The amyloid-beta (Aβ) hypothesis of Alzheimer's disease (AD) causality is now well into its third decade and is finally entering a phase of rigorous clinical testing in numerous late stage clinical trials. The use of Aβ-based animal models of AD has been essential to the discovery and/or preclinical validation of many of these therapeutic approaches. While several neuropathologically based results from preclinical studies have translated nicely into AD patients, the full clinical value of Aβ-directed therapies awaits results from trials now in progress.
Successful disease modifying drug development for Alzheimer’s disease (AD) has hit a roadblock with the recent failures of amyloid-based therapies, highlighting the translational disconnect between preclinical animal models and clinical outcome. Although disease modifying therapies are the Holy Grail to pursue, symptomatic therapies addressing cognitive and neuropsychiatric aspects of the disease are also extremely important for the quality of life of patients and caregivers. Despite the fact that neuropsychiatric problems in Alzheimer patients are the major driver for costs associated with institutionalization, no good preclinical animal models with predictive validity have been documented. We propose a combination of quantitative systems pharmacology (QSP), phenotypic screening and preclinical animal models as a novel strategy for addressing the bottleneck in both cognitive and neuropsychiatric drug discovery and development for AD. Preclinical animal models such as transgene rats documenting changes in neurotransmitters with tau and amyloid pathology will provide key information that together with human imaging, pathology and clinical data will inform the virtual patient model. In this way QSP modeling can partially overcome the translational disconnect and reduce the attrition of drug programs in the clinical setting. This approach is different from target driven drug discovery as it aims to restore emergent properties of the networks and therefore likely will identify multitarget drugs. We review examples on how this hybrid humanized QSP approach has been helpful in predicting clinical outcomes in schizophrenia treatment and cognitive impairment in AD and expand on how this strategy could be applied to neuropsychiatric symptoms in dementia. We believe such an innovative approach when used carefully could change the Research and Development paradigm for symptomatic treatment in AD.
computer simulation; Alzheimer’s disease; apathy; cognitive disorders; drug discovery
Amyotrophic lateral sclerosis is a devastating neurodegenerative disease caused by loss of motor neurons. Its pathophysiology remains unknown, but progress has been made in understanding its genetic and biochemical basis. Clinical trialists are working to translate basic science successes into human trials with more efficiency, in the hope of finding successful treatments. In the future, new preclinical models, including patient-derived stem cells may augment transgenic animal models as preclinical tools. Biomarker discovery projects aim to identify markers of disease onset and progression for use in clinical trials. New trial designs are reducing study time, improving efficiency and helping to keep pace with the increasing rate of basic and translational discoveries. Ongoing trials with novel designs are paving the way for amyotrophic lateral sclerosis clinical research.
antisense oligonucleotide; continual reassessment model; futility design study; induced pluripotent stem cells; selection design study
A substantial number of therapeutic drugs for Alzheimer's disease (AD) have failed in late-stage trials, highlighting the translational disconnect with pathology-based animal models.
To bridge the gap between preclinical animal models and clinical outcomes, we implemented a conductance-based computational model of cortical circuitry to simulate working memory as a measure for cognitive function. The model was initially calibrated using preclinical data on receptor pharmacology of catecholamine and cholinergic neurotransmitters. The pathology of AD was subsequently implemented as synaptic and neuronal loss and a decrease in cholinergic tone. The model was further calibrated with clinical Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-Cog) results on acetylcholinesterase inhibitors and 5-HT6 antagonists to improve the model's prediction of clinical outcomes.
As an independent validation, we reproduced clinical data for apolipoprotein E (APOE) genotypes showing that the ApoE4 genotype reduces the network performance much more in mild cognitive impairment conditions than at later stages of AD pathology. We then demonstrated the differential effect of memantine, an N-Methyl-D-aspartic acid (NMDA) subunit selective weak inhibitor, in early and late AD pathology, and show that inhibition of the NMDA receptor NR2C/NR2D subunits located on inhibitory interneurons compensates for the greater excitatory decline observed with pathology.
This quantitative systems pharmacology approach is shown to be complementary to traditional animal models, with the potential to assess potential off-target effects, the consequences of pharmacologically active human metabolites, the effect of comedications, and the impact of a small number of well described genotypes.
The rising prevalence of Alzheimer’s disease (AD) is rapidly becoming one of the largest health and economic challenges in the world. There is a growing need for the development and implementation of reliable biomarkers for AD that can be used to assist in diagnosis, inform disease progression, and monitor therapeutic efficacy. Preclinical models permit the evaluation of candidate biomarkers and assessment of pipeline agents before clinical trials are initiated and provide a translational opportunity to advance biomarker discovery. Fast and inexpensive data can be obtained from examination of peripheral markers, though they currently lack the sensitivity and consistency of imaging techniques such as MRI or PET. Plasma and cerebrospinal fluid (CSF) biomarkers in animal models can assist in development and implementation of similar approaches in clinical populations. These biomarkers may also be invaluable in decisions to advance a treatment to human testing. Longitudinal studies in AD models can determine initial presentation and progression of biomarkers that may also be used to evaluate disease-modifying efficacy of drugs. The refinement of biomarker approaches in preclinical systems will not only aid in drug development, but may facilitate diagnosis and disease monitoring in AD patients.
Alzheimer’s disease; biomarkers; animal models; drug development
To improve human health, scientific discoveries must be translated into practical applications. Inherent in the development of these technologies is the role of preclinical testing using animal models. Although significant insight into the molecular and cellular basis has come from small animal models, significant differences exist with regard to cardiovascular characteristics between these models and humans. Therefore, large animal models are essential to develop the discoveries from murine models into clinical therapies and interventions.
This paper will provide an overview of the more frequently used large animal models, especially porcine models for preclinical studies.
Although in vitro screens are essential for the initial identification of candidate therapeutic agents, a rigorous assessment of the drug's ability to inhibit tumor growth must be performed in a suitable animal model. The type of animal model that is best for this purpose is a topic of intense discussion. Some evidence indicates that preclinical trials examining drug effects on tumors arising in transgenic mice are more predictive of clinical outcome1and so candidate therapeutic agents are often tested in these models. Unfortunately, transgenic models are not available for many tumor types. Further, transgenic models often have other limitations such as concerns as to how well the mouse tumor models its human counterpart, incomplete penetrance of the tumor phenotype and an inability to predict when tumors will develop.
Consequently, many investigators use xenograft models (human tumor cells grafted into immunodeficient mice) for preclinical trials if appropriate transgenic tumor models are not available. Even if transgenic models are available, they are often partnered with xenograft models as the latter facilitate rapid determination of therapeutic ranges. Further, this partnership allows a comparison of the effectiveness of the agent in transgenic tumors and genuine human tumor cells. Historically, xenografting has often been performed by injecting tumor cells subcutaneously (ectopic xenografts). This technique is rapid and reproducible, relatively inexpensive and allows continuous quantitation of tumor growth during the therapeutic period2. However, the subcutaneous space is not the normal microenvironment for most neoplasms and so results obtained with ectopic xenografting can be misleading due to factors such as an absence of organ-specific expression of host tissue and tumor genes. It has thus been strongly recommended that ectopic grafting studies be replaced or complemented by studies in which human tumor cells are grafted into their tissue of origin (orthotopic xenografting)2. Unfortunately, implementation of this recommendation is often thwarted by the fact that orthotopic xenografting methodologies have not yet been developed for many tumor types.
Malignant peripheral nerve sheath tumors (MPNSTs) are highly aggressive sarcomas that occur sporadically or in association with neurofibromatosis type 13and most commonly arise in the sciatic nerve4. Here we describe a technically straightforward method in which firefly luciferase-tagged human MPNST cells are orthopically xenografted into the sciatic nerve of immunodeficient mice. Our approach to assessing the success of the grafting procedure in individual animals and subsequent non-biased randomization into study groups is also discussed.
Oxidative damage is strongly implicated in the pathogenesis of neurodegenerative diseases including Alzheimer’s disease, amyotrophic lateral sclerosis, Huntington’s disease, Parkinson’s disease and stroke (brain ischemia/reperfusion injury). The availability of transgenic and toxin-inducible models of these conditions has facilitated the preclinical evaluation of putative antioxidant agents ranging from prototypic natural antioxidants such as vitamin E (α-tocopherol) to sophisticated synthetic free radical traps and catalytic oxidants. Literature review shows that antioxidant therapies have enjoyed general success in preclinical studies across disparate animal models, but little benefit in human intervention studies or clinical trials. Recent high-profile failures of vitamin E trials in Parkinson’s disease, and nitrone therapies in stroke, have diminished enthusiasm to pursue antioxidant neuroprotectants in the clinic. The translational disappointment of antioxidants likely arises from a combination of factors including failure to understand the drug candidate’s mechanism of action in relationship to human disease, and failure to conduct preclinical studies using concentration and time parameters relevant to the clinical setting. This review discusses the rationale for using antioxidants in the prophylaxis or mitigation of human neurodiseases, with a critical discussion regarding ways in which future preclinical studies may be adjusted to offer more predictive value in selecting agents for translation into human trials.
Alzheimer’s disease; amyotrophic lateral sclerosis; antioxidants; Huntington’s disease; neurodegeneration; neuroinflammation; Parkinson’s disease; tocopherols
Scientific research involving non‐human primates has contributed towards many advances in medicine and surgery. This review discusses its role in the progress made towards our understanding of Parkinson's disease and its treatment. Established medical treatments like dopamine agonists continue to need primate models to assess their efficacy, safety, and mechanism of action. The recently developed treatment of deep brain stimulation of the subthalamic nucleus required validation in primates before entering the clinic. Controversies surrounding future treatments such as gene therapy show the need for properly evaluated preclinical research using appropriate animal models before progression to clinical trials. Research on primates has played—and continues to play—a crucial part in deepening our understanding of Parkinson's disease, improving current therapies, and developing new treatments that are both safe and effective. In animal research, the “three Rs” of humane technique—reduction, refinement, and replacement—should be adhered to.
Parkinson's disease; animals; basal ganglia; history; primates
Alzheimer disease (AD) is the most common form of dementia. The amyloid-β (Aβ) peptide has become a major therapeutic target in AD on the basis of pathological, biochemical and genetic evidence that supports a role for this molecule in the disease process. Active and passive Aβ immunotherapies have been shown to lower cerebral Aβ levels and improve cognition in animal models of AD. In humans, dosing in the phase II clinical trial of the AN1792 Aβ vaccine was stopped when ~6% of the immunized patients developed meningoencephalitis. However, some plaque clearance and modest clinical improvements were observed in patients following immunization. As a result of this study, at least seven passive Aβ immunotherapies are now in clinical trials in patients with mild to moderate AD. Several second-generation active Aβ vaccines are also in early clinical trials. On the basis of preclinical studies and the limited data from clinical trials, Aβ immunotherapy might be most effective in preventing or slowing the progression of AD when patients are immunized before or in the very earliest stages of disease onset. Biomarkers for AD and imaging technology have improved greatly over the past 10 years and, in the future, might be used to identify presymptomatic, at-risk individuals who might benefit from Aβ immunization.
Preclinical animal models have supported much of the recent rapid expansion of neuroscience research and have facilitated critical discoveries that undoubtedly benefit patients suffering from psychiatric disorders. This overview serves as an introduction for the following chapters describing both in vivo and in vitro preclinical models of psychiatric disease components and briefly describes models related to drug dependence and affective disorders. Although there are no perfect animal models of any psychiatric disorder, models do exist for many elements of each disease state or stage. In many cases, the development of certain models is essentially restricted to the human clinical laboratory domain for the purpose of maximizing validity, whereas the use of in vitro models may best represent an adjunctive, well-controlled means to model specific signaling mechanisms associated with psychiatric disease states. The data generated by preclinical models are only as valid as the model itself, and the development and refinement of animal models for human psychiatric disorders continues to be an important challenge. Collaborative relationships between basic neuroscience and clinical modeling could greatly benefit the development of new and better models, in addition to facilitating medications development.
Animal model; Anxiety; Depression; Drug addiction; Preclinical model; Psychiatric disorders; Stress
Animal models with high predictive power are a prerequisite for translational research. The closer the similarity of a model to Parkinson’s disease (PD), the higher is the predictive value for clinical trials. An ideal PD model should present behavioral signs and pathology that resemble the human disease. The increasing understanding of PD stratification and etiology, however, complicates the choice of adequate animal models for preclinical studies. An ultimate mouse model, relevant to address all PD-related questions, is yet to be developed. However, many of the existing models are useful in answering specific questions. An appropriate model should be chosen after considering both the context of the research and the model properties. This review addresses the validity, strengths, and limitations of current PD mouse models for translational research.
The Mary S. Easton Center for Alzheimer’s Disease Research (UCLA-Easton Alzheimer’s Center) is committed to the “therapeutic imperative” and is devoted to finding new treatments for Alzheimer’s disease (AD) and to developing technologies (biomarkers) to advance that goal. The UCLA-Easton Alzheimer’s Center has a continuum of research and research-related activities including basic/foundational studies of peptide interactions; translational studies in transgenic animals and other animal models of AD; clinical research to define the phenotype of AD, characterize familial AD, develop biomarkers, and advance clinical trials; health services and outcomes research; and active education, dissemination, and recruitment activities. The UCLA-Easton Alzheimer’s Center is supported by the National Institutes on Aging, the State of California, and generous donors who share our commitment to developing new therapies for AD. The naming donor (Jim Easton) provided substantial funds to endow the center and to support projects in AD drug discovery and biomarker development. The Sidell-Kagan Foundation supports the Katherine and Benjamin Kagan Alzheimer’s Treatment Development Program, and the Deane F. Johnson Alzheimer’s Research Foundation supports the Deane F. Johnson Center for Neurotherapeutics at UCLA. The John Douglas French Alzheimer’s Research Foundation provides grants to junior investigators in critical periods of their academic development. The UCLA-Easton Alzheimer’s Center partners with community organizations including the Alzheimer’s Association California Southland Chapter and the Leeza Gibbons memory Foundation. Collaboration with pharmaceutical companies, biotechnology companies, and device companies is critical to developing new therapeutics for AD and these collaborations are embraced in the mission of the UCLA-Easton Alzheimer’s Center. The Center supports excellent senior investigators and serves as an incubator for new scientists, agents, models, technologies and concepts that will significantly influence the future of AD treatment and AD research.
The initial Stroke Therapy Academic Industry Roundtable (STAIR) recommendations published in 1999 were intended to improve the quality of preclinical studies of purported acute stroke therapies. Although recognized as reasonable, they have not been closely followed nor rigorously validated. Substantial advances have occurred regarding the appropriate quality and breadth of preclinical testing for candidate acute stroke therapies for better clinical translation. The updated STAIR preclinical recommendations reinforce the previous suggestions that reproducibly defining dose response and time windows with both histological and functional outcomes in multiple animal species with appropriate physiological monitoring is appropriate. The updated STAIR recommendations include: the fundamentals of good scientific inquiry should be followed by eliminating randomization and assessment bias, a priori defining inclusion/exclusion criteria, performing appropriate power and sample size calculations, and disclosing potential conflicts of interest. After initial evaluations in young, healthy male animals, further studies should be performed in females, aged animals, and animals with comorbid conditions such as hypertension, diabetes, and hypercholesterolemia. Another consideration is the use of clinically relevant biomarkers in animal studies. Although the recommendations cannot be validated until effective therapies based on them emerge from clinical trials, it is hoped that adherence to them might enhance the chances for success.
preclinical; stroke models; therapy
Most therapeutic agents used in clinical practice today were originally developed and tested in animal models so that drug toxicity and safety, dose-responses and efficacy could be determined. Retrospective analyses of preclinical intervention studies using animal models of different diseases demonstrate that only a small percentage of the interventions reporting promising effects translate to clinical efficacy. The failure to translate therapeutic efficacy from bench to bedside may be due, in part, to shortcomings in the design of the clinical studies; however, it is becoming clear that much of the problem resides within the preclinical studies. One potential strategy for improving our ability to identify new therapeutics that may have a reasonable chance of success in well-controlled clinical trials is to identify the most relevant mouse models IBD and pharmacologic strategies that most closely mimic the clinical situation. To begin this process, we present a critical evaluation of the different mouse models and pharmacological approaches that may be used in intervention studies as well as discuss emerging issues related to study design and data interpretation of preclinical studies.
small molecules; therapeutics; biologics; cytokines; cell-based therapy; T-cells; regulatory T-cells; blood flow
In drug development, phase 1 first-in-human studies represent a major milestone as the drug moves from preclinical discovery to clinical development activities. The safety of human subjects is paramount to the conduct of these studies and regulatory considerations guide activities. Forces of evolution on the pharmaceutical industry are re-shaping the first-in-human dose selection strategy. Namely, high attrition rates in part due to lack of efficacy have led to the re-organization of research and development organizations around the umbrella of translational research. Translational research strives to bring basic research advances into the clinic and support the reverse transfer of information to enhance compound selection strategies. Pharmacokinetic/pharmacodynamic (PK/PD) modeling holds a unique position in translational research by attempting to integrate diverse sets of information. PK/PD modeling has demonstrated utility in dose selection and trial design for later stages of drug development and is now being employed with greater prevalence in the translational research setting to manage risk (i.e., oncology and inflammation/immunology). Moving from empirical Emax models to more mechanistic representations of the biological system, a higher fidelity of human predictions is expected. Strategies that have proven useful for PK predictions are being applied to PK/PD predictions. This review article examines examples of the application of PK/PD modeling in establishing target concentrations for supporting first-in-human study design.
biomarker; drug development; pharmacodynamics; pharmacokinetics; PK/PD; translation
Despite advances in understanding cancer at the molecular level, timely and effective translation to clinical application of novel therapeutics in human cancer patients is lacking. Cancer drug failure is often a result of toxicity or inefficacy not predicted by preclinical models, emphasizing the need for alternative animal tumor models with improved biologic relevancy. Companion animals (dogs and cats) provide an opportunity to capitalize on an underutilized and biologically relevant translational research model which allows spontaneous disease modeling of human cancer. Head and neck squamous cell carcinoma (HNSCC) is a common cancer with a poor prognosis and limited clinical advancements in recent years. One potential novel spontaneous animal tumor model is feline oral squamous cell carcinoma (FOSCC). FOSCC and HNSCC share similar etiopathogenesis (tobacco and papillomavirus exposure) and molecular markers (EGFR, VEGF, and p53). Both human and feline SCCs share similar tumor biology, clinical outcome, treatment, and prognosis. Future clinical trials utilizing FOSCC as a tumor model may facilitate translation of preclinical cancer research for human cancer patients.
The Stroke Therapy Academic Industry Roundtable (STAIR) provided initial (in 1999) and updated (in 2009) recommendations with the goal of improving preclinical stroke therapy assessment and to increase the translational potential of experimental stroke treatments. It is important for preclinical stroke researchers to frequently consider and revisit these concepts, especially since promising experimental stroke treatments continue to fail in human clinical trials. Therefore, this paper will focus on considerations for several key aspects of preclinical stroke studies including the selection and execution of the animal stroke model, drug/experimental treatment administration, and outcome measures to improve experimental validity and translation potential. Specific points of interest discussed include the incorporation of human comorbid conditions and drugs, the benefits of defining a proposed mechanism of action, replication of results using multiple methods, using clinically relevant routes of administration and treatment time windows, and performing and reporting good experimental methods to reduce bias such as, as suggested by the updated STAIR recommendations, sample size calculations, randomization, allocation concealment, blinding, and appropriate inclusion/exclusion criteria. It is our hope that reviewing and revisiting these considerations will benefit researchers in their investigations of stroke therapies and increase the likelihood of translational success in the battle against stroke.
Despite great advances in basic neuroscience knowledge, the improved understanding of brain functioning has not yet led to the introduction of truly novel pharmacological approaches to the treatment of central nervous system disorders. This situation has been partly attributed to the difficulty of predicting efficacy in patients based on results from preclinical studies. To address these issues, this review critically discusses the traditional role of animal models in drug discovery, the difficulties encountered, and the reasons why this approach has led to suboptimal utilization of the information animal models provide. The discussion focuses on how animal models can contribute most effectively to translational medicine and drug discovery and the changes needed to increase the probability of achieving clinical benefit. Emphasis is placed on the need to improve the flow of information from the clinical/human domain to the preclinical domain and the benefits of using truly translational measures in both preclinical and clinical testing. Few would dispute the need to move away from the concept of modeling CNS diseases in their entirety using animals. However, the current emphasis on specific dimensions of psychopathology that can be objectively assessed in both clinical populations and animal models has not yet provided concrete examples of successful preclinical-clinical translation in CNS drug discovery. The purpose of this review is to strongly encourage ever more intensive clinical and preclinical interactions to ensure that basic science knowledge gained from improved animal models with good predictive and construct validity readily becomes available to the pharmaceutical industry and clinical researchers to benefit patients as quickly as possible.
Preclinical evaluation of antibody-based immunotherapies for the treatment of type 1 diabetes (T1D) in animal models is often hampered by the fact that the human antibody drug does not cross-react with its mouse counterpart. In this issue of Science Translational Medicine, researchers describe a new mouse model that expresses the human isoform of a molecule targeted by T1D antibody therapies that are currently being tested in clinical trials—the human epsilon chain of the CD3 complex expressed on T cells. Anti-CD3 is capable of reducing insulin needs in individuals with recently diagnosed T1D; however, the precise underlying mechanisms of action and the minimal effective dose have been difficult to define. The new humanized mouse model will be instrumental in optimizing anti-CD3–based therapies and accelerating their clinical realization.
Dementia disorders are characterized by clinicopathological criteria. Molecular understandings of these disorders, based on immunohistochemical studies, biochemical investigations, genetic approaches, and animal models have resulted in advances in diagnosis. Likewise translational research has allowed application of increasing basic scientific knowledge regarding neurodegeneration, to the rational development of new investigational therapies based on current understanding of disease pathogenesis. This review discusses application of translational research to both diagnosis and treatment of dementia disorders. The development of biomarkers has yielded imaging and biochemical methods that more assist in the diagnosis of neurodegenerative dementias, especially Alzheimer’s disease. New diagnostic criteria for disease are based on these molecular-based techniques. And these biomarkers are of potential use in monitoring disease activity during therapeutic trials. Translational investigations likewise have led towards new avenues in targeted dementia research. This is particularly so in the development and testing of disease-modifying treatments that might slow or deter progressive deterioration. Recent clinical trials have not been based on empiric trial of established drugs, but rather upon trial of drugs shown through culture and animal models to interfere with known elements of the pathogenetic cascade of Alzheimer disease.
The identification of genes linked to neurodegenerative diseases such as Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), Huntington's disease (HD) and Parkinson's disease (PD) has led to the development of animal models for studying mechanism and evaluating potential therapies. None of the transgenic models developed based on disease-associated genes have been able to fully recapitulate the behavioral and pathological features of the corresponding disease. However, there has been enormous progress made in identifying potential therapeutic targets and understanding some of the common mechanisms of neurodegeneration. In this review, we will discuss transgenic animal models for AD, ALS, HD and PD that are based on human genetic studies. All of the diseases discussed have active or complete clinical trials for experimental treatments that benefited from transgenic models of the disease.
ALS; PD; AD; HD; Huntington's disease; Parkinson's disease; Amyotrophic lateral sclerosis; Alzheimer's disease; Transgenic; Animal model; Neurodegeneration; Genetic linkage
Traumatic brain injury (TBI) causes secondary biochemical changes that contribute to subsequent tissue damage and associated neuronal cell death. Neuroprotective treatments that limit secondary tissue loss and/or improve behavioral outcome have been well established in multiple animal models of TBI. However, translation of such neuroprotective strategies to human injury have been disappointing, with more than thirty controlled clinical trials having failed. Both conceptual issues and methodological differences between preclinical and clinical injury have undoubtedly contributed to these translational difficulties. More recently, changes in experimental approach, as well as altered clinical trial methodologies, have raised cautious optimism regarding outcomes of future clinical trials. Here, we critically review developing experimental neuroprotective strategies that show promise and propose criteria for improving the probability of successful clinical translation.
Research in animals and humans has associated Alzheimer’s disease (AD) with decreased cerebrospinal fluid levels of insulin in combination with decreased insulin sensitivity (insulin resistance) in the brain. This phenomenon is accompanied by attenuated receptor expression of insulin and insulin-like growth factor, enhanced serine phosphorylation of insulin receptor substrate-1, and impaired transport of insulin across the blood-brain barrier. Moreover, clinical trials have demonstrated that intranasal insulin improves both memory performance and metabolic integrity of the brain in patients suffering from AD or its prodrome, mild cognitive impairment. These results, in conjunction with the finding that insulin mitigates hippocampal synapse vulnerability to beta amyloid, a peptide thought to be causative in the development of AD, provide a strong rationale for hypothesizing that pharmacological strategies bolstering brain insulin signaling, such as intranasal administration of insulin, could have significant potential in the treatment and prevention of AD. With this view in mind, the review at hand will present molecular mechanisms potentially underlying the memory-enhancing and neuroprotective effects of intranasal insulin. Then, we will discuss the results of intranasal insulin studies that have demonstrated that enhancing brain insulin signaling improves memory and learning processes in both cognitively healthy and impaired humans. Finally, we will provide an overview of neuroimaging studies indicating that disturbances in insulin metabolism—such as insulin resistance in obesity, type 2 diabetes and AD—and altered brain responses to insulin are linked to decreased cerebral volume and especially to hippocampal atrophy.
What will it take to develop interventions for the treatment of age-related cognitive
decline? Session V of the Summit provided perspectives on the design of clinical trials to
evaluate promising but unproven interventions, and some of the steps needed to accelerate
the discovery and evaluation of promising treatments. It considered strategies to further
characterize the biological and cognitive changes associated with normal aging and their
translation into the development of new treatments. It provided regulatory, scientific,
and clinical perspectives about neurocognitive aging treatments, their potential benefits
and risks, and the strategies and endpoints needed to evaluate them in the most rapid,
rigorous, and clinically meaningful way. It considered lessons learned from the study of
Alzheimer's disease, the promising roles of biomarkers in neurocognitive aging
research, and ways to help galvanize the scientific study and treatment of neurocognitive
Cognition; Clinical trials; Aging