NIH/NIA – Alzheimer Centers for Discovery of New Medicines (U54 Clinical Trial Not Allowed)

August 6, 2018 by School of Medicine Webmaster

This Funding Opportunity Announcement (FOA) invites applications to establish multi-component Alzheimer Centers for Discovery of New Medicines. The overarching objective of this Centers program is to improve, diversify and reinvigorate the Alzheimer’s disease (AD) drug development pipeline by accelerating the characterization and experimental validation of next generation therapeutic targets and integrating the targets into drug discovery campaigns. More specifically, each funded Center will 1) design, develop and disseminate tools that support target enabling packages (TEPs) for the experimental validation of novel, next generation therapeutic targets, including those emanating from the NIA-funded target discovery programs such as AMP-AD/AMP-AD Wall of Targets, and 2) initiate early stage drug discovery campaigns against the enabled targets. To achieve these goals, it is expected that each Center will be staffed by a multi-disciplinary team of scientists with combined expertise in data science, computational biology, network biology, disease biology, structural genomics, biostatistics, assay development, medicinal chemistry, pharmacology, and clinical science. Central to this initiative is the open-access, rapid dissemination of data, methods, and computational and experimental tools generated by the Centers to all qualified researchers for their use in advancing AD drug discovery and AD disease biology.

Background

Alzheimer’s disease (AD) is the most common cause of dementia in elderly persons and is among the greatest healthcare challenges of the 21st century. The disease currently affects an estimated 5.5 million in the United States; by 2050 this number could rise as high as 14 million. Delaying symptom onset by five years could reduce disease prevalence by as much as 50%; this would significantly reduce the human burden and health care costs associated with the disease. Unfortunately, the clinically available therapies fall short of this requirement and provide only limited and temporary relief of symptoms. Therefore, to avert this large and escalating public health crisis, new therapies that effectively prevent, slow the progression or improve the symptoms of AD are urgently needed.  Unfortunately, despite more than two decades of massive investment and research, not one drug purported to prevent, slow, or cure AD has successfully completed the FDA-required clinical testing process. In fact, over this timespan there has been an extremely high attrition rate of AD treatments in Phase II and Phase III, with more than half failing due to issues of efficacy.

Many factors have contributed to the lack of progress in developing effective AD therapies, including the strong possibility that AD drug candidates have failed in the clinic because their development has been based on a very narrow understanding of the disease that is centered on the amyloid hypothesis. In contrast to this conventional wisdom, growing amounts of new data suggest that clinical AD is a highly heterogeneous, multimodal and multicomponent disease, caused by manifold genetic and environmental factors acting to perturb molecular networks across multiple interrelated biological pathways. This realization, coupled with the failure of numerous anti-amyloid drugs, has raised a degree of skepticism on the current amyloid-based model of AD and has highlighted the need for alternative therapeutic approaches that require the identification of next generation, novel AD drug targets. Therefore, to improve, reinvigorate and diversify the AD drug development pipeline, next generation targets must be evaluated, prioritized, and advanced into drug discovery campaigns.

In 2013 the NIA launched the AMP-AD Target Discovery initiative to facilitate the discovery and preclinical validation of the next-generation AD drug targets. AMP-AD is a large-scale, open-science consortium and, as such, all generated data and analysis are deposited into a common data sharing platform—the AMP-AD Wall of Targets —for rapid and broad dissemination into the public domain. The overarching aims of AMP-AD include: building a predictive, multiscale model of AD that better represents disease heterogeneity; identifying potential therapeutic targets; and gaining a systems-level understanding of the gene, protein, and metabolic networks within which the targets operate. To accomplish these goals AMP-AD has taken a systems and network biology approach that integrates multiple outcome measures (i.e., genetic, neuropathological, clinical, neuroimaging, fluid biomarker, and environmental), together with state-of-the art, multi-level “-omics” of normal and AD human brain, cell and animal model bio-samples. Taken together, these data have been used to generate experimental gene/protein interaction networks that, in turn, have been used to build computational models of AD. Through this process AMP-AD investigators have identified a series of novel molecular networks, and their key regulators or network drivers, that are associated with different, stage-specific AD endophenotypes. Given that the network drivers represent genes/proteins, it is highly plausible that some of these nodal points are potential drug targets. Based on these suppositions, an analysis, across the AMP-AD consortium, of molecular networks and their key drivers has led to the identification of more than 30 candidate drug targets.

Target identification is a critical first step in the drug discovery pipeline; however, before integration into a drug discovery campaign a candidate target must undergo an evaluation and prioritization process. This typically includes an assessment across a common set of selection criteria such as genetic evidence, druggability, assay-ability, availability of crystal structure, and availability of known ligands, followed by preclinical validation aimed at understanding target biology and demonstrating a functional role of the target in a disease phenotype. The robust validation of candidate drug targets requires the integral use of a diverse set of approaches, tools, reagents, and information; these include computational approaches to assist in target prioritization, and tools/reagents for experimental target validation. The challenge to fully evaluating, prioritizing and advancing candidate targets into drug discovery is that many of the targets are not well studied, and for most there are no tools or reagents for target validation or drug discovery. Therefore, to capitalize on the innovations and discoveries of AMP-AD, and other target discovery programs, it is imperative to design and develop tools, methods and reagents that will enable next generation AD drug targets for entry into drug discovery. The open dissemination of these experimental tools, methods and reagents, to all qualified scientists, will ensure collaborative, transparent, and reproducible research, and eventually de-risk potential therapeutics to the point that industry will invest in them, accelerating the delivery of new drugs to AD patients.

Research Objectives and Scope

The overarching objective of this initiative is to create Alzheimer Translational Centers focused on improving, diversifying and reinvigorating the AD drug development pipeline. Further, this program aims to de-risk potential therapeutics to the point that industry will invest in them, thereby accelerating the delivery of new drugs to AD patients. To this end, the new Centers will bring together technology and expertise needed to design and develop tools and methods that enable the characterization and experimental validation of candidate drug targets, including those emanating from the AMP-AD, and initiate drug discovery campaigns against these targets. In addition, this initiative will promote the open-access, rapid dissemination of all data, methods, and tools generated by the Centers to all qualified researchers, for their use in advancing AD drug discovery and/or elucidating disease biology. To achieve these goals the Centers will need to bring together multi-disciplinary teams of experts in computational biology, network biology, disease biology, biochemistry, biophysics, structural biology, biostatistics, assay development, medicinal chemistry, pharmacology, and clinical science.

Specifically, this FOA will provide support for:

  1. developing computational and bioinformatic tools and methods to assess multicomponent data emanating from the AMP-AD/AMP-AD Wall of Targets and other NIA-funded target discovery programs to assist in prioritizing drug targets for validation and drug discovery;
  2. designing and developing research reagents, tools and methods that support target enabling packages (TEPs) for prioritized drug targets, to be used for the validation and integration of drug targets into drug discovery campaigns;
  3. developing and optimizing assay systems for target validation and early stage drug discovery;
  4. launching robust early drug discovery campaigns against prioritized/enabled candidate drug targets;
  5. delivering lead compounds suitable for further drug development and for efficacy testing in AD animal models (e.g., through the NIA-funded MODEL-AD program); and
  6. establishing a publicly available data sharing platform housing all data generated by the Center.

In addition, this initiative will promote the rapid dissemination of all tools and methods generated by the Center to all qualified researchers for their use in drug discovery and advancing the understanding of disease biology.

Specific areas of research interest include but are not limited to:

  • Developing computational tools and bioinformatic methods that assess evidence on candidate targets emanating from the AMP-AD/AMP-AD Wall of Targets and other target identification programs to support prioritization of candidate drug targets for experimental validation and drug discovery.
  • Developing reagents, tools and methods that support Target Enabling Packages (TEPs) for characterization and validation candidate targets. A typical TEP tool kit will include the following:
  • purified target proteins to assess biochemical and biophysical properties
  • methods to determine 3-D structures using the latest technology i.e., cryo-EM
  • antibodies and/or nanobodies against target proteins
  • small molecule molecular probes that modulate the activity and function of target proteins
  • siRNA and gene editing tools (e.g., CRISPR/Cas9) for manipulation of target protein genes
  • in silico tools and methods for virtual ligand screening and profiling
  • suite of assay platforms to assess ligand binding, enzyme activity, biophysical properties, including High Throughput Screen (HTS) assays for molecular probe discovery and cell-based assays to measure target engagement and assess biological target activity and downstream consequences of target modulation
  • Launching early drug discovery campaigns for enabled candidate targets. A typical drug discovery campaign will include the following:
  • chemical libraries for robotic and in silico screening
  • cheminformatics tools and methods
  • a suite of screening platforms to identify molecular probes, “hit” compounds, including robotic and in silico HTS and phenotypic screens with emphasis on human iPSCs
  • iterative, hit-to-lead medicinal chemistry for optimization of drug-like properties, potency, target selectivity, and pharmacological properties
  • tools and methods that enable in silico pharmacology
  • selectivity and counter-screening assays to address potential activity at related targets and other undesirable activities or artifacts
  • assays and tools for pharmacological characterization including early pharmacokinetic and ADME/T profiling lead candidates
  • assays for early toxicology profiling of lead candidates
  • cell-based and animal models to assess in vivo efficacy and target engagement of lead candidates
  • Developing strategies and web-based infrastructure for rapid, open-access dissemination of data and methodology and for rapid distribution of all tools and methods for their use in AD therapy development.
Overall Organization of the Center

The Center should have the following structure:

  • The Administrative and Data Management Core will serve as the focus for the synergistic activities of the Center. Through the Steering Committee, it will be responsible for managing, coordinating, and supervising the entire range of Center activities, including monitoring progress and ensuring that the overall project management plan is effectively implemented and that yearly milestones are achieved within proposed timelines. In addition, the Core will be responsible for: maintaining an internal and an outward facing, publicly available data platform housing data generated by the Center; oversight for open-access sharing and distribution of tools, assays, models, methods and data to all qualified scientists from the academic and biopharma communities; and organizing an annual meeting held to facilitate communication and collaboration among Center scientists, members of the External Advisory Board (EAB), and scientists from other NIA-funded Centers.
  • The Bioinformatics and Computational Biology Core will develop and deploy analytical tools and methods that enable the identification and prioritization of candidate drug targets for experimental validation and entry into drug discovery. For this purpose, the Core will use both standard and innovative biostatistics, bioinformatics and computational biology approaches to analyze and interpret high-dimensional data emanating from the AMP-AD and deposited on the AMP-AD Wall of Targets platform and from other external databases (i.e., ADSP, ADGC, ADNI, MODEL-AD).
  • The Structural Biology Core will develop high-quality reagents, tools and methods that support Target Enabling Packages (TEPs) for the experimental characterization, validation, and eventual translation of candidate targets into drug discovery campaigns. The Core will be responsible for cloning and sub-cloning candidate target genes; protein production; biochemical and biophysical characterization of candidate target proteins; determination of 3-D protein structures using cutting-edge technologies (i.e., cryo-EM); in silico approaches that inform target validation; design and production of recombinant antibodies; and design of siRNA/shRNA and gene editing tools for target gene manipulations. This Core, in collaboration with the Assay Development Core, will develop biochemical assays suitable for functional characterization and cell-based assays for target modulation, including phenotypic screens with emphasis on human iPSCs.
  • The Assay Development and High Throughput Screening Core will develop innovative assay and screening methods to enable a wide range of the Center’s activities, including characterization and experimental validation of candidate targets and drug discovery. Specific capabilities should include assay design, optimization, validation, miniaturization and transfer. The Core will develop: high throughput screens (HTS); biochemical and cell-based assays for target modulation including phenotypic screens with emphasis on human iPSCs; HTS screening platforms to identify “hit” compounds for molecular probe and small molecule drugs; and screens for early cytotoxicity profiling of “hits” and lead candidates. In addition, the Core will provide support for interpretation and analysis of data derived from these assays.
  • The Medicinal Chemistry and Chemical Biology Core will provide molecular probe development and drug discovery services to Center. These will include: custom library development, synthesis and curation; in silico HTS screening of compounds libraries; advanced cheminformatics analysis on primary robotic and in silico high-throughput HTS hit data; computational resources for managing chemical structures and data; scale-up synthesis for hit validation and medicinal chemistry optimization; computational docking studies and analyses; molecular probe synthesis for target validation; chemical biology approaches to selectively modulate the activity of candidate drug targets; synthetic medicinal chemistry for hit-to-lead optimization; structure-activity relationship (SAR) analysis; fragment-based drug discovery; analysis of drug-like and physical-chemical properties (i.e. drug stability and solubility); support for drug structural determination (i.e., NMR, MS); and exploratory pharmacology (i.e., early PK and ADME/T profiling).
  • The Center Steering Committee will serve as the operational governing board. The Steering Committee should include the PD(s)/PI(s), Unit leads, the NIH Project Scientist (voting), and external scientist(s) (if required). Among other functions, the Steering Committee will have primary responsibility for finalizing standard procedures and protocols; holding regular webinars/teleconferences; developing a prioritized portfolio of therapeutic targets for validation and drug discovery; deciding which  drug target projects will be initiated by the Center; and evaluation of lead candidates generated by the Center and their prioritization for entry into animal efficacy studies (MODEL-AD) and entry into  other NIA/NIH drug development programs.
  • The External Advisory Board should be organized from non-conflicted experts outside of the Center to guide the Center leadership in assessing the Center’s progress in achieving the yearly milestones, assessing new scientific opportunities as they are presented and evaluating the effectiveness of interaction among Cores and Center participants. The external advisory board will advise the steering committee on different aspects of the Center’s function, including prioritization of projects; changes in direction or approach; sharing of tools, methods and data; and problem identification and resolution.
Milestones

Milestone-driven research is used to ensure research is focused on a well-defined goal and achieving that goal with greatest efficiency. As translational research is inherently high risk, the use of milestones provides clear indicators of a project’s continued success or emergent difficulties. The milestones must provide objective and quantitative success criteria which are recognizable as appropriate endpoints for a specific scientific goal and that can be used to monitor the progress made by a research project. The milestones will serve as a basis for go/no-go decision making between NIA program staff and the project research team. Prior to funding of an application, NIA Program staff will contact the applicant to discuss the proposed milestones and any modifications to the milestones as recommended by the review committee or NIA Program staff. A final set of approved milestones will be specified in the Notice of Award. Progress towards achievement of the established milestones will be evaluated by a committee composed of NIA Program Staff. NIA staff may seek advice from staff from other NIH ICs with relevant expertise, as necessary. If warranted, the milestones for future years may be revised based on data and research progress during the preceding year.

Deadline:  January 1, 2019 (letters of intent); February 1, 2019 (full proposals)

URL:  https://grants.nih.gov/grants/guide/rfa-files/RFA-AG-19-010.html

Filed Under: Funding Opportunities