Precision pharmacology for Alzheimer's disease

Abstract

The complex multifactorial nature of polygenic Alzheimer's disease (AD) presents significant challenges for drug development. AD pathophysiology is progressing in a non-linear dynamic fashion across multiple systems levels - from molecules to organ systems - and through adaptation, to compensation, and decompensation to systems failure. Adaptation and compensation maintain homeostasis: a dynamic equilibrium resulting from the dynamic non-linear interaction between genome, epigenome, and environment. An individual vulnerability to stressors exists on the basis of individual triggers, drivers, and thresholds accounting for the initiation and failure of adaptive and compensatory responses. Consequently, the distinct pattern of AD pathophysiology in space and time must be investigated on the basis of the individual biological makeup. This requires the implementation of systems biology and neurophysiology to facilitate Precision Medicine (PM) and Precision Pharmacology (PP). The regulation of several processes at multiple levels of complexity from gene expression to cellular cycle to tissue repair and system-wide network activation has different time delays (temporal scale) according to the affected systems (spatial scale). The initial failure might originate and occur at every level potentially affecting the whole dynamic interrelated systems within an organism. Unraveling the spatial and temporal dynamics of non-linear pathophysiological mechanisms across the continuum of hierarchical self-organized systems levels and from systems homeostasis to systems failure is key to understand AD. Measuring and, possibly, controlling space- and time-scaled adaptive and compensatory responses occurring during AD will represent a crucial step to achieve the capacity to substantially modify the disease course and progression at the best suitable timepoints, thus counteracting disrupting critical pathophysiological inputs. This approach will provide the conceptual basis for effective disease-modifying pathway-based targeted therapies. PP is based on an exploratory and integrative strategy to complex diseases such as brain proteinopathies including AD, aimed at identifying simultaneous aberrant molecular pathways and predicting their temporal impact on the systems levels. The depiction of pathway-based molecular signatures of complex diseases contributes to the accurate and mechanistic stratification of distinct subcohorts of individuals at the earliest compensatory stage when treatment intervention may reverse, stop, or delay the disease. In addition, individualized drug selection may optimize treatment safety by decreasing risk and amplitude of side effects and adverse reactions. From a methodological point of view, comprehensive "omics"-based biomarkers will guide the exploration of spatio-temporal systems-wide morpho-functional shifts along the continuum of AD pathophysiology, from adaptation to irreversible failure. The Alzheimer Precision Medicine Initiative (APMI) and the APMI cohort program (APMI-CP) have commenced to facilitate a paradigm shift towards effective drug discovery and development in AD.

Keywords: Alzheimer’s disease; Clinical trials; Pathophysiology; Pathway-based therapy; Precision medicine; Precision pharmacology.

Fig. 1.

(A) Trajectory of pathophysiological mechanisms across the continuum of systems multi-scale hierarchical self-organization, from systems homeostasis to systems failure: conceptual basis for molecular pathway-based therapies. The preservation of human organism homeostasis is strictly related to the interactions between human systems factors, i.e. genome/epigenome and ecosystem factors, i.e. environment (the circles). Such interactions shows a non-linear fashion with complex dynamic changes over time that are essential at the individual level for adaptation and survival of the single organism to a certain ecosystem and at extra-individual level for adaptive (genetic) evolutionary transitions finally resulting in the trans-generational process of natural selection. For instance, the impact of a genetic mutation on a single organism may lead to wide-ranging severe maladaptive effects even though from an evolutionary trans-generational perspective this may represent a primary driver for optimized survival and reproduction. Therefore, adaptive responses are differently distributed in space and time scales, aimed at different key roles consistently with the individual, extra-individual and the trans-generational level. Unrevealing the spatial-temporal coordinates of multilevel adaptive events across human systems (from molecular level to system level) and between these and ecosystem will uncover key notions essential for the comprehensive understanding of complex disease and at an higher level of complexity to achieve a unified theory of genetic adaptation leading to evolution. Thus, an individual vulnerability to stressors exists with an individual threshold of anti-stress response activation and failure. The non-linear orange-shaped line represents the entire spectrum of pathophysiological mechanisms across all systems levels, during the course and progression of disease. Such alterations originate from initial adaptation processes leading through triggers, drivers, thresholds to a point of decompensation at both structural and functional level. The green circle surrounding the five levels represents the marked interplay among the different hierarchical self-organized systems levels. Such interactions support the hypothesis that the initial loss of homeostasis might originate and occur at every level taking into account that a single level potentially affects the whole dynamic interrelated system and, therefore, initially or ultimately the entire affected organism. The molecular level shows aberrant conformational states of proteins and dysregulated molecular pathways, including: post-translational modifications, inefficient autophagic mechanisms, dysfunction of membrane dynamics. The cellular level originates from the sum of a number of distinct and/or interrelated aberrant molecular pathways. This has a negative impact on anti-stress responses with a subsequent overall impairment of cytoprotective and homeostatic mechanisms. The tissue level presents a substantial loss of structural and functional organization induced by certain categories of cells. At brain system level, aberrant neural oscillatory, altered metabolic, blood-flow and oxygenation activities might successively or simultaneously occur across different brain system networks, thus affecting different network integration processes and the whole functioning of the system. Therefore, brain-wide shifts in large scale network functioning allow a spatial and temporal processing resources redistribution to cope with stressors. Such hypothetical model can explain how pathophysiological alterations at the brain system level may precede, support and impact abnormal upstream to downstream molecular and cellular pathways. The organ systems level represents an enormous and most complex interplay among several networks of different body systems including brain. The existence of many cross-links-talks between CNS and the periphery might account for the hypothesis that brain diseases can originate or be substantially related to peripheral failure. The idea of an isolated brain disease has to be critically assessed in view of the organ systems level. The colored pyramid represents potential outcome of effective treatment, the potential drug response at each level (from green to red and from the base to the peak there is a decreasing amplitude of effect). The arrows explain the likelihood to restore compensatory mechanisms (i.e. disease-modifying effect) at the single level; the thicker the arrow is, the higher is the chance that the treatment is effective. The “x” positioned in correspondence of the organ systems failure indicates a hypothetical “point of no return” (pathophysiological irreversibility threshold) without any significant possibility for the drug to reverse, stop or modify the disease dynamic and progression. Abbreviations: CNS, central nervous system. (B) Hypothetical model of spatio-temporal systems-wide shifts in large scale networks along the continuum of AD pathophysiological processes: from adaptation to irreversible failure. Organisms are made of systems which are entities consisting in hierarchically self-organized levels with increasing structural complexity resulting in different emerging properties. Multilevel systems are strictly and dynamically interconnected through feedback and cross-talking mechanisms. As a consequence, spatial selective network activation from molecular pathways to systems large scale networks as well as time-dependent cascade of activation can allow to achieve the most effective output to copy with stressors. This, in turn is aimed to maintain homeostasis a dynamic equilibrium resulting from the dynamic interaction between genome, epigenome and environment. The regulation of several processes at multilevel of complexity from gene expression to cellular cycle to tissue repair and system-wide network activation has different time delays (time scale) according to the system (space scale). Thus, spatio-temporal systems-wide shifts in large scale network functioning are essential to reallocate processing resources fundamental for adaptation. The understanding of how to measure and possibly control space and time scaled adaptive and compensatory responses occurring during complex polygenic diseases with non-linear pathophysiology, as AD, will represent a crucial step for achieving the capability to effectively modify disease. Biomarkers will guide in exploring how the space and time dimensions are mechanistic involved in complex disease as AD. Functional Stage – Adaptation Stage – Multilevel Stress Response: from metabolic reconfiguration to functional switch in cellular/tissue/systems network activity aimed to copy with different stressors/pathophysiological processes. Functional-Structural Stage – Compensation Stage – Multilevel Compensatory Mechanism: structural and functional dynamically balancing one another in order to copy with different pathophysiological processes. Early Systems Failure Stage – Decompensation Stage – Multilevel Breakdown/Lack of Reverse in Compensatory Mechanisms: initial and progressive loss of physiological interactions and pathophysiological compensations across multilevel systems network. Late Systems Failure Stage – Decompensation Stage – Multilevel Breakdown/Lack of Reverse in Compensatory Mechanisms: progressed loss of physiological and pathophysiological simultaneous interactions between multilevel systems network From the first stage to the third stage there is a decreasing chance to restore homeostatic condition (as highlighted by the colors from green to red). No option to recover homeostasis at the last stage. Abbreviations: AD, Alzheimer’s disease.

Fig. 2.

Agents in clinical trials for the treatment of Alzheimer’s disease in 2017 (from clinicaltrials.gov accessed on 1/5/2017). Abbreviations: ATP, adenosine triphosphate; BNC, bisnorcymserine; GM-CSF, granulocyte-macrophage colony-stimulating factor; OAA, oxaloacetate; IVIG, intravenous immunoglobulin; SLAT, simvastatin 1L-arginine 1 tetrahydrobiopterin. From Cummings J et al. “Alzheimer’s disease drug development pipeline: 2017.” Alzheimers Dement (N Y). 2017 May 24;3(3):367-384. doi: 10.1016/j.trci.2017.05.002. Copyright © 2017 Elsevier. Reprinted with permission from Elsevier.

Fig. 3.

Drug discovery programs workflow. Many drug discovery programs progress through a logical sequence where the findings from one type of experiment inform the next step. Significant confidence is generated in programs where the data generated within each phase are concordant with subsequent phases. Programs that lack this translational quality are subject to increasing risk of failure. Abbreviations: MAD, Multiple Ascending Dose; NME, New Molecular Entity; SAD, Single Ascending Dose. Adapted from Karran E, Hardy J. “A critique of the drug discovery and phase 3 clinical programs targeting the amyloid hypothesis for Alzheimer disease.” Ann Neurol. 2014 Aug;76(2):185-205. doi: 10.1002/ana.24188. Copyright © 2014 Wiley. Reprinted with permission from Wiley.

Fig. 4.

The four categories of biomarker: target, mechanism, pathophysiological, and diagnostic. Biomarkers can be categorized into four groups on the basis of their contribution to business, regulatory and clinical decision-making. Clinical decision-making can be further divided into clinical research and patient care diagnostic subcategories. The objective is to use biomarkers as early as possible in the drug development process. – The initial step is to confirm that a test compound hits the target and to quantify the extent to which it does so. Next is to test three concepts in logical sequence. – First, that hitting this target alters the pathophysiological mechanism. – Second, that altering this mechanism affects the pathophysiology. – Third, that affecting pathophysiology predictably improves the clinical status of the patients. – Biomarkers qualified to confirm the presence of the target and or extent to which the drug candidate hits the target may be validated later as diagnostic tests for early detection or diagnosis of Alzheimer’s disease (when that target is expressed differentially between healthy and diseased states). – Biomarkers qualified for confirming and quantifying mechanistic effects may be validated later as diagnostic tests to inform choice of therapeutic regimen, either in choice of drug or initial dosing regimen. – Biomarkers qualified for longitudinal quantification of patient response in terms of clinically relevant pathophysiology, may be validated later as diagnostic tests for monitoring and individualization of a therapeutic regimen. – Biomarkers qualified for either monitoring or individualization of therapy on clinically relevant pathophysiology may also serve as surrogate end points to support regulatory decision-making. In addition, they can be used to ensure appropriateness of use, and as quantifiers of clinical outcomes to support reimbursement decisions. From Hampel H et al. “Biomarkers for Alzheimer’s disease: academic, industry and regulatory perspectives.” Nat Rev Drug Discov. 2010 Jul;9(7):560-574. doi: 10.1038/nrd3115. Copyright © 2010 Springer Nature. Reprinted with permission from Springer Nature.