasma-based biomarkers in Alzheimer’s disease (AD), mild
Declaration of interest Both authors declare support from the NIMH. WZ Potter acts as a senior consultant for the NIMH and has served on the advisory boards for AgeneBio, Amgen, Ironwood, Eli Lilly & Co., MedAvante, Taisho Pharmaceuticals, Takeda and Theravance. WZ Potter also has personal financial holdings from their previous employment at Merck & Co.
cognitive impaired (MCI) and agematched healthy controls (HC) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Alzheimers Dement 2012;8(4):P217
Papers of special note have been highlighted as either of interest () or of considerable interest () to readers. 1.
generating and reviewing specific proposals for funding by all relevant sources.
10.
11.
12.
Siuciak JA, Pickering EH, Immermann F, et al. Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Foundation for NIH Biomarkers Consortium CSF Proteomics Project Team. Cerebrospinal fluid (CSF) biomarkers in Alzheimer’s disease (AD), mild cognitively impaired (MCI) and age-matched healthy controls (HC) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Alzheimers Dement 2012;8(4):P216-P17 Soares HD, Potter WZ, Pickering E, et al. Plasma biomarkers associated with the apolipoprotein E genotype and Alzheimer disease. Arch Neurol 2012;69(10):1310-17 NIH-Industry Pilot, Discovering New Therapeutic Uses for Existing Molecules (New Therapeutic Uses). Available from: http://www.ncats.nih.gov/research/ reengineering/rescue-repurpose/ therapeutic-uses/therapeutic-uses.html
..
17.
.
innovation challenge. Clin Pharmacol Ther 2012;91(3):418-25 An overview of the IMI and the projects conducted by the IMI consortia. Rabinowitz J, Werbeloff N, Caers I, et al. Negative symptoms in schizophrenia - the remarkable impact of inclusion definitions in clinical trials and their consequences. Schizophr Res 2013;150(2-3):334-8 An analysis of data from the NewMeds repository examining the impact of operational criteria for negative symptoms on patient inclusion and outcome in schizophrenia trials.
18.
Psychiatric Genomics Consortium. Available from: https://pgc.unc.edu/
19.
Psychiatric GWAS Consortium Steering Committee. A framework for interpreting genome-wide association studies of psychiatric disorders. Mol Psychiatry 2009;14(1):10-17
20.
Lee SH, Ripke S, Neale BM, et al. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat Genet 2013;45(9):984-94 A meta-analysis of genome-wide genotype data for cases and controls in schizophrenia, bipolar disorder, MDD, ASDs and ADHD conducted by the Cross-Disorder Group of the PGC.
..
13.
Colvis CM, Devaney S, Brady LS, Hudson KL. Partnering for therapeutics discovery. Clin Pharmacol Ther 2013;93(1):24-5
14.
Wadman M. NIH gambles on recycled drugs. Nature 2013;499(7458):263-4
21.
15.
Novel Methods Leading to New Medications in Depression and Schizophrenia (New Meds). Available from: http://www.newmeds-europe.com/ en/news.php
National Cooperative Reprogrammed Cell Research Groups (NCRCRG) to Study Mental Illness. Available from: http://grants.nih.gov/grants/guide/pa-files/ PAR-13-225.html
22.
Panchision DM. Meeting report: using stem cells for biological and therapeutics discovery in mental illness. Stem Cells Transl Med 2013;2(3):217-22
16.
Goldman M. The innovative medicines initiative: a European response to the
Expert Opin. Drug Discov. (2014) 9(1)
7
L. S. Brady & W. Z. Potter
23.
Expert Opin. Drug Discov. Downloaded from informahealthcare.com by Cornell University on 12/15/14 For personal use only.
..
The Parkinson Progression Marker Initiative. The Parkinson Progression Marker Initiative (PPMI). Prog Neurobiol 2011;95(4):629-35 An overview of the goals and objectives of the PPMI, an international, multicenter study to identify PD progression biomarkers.
24.
P1vital. Available from: http://www. p1vital.com/
25.
Landau SM, Breault C, Joshi AD, et al. Amyloid-beta imaging with Pittsburgh compound B and florbetapir: comparing radiotracers and quantification methods. J Nucl Med 2013;54(1):70-7
26.
Critical Path Institute (C-Path). Available from: http://c-path.org/
27.
Coalition Against Major Diseases (CAMD). Available from: http://c-path. org/programs/camd/
28.
29.
30.
8
www.alzheimer-europe.org/Research/ PharmaCog
from: http://www.eu-aims.eu/ http:// www.imi.europa.eu/content/eu-aims 31.
Innovative Medicines Initiative (IMI). Available from: http://www.imi.europa.eu/
37.
One Mind for Research. Available from: http://1mind4research.org/
32.
Medical Research Council (MRC)/ AstraZeneca Mechanisms of Disease Initiative. Available from: http://www. mrc.ac.uk/Fundingopportunities/Calls/ MoD/MRC008389 http://www. astrazeneca.com/Media/Press-releases/ Article/20121131--astrazeneca-MRCcollaboration-disease-research
38.
Structural Genomics Consortium (SGC). Available from: http://www.thesgc.org/
39.
Norman TC, Bountra C, Edwards AM, et al. Leveraging crowdsourcing to facilitate the discovery of new medicines. Sci Transl Med 2011;3(88):88mr1
40.
NIH-Industry Target Validation Consortium. Available from: http://www. ncats.nih.gov/research/reengineering/drugtargets/drug-targets.html
41.
TRIMAGE. Available from: http://ec. europa.eu/research/health/medicalresearch/brain-research/projects/ trimage_en.html
33.
34.
Patient-Reported Outcome (PRO). Available from: http://c-path.org/ programs/pro/
National Cooperative Drug Discovery/ Development Groups (NCDDG) for the Treatment of Mental Disorders, Drug or Alcohol Addiction (U19). Available from: http://grants.nih.gov/grants/guide/ pa-files/PAR-13-086.html Functional Selectivity: a Novel Approach for CNS Drug Discovery. Available from: http://projectreporter.nih.gov/ project_info_description.cfm? aid =8527845&icde=18333422 &ddparam=&ddvalue=&ddsub= &cr=3&csb=default&cs=ASC
Predictive Safety Testing Consortium (PSTC). Available from: http://c-path. org/programs/pstc/
35.
European Autism Interventions A Multicentre Study for Developing New Medications (EU-AIMS). Available
Parkinson’s Progression Markers Initiative (PPMI). Available from: http://www.ppmi-info.org/
36.
PharmaCog. Available from: http://www. imi.europa.eu/content/pharma-cog http://
Expert Opin. Drug Discov. (2014) 9(1)
Affiliation
Linda S Brady†1 & William Z Potter2 Author for correspondence 1 National Institute of Mental Health, Division of Neuroscience and Basic Behavioral Science, 6001 Executive Blvd., Bethesda, MD, USA E-mail: [email protected] 2 Senior Advisor to the Director, National Institute of Mental Health, Bethesda, MD, USA †
