Advisory Council January 2018 Meeting Presentation: Overview on NIA Preclinical Pipeline



Friday, January 26, 2018

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Overview on NIA preclinical pipeline

Eliezer Masliah, M.D.
Director, Division of Neuroscience,
National Institute on Aging, NIH

NIA Translational research pipeline for AD and ADRD:The Team

Genetics and Epigenetics
Marilyn Miller

Target Discovery and Validation
AMP-AD Targets, M2OVE-AD-AD, Resilience-AD
Suzana Petanceska

Drug Discovery and Preclinical Drug Development
Drug development (U01), MODEL-AD, AlzPED, SBIR's
Lorenzo Refolo PhD

Clinical Drug Development
AMP-AD Biomarkers, ABC-DS, ACTC, Clinical trials, DIAN-TU
Laurie Ryan PhD

Dementias of the aging population

Complicated diagram. Listen to session video for explanation.

Mechanisms of toxicity in neurodegenerative disorders

Complicated diagram. Listen to session video for explanation.
Masliah and Valera MDS 2015

Mechanisms of neurodegeneration in Alzheimer's Disease

Complicated diagram. Listen to session video for explanation.

Alzheimer's Disease drug development pipeline-2017

Complicated diagram discussing Symptomatic Agents, Disease-Modifying Immunotherapy, and Disease-Modifying Small Molecules. Listen to session video for explanation.
Cummings et al Alz Dem 2017

AD pipeline- how does it compare to others?

  HCV Alzheimer disease MRSA Industry average*
Preclinical 30.2 119.3 13.0 14.6
Phase I 10.5 33.6 4.7 8.6
Phase II 6.6 23.0 2.9 4.6
Phase III 1.7 5.8 1.8 1.6
Registration 1.1 1.0 1.1 1.1
Launch 1.0 1.0 1.0 1.0
Overall success rate 2.0% 0.5% 4.6% 4.1%
Nature Review | Drug Discovery

Failure in the Clinic- where does the fault lie?

  • Too late?
    • Drug interventions are started at the wrong stage of disease
  • Too little?
    • May need greater drug effects
    • Insufficient dose
    • Lack of BBB penetration
  • Lack of target engagement
    • Drugs do not engage with intended targets in patients
    • Lack of translatable pharmaco-dynamic biomarkers
  • Wrong target?
    • We are targeting the wrong pathophysiological mechanisms
    • We need to target networks rather than single molecules
    • Unclear which toxic species to target

Sperling, Jack and Aisen, Science Translational Medicine, 2011

Key AD Summits Recommendations

  • Recognize the heterogeneity and the multifactorial nature of the disease.
  • Support extensive molecular profiling of existing and establish new cohorts to fill the gaps in large-scale human data needed to build predictive models of disease and wellness.
  • Employ new research paradigms such as systems biology and systems pharmacology.
  • Enable rapid and extensive sharing of data, disease models, and biological specimens.
  • Develop computational tools and infrastructure for storage, integration, and analysis of large-scale biological and other patient-relevant data.
  • Build new multidisciplinary translational teams and create virtual and real spaces where these teams can operate.
  • Support and enable open science.
  • Develop new precompetitive public-private partnerships.
  • Change academic, publishing, and funding incentives to promote collaborative, transparent, and reproducible research.
  • Engage patients, caregivers and citizens as direct partners in research.››

NAPA Research Goal #1: Treat and Prevent AD by 2025

  • New Funding Opportunities and Public Private Partnerships
  • Implementation Research Milestones
  • NIH AD Research Summits Recommendations

NIH AD Research Summits: Path to Treatment and Prevention

  • May 14-15, 2012
  • Feb 9-10, 2015
  • March 1-2, 2018

Integrated NIA AD-Drug Development Program

Complicated diagram. Listen to session video for explanation.

NIA and Trans-NIH translational pipeline for AD and ADRD

Complicated diagram. Listen to session video for explanation.

Alzheimer's Disease Sequencing Project (ADSP)

PI: G. Schellenberg; L. San U Penn; NIA Contact: Marilyn Miller

  1. New genomic variants contributing to Late-Onset AD (LOAD)
  2. Identify genomic variants contributing to protection against AD
  3. Provide insight as to why individuals with known risk factor variants escape developing AD
  4. Examine these factors in multi-ethnic populations to identify new pathways

Associated Programs

  • ADGC- Alzheimer's Disease Genetic Consortium
  • GCAD- Genome Center for AD
  • NIAGDS- NIA Genetics of AD storage site

Now WGS in 10,000 controls and 10,000 AD, 10,000 diverse populations

Complicated diagram. Listen to session video for explanation.

From single target to networks approach for AD-drug development

Complexity of Drug Action
Complicated diagram discussing Idealistic view, Real life scenario, Polypharmacy, and Chronopharmacy. Listen to session video for explanation.

Accelerating Medicines Partnership (AMP)

Alzheimer's Disease Program
Foundation for the National Institutes of Health
Complicated diagram discussing the Target Discovery and Preclinical Validation Project, and the Biomarkers Project. Listen to session video for explanation.
  • Progress over 4 years:
    • Centralized data resource established
    • All data deliverables/milestones met
    • Over 100 novel targets discovered; currently undergoing data-driven prioritization for further preclinical validation
    • A variety of experimental validation models developed
    • Novel biomarker discovery initiated
    • AMP-AD Partners
      • National Institute of Neurological Disorders and Stroke
      • Food and Drug Administration
      • Abbvie
      • Biogen
      • GlaxoSmithKline
      • Lilly
      • Alzheimer's Association
      • Alzheimer's Drug Discovery Foundation
      • USAgainst Alzheimer's
      • Foundation for the National Institutes of Health
AMP-AD Teams
Candidate Targets: preliminary list
SFRP1   S100A8   IGFBP5   SYP
PPP1R7   S100A9   ISYNA1   PCSK1
DNM3   P2RY2   KIF1C   KMO
EPB41L3   P2RY12   SLC38A2   MLIP
TUBB3   P2RY13   SNAP25   DLGAP1
MSN   CR1   SV2B   YAP1
CD44   CSF1R   SYT1   GNA13
LMNA   CX3CR1   SYT12   TRIM56
    SPI1   ZBTB47    
    TNFRSF10A   VGF    
    TNFRSF10B   PLXNB1    
  1. P. De Jager, D. Bennett
  2. E. Schadt, B. Zhang, S. Gandy, J. Zhu, M. Ehrlich
  3. T. Golde, N.Price, N. Ertekin-Taner, S. Younkin,
  4. A. Levey, T. Montine, J. Troncoso, D. Geschwind
  5. R. Kaddurah-Daouk
  6. B. Yakner, L. Huei Tsai

Secreted peptide VGF (non-acronymic)

Specifically expressed in a subpopulation of neuroendocrine cells, and is upregulated by nerve growth factor. The encoded secretory protein also shares similarities with the secretogranin/chromogranin family, however, its exact function is not known. Multiple VGF peptides reported to be significantly decreased between converting and non-converting MCI patients (ADNI) Spellman et al. 2015 - NIH (FNIH) Biomarkers Consortium CSF Proteomics Project Team

Complicated diagram discussing Differential Expression of VGF in Different Regions, Correlation of VGF with Traits, Gene Causal Network, and Protein Causal Network. Listen to session video for explanation.

Protein Networks as Novel Biomarkers

AMP-AD Emory Team
PI: Allan Levey

Hub proteins from brain networks are found in human CSF and discriminate AD from control and PD patients. Hub proteins are defined as proteins with the highest intra-modular connectivity (i.e., proteins that are most central within the module) in the M1, M4 and M7 modules. Red symbols are proteins that were also identified in the CSF.

Complicated diagram discussing M1 Synapse, M4 Immune Response, and M7 Protein Polymerization. Listen to session video for explanation.

Building on and expanding the AMP-AD Target Discovery Project

Molecular Mechanisms of the Vascular Etiology of Alzheimer's Disease (M2OVE-AD)
NIA contact- Suzana Petanceska
A collaboration between NIA and NINDS

  • ~$30 million over 5 years to support cross disciplinary research teams:
  • 5 research teams will generate various "omics" data from brain and peripheral fluids from individuals participating in several natural history and population studies
  • Predictions about molecular mechanisms will be explored in animal models (AD models and models of vascular/metabolic risk factors).
  • Goals and deliverables:
    • rapid and broad sharing of data
    • deeper understanding of the phenotypes of risk and the mechanisms linking vascular risk factors, cerebrovascular disease and AD
    • new disease-relevant therapeutic targets for prevention
    • molecular signatures that can be non-invasively measured and used for patient stratification

NINDS ADRD Translation Research Initiatives

In collaboration with NIA
NINDS contact: Roderick Corriveau (

Complicated diagram. Listen to session video for explanation.

Some examples of NIA pipeline for AD and ADRD

Complicated diagram. Listen to session video for explanation.


AD Drug Development Progarm
PI Institution Project or Target
Tuszynski M UCSD BDNF Gene Delivery
Catalano C Cognition Therapeutics, Inc Receptor Antagonist CT0093
Lin CL OSU Activators of glutamate transporter EAAT2
Wagner S UCSD Soluble Gamma-Secretase Modulators
Ives J Acumen Pharmaceuticals, Inc. Amyloid-Beta Oligomer Selective Immunotherapy
Van Eldik L U Kentucky MW151, block cytokine
Agadjanvan M Inst of Molecular Med AV1959 anti-Amyloid vaccine
Thota G Emory U EP2 receptor antagonists
Watterson DM Northwestern U MAPK Inhibitors
Brinton R USC Allopregnanolone


Blueprint, Drug Discovery for CNS, and Preclinical Drug Development
PI Institution Project or Target
Rosenzweig-Lipson S AgeneBio GAB-A 5 agonists
Brunden K U Penn Microtubule-stabilizers for tauopathy
Zhang, S VCU Aß oligomerization inhibitors
Pahan, K Rush U HEX, OCT and 3-hydroxy, 2, 2-dimethyl butyrate (HMB)
Bitan G UCLA 'Molecular Tweezers' CLR01 as
Witt K Southern Illinois U Somatostatin-based therapeutics
Varghese J UCLA ApoE4-targeted therapeutics
LU K Beth Israel Deaconess pT231-tau mAbs
Stutzmann G Rosalind Franklin Univ Ryanodine Calcium Channels
Sung Ok Yoon OSU JNK3 inhibitors
Diamond M Wash U Anti-Tau Antibodies
Cai J USF anti-Aß aggregation peptides

NIA Translational Center for Animal Model Resources MODEL-AD

  • NIA contact, Larry Refolo
  • RFA AG16-014 (U54): Indiana University/Jax Labs/Sage Bionetworks (Bruce Lamb, PI) and UCI (Frank LaFerla)
    • Maximize human datasets to identify putative variants, genes and biomarkers for AD
    • Generate, phenotype and validate the next generation of Tg mouse models of AD (50 new models over 5 years; deep, longitudinal phenotyping)
    • Develop a preclinical testing pipeline that implements rigorous study design and data analysis
    • Make data and animal models available to the research community for use in therapy development without IP barrier.

NIA Translational Center for Animal Model Resources

Complicated diagram discussing UCI and IU/JAX. Listen to session video for explanation.

Alzheimer's Disease Preclinical Efficacy Database

NIA contact, Larry Refolo

Screen shot of Alzheimer’s Disease Preclinical Efficacy Database home page.

New* NIA funding opportunities for translation research

SBIR/STTR opportunities

Next steps toward developing an AD Translational pipeline

Attaining the Goal of Precision Medicine for AD
Complicated diagram. Listen to session video for explanation.

Alzheimer's Disease Summit Program- 2018

Alzheimer's Disease Research Summit 2012: Path to Treatment and Prevention
March 1-2, 2018
National Institutes of Health
Bethesda, MD

The 2018 Summit will build on the foundation laid by the NIH AD Research Summits held in 2012 ( and 2015 ( It will feature progress towards achieving the AD research implementation milestones ( and continue the development of an integrated multidisciplinary research agenda necessary to enable precision medicine for AD treatment and prevention.

  • Novel Mechanistic Insights into the Complex Biology and Heterogeneity of AD
  • Enabling Precision Medicine for AD
  • Translational Tools and Infrastructure to Enable Predictive Drug Development
  • Emerging Therapeutics
  • Understanding the Impact of the Environment to Advance Disease Prevention
  • Advances in Disease Monitoring, Assessment and Care
  • Building an Open Science Research Ecosystem to Accelerate AD Therapy Development


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