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Enregistrement W2014141048 · doi:10.1111/j.1752-8062.2009.00121.x

Translational Medicine Lessons from Flurizan's Failure in Alzheimer's Disease (AD) Trial: Implication for Future Drug Discovery and Development for AD

2009· letter· en· W2014141048 sur OpenAlexaffabout
Hong Wan, Jan Jacobsen, J. Lynn Rutkowski, Giora Feuerstein

Notice bibliographique

RevueClinical and Translational Science · 2009
Typeletter
Langueen
DomaineMedicine
ThématiqueCholinesterase and Neurodegenerative Diseases
Établissements canadiensWomen's Health Research Institute
Organismes subventionnairesnon disponible
Mots-clésDrug developmentDrug discoveryMedicineTranslational medicineDiseaseAlzheimer's diseaseClinical trialDrug trialTranslational researchDrugMEDLINEIntensive care medicinePharmacologyBioinformaticsInternal medicinePathologyBiology

Résumé

récupéré en direct d'OpenAlex

Alzheimer's disease (AD) is a progressive and fatal brain disease. According to the Alzheimer's Association, as many as 5.2 million people in the United States are living with AD and 10 million "baby boomers" are expected to develop the disease in their lifetime. AD is the sixth leading cause of death, and the direct and indirect costs of dementia amount to more than $148 billion each year (2008 Alzheimer's Disease Facts and Figures, Alzheimer's Association). Currently, there is no cure. To date, the U.S. Food and Drug Administration (FDA) has approved three cholinesterase inhibitors (donepezil, galantamine, and rivastigmine) and an N-methylD-aspartate (NMDA) receptor antagonist (memantine) that offer modest improvement in cognitive function in some individuals, but such treatments are often discontinued within 6 months because of inadequate efficacy and/or tolerability issues. Although treatments with the potential to modify the course of AD by affecting the underlying pathophysiology are rapidly evolving and several of them have entered advanced phases of human clinical trials, none has shown convincing clinical efficacy in a large pivotal trial. The recent announcement from Myriad Pharmaceuticals, Inc. (Salt Lake City, UT, USA) on June 30, 2008, that Flurizan (Tarenflurbil, MPC-7869) failed to demonstrate statistically significant efficacy in either of the co-primary endpoints in the phase III trial represents another high-profile failure in the pursuit of disease-modifying therapeutics for AD. It is believed that on the basis of this result, Myriad and partner Lundbeck decided to discontinue the development of Flurizan, including the ongoing international phase III trial, which was due to complete in October. This phase III trial followed 1,684 AD patients over an 18-month treatment period for a change in the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) score (a cognitive measure) and Alzheimer's Disease Cooperative Study-Activities of Daily Living Inventory (ACDS-ADL) score (a functional measure) relative to placebo as the efficacy endpoints. As this trial was powered to achieve statistical significance in a nonclinically significant change in the ADAS-Cog score, the failure confirms that Flurizan has no clinical effect beyond the standard of care (and placebo). Prior to Myriad's announcement, the most recent failure was tramiprosate (Alzhemed), developed by Neurochem (Laval, Quebec, Canada), which was supposed to act by binding soluble amyloid Aβ peptides. It was terminated in August 2007 again after a large phase III trial that included over 1,800 AD patients treated for 18 months showed no statistical significant difference b etween treatment and placebo groups in both primary efficacy endpoints of the ADAS-Cog and Disability Assessment for Dimentia (DAD). These two large clinical trials with compounds reputed for their antiamyloid mechanism of action were disappointing news to the AD community, especially for the patients and caregivers who are desperately waiting for a disease-modifying therapy that would offer some hope for disease slowing beyond the short-term symptomatic relief. In this commentary, we offer a translational medicine perspective on the choices made to select and develop these compounds for AD treatment. A close examination of the Flurizan case presented below could provide important insights and "lessons learned," especially regarding the issues of evidence-based clinical decision making during the drug development program. This case study highlights the importance of appropriate and rigorous use of biomarkers in AD drug development. We take the position, based on our analysis and available literature, that these compounds are inadequate tools to fully investigate the role of amyloid pathways in AD. We further recommend a biomarker-driven roadmap that could be used at different stages to reduce the risk of development of innovative compounds based on a new mechanism of action in the AD program. It is widely recognized that today's environment for a new pharmaceutical development is increasingly challenging, particularly since many new targets are not as well validated. In response to this challenge, the pharmaceutical industry is increasingly using biomarkers as rationales and potentially cost-effective means of predicting potential success of novel therapeutics in drug discovery and development. Biomarkers can be employed to (1) understand the relevance of the drug target to human disease, (2) demonstrate drug-target interaction, (3) measure the consequences of target modulation (pharmacodynamic [PD] effects), (4) detect modulation of pathophysiological processes, and (5) optimize patient selection to detect medical benefits. The use of such evidence-based biomarkers can increase confidence during early development, improve the ability to prioritize clinical drug candidates across a broad portfolio, and yield better and more cost-effective advancement decisions.1–4 For convenience and to achieve a uniform lexicon, we group biomarkers into the following categories based on their intended use (Box): Target validation biomarkers provide scientific evidence on the role of the target in human diseases and its potential to be exploited in drug discovery and development campaigns. Target-compound interaction biomarkers provide evidence on the physical-chemical interaction of the drug with its intended target. PD biomarkers report on the biological consequences of drug action in the exposed organism or patient. These include biomarkers of efficacy and safety. Disease biomarkers report on disease severity, progression, and regression and could provide guidance as to whether a drug candidate has the potential to fundamentally alter or modify the disease process. Patient selection biomarkers provide information on those patients most likely to respond (or not respond) to the treatment. Such biomarkers provide an opportunity to stratify patients for risk of disease progression and potentially enable shorter trials with higher event rates and earlier outcome assessments. Box. Biomarkers: utilitarian classification. In the following sections, we examine the case of Flurizan with regard to these five criteria and discuss the potential value of biomarker in decision making. While the precise etiology and pathogenesis of AD are still unclear, the most convincing hypothesis postulates that the accumulation of Aβ peptide triggers the formation of amyloid plaques and neurofibrillary tangles with subsequent inflammation and brain atrophy5 (Figure 1). Rare, inherited forms of AD offer strong support for the role of Aβ in the pathogenesis of the disease. Mutations in either the precursor protein or the processing enzymes lead to Aβ accumulation and amyloid plaque and tangle formation.6,7 Despite the fact that the etiology of the disease in sporadic AD remains elusive, Aβ peptides and amyloid plaques also accumulate in these patients. Amyloid cascade hypothesis. Tremendous progress has been made in understanding the biological role of Aβ, including its production, clearance, and physiological impact on neuronal function and pathology. Multiple agents targeting this pathway, which are expected to further reduce Aβ production or clear amyloid plaques, are in various stages of clinical testing. The results of such ongoing clinical trials are expected to provide proof of concept (POC) for an Aβ-lowering mechanism as being sufficient to modify the disease course. Although clinical evidence of such amyloid-targeted therapeutics has not been demonstrated in a pivotal study to date, promising data have been recently emerging.8,9 Gaps in our understanding of Aβ as a drug target remain, and the tools currently available to study Aβ in its various forms are limiting. In vitro and animal studies indicate that soluble forms of Aβ aggregates rather than amyloid deposits are the neurotoxic species and these aggregates are difficult to measure, particularly in a clinical setting. Any measurement of soluble Aβ directly in the human brain is problematic, and although measurements in the cerebrospinal fluid (CSF) or plasma are feasible, their relationship to brain levels is confounded by the differences in the dynamic equilibrium between compartments and the rather ubiquitous expression of the amyloid precursor protein (APP) precursor and processing enzymes. Positron emission tomography (PET) is a promising method that has been used for the in vivo detection of Aβ plaque burden. However, longitudinal studies indicate that amyloid deposition precedes cognitive impairment by decades and correlates with memory loss only in the very mildest stages of AD or in normal elderly.10 The issues with validating antibody (Ab) as a drug target in AD patients and the inherent limitations of current biomarkers are not unique to Flurizan and relate to all Aβ-lowering agents. Flurizan is the pure R-enantiomer form of flurbiprofen—a nonsteroidal anti-inflammatory drug (NSAID) with 25 years of clinical experience behind it. Unlike classical NSAIDs, however, Flurizan is not an inhibitor of cyclooxygenase enzymes (COX-1 and COX-2).11 Based on in vitro cell-based assay results, Flurizan is proposed to be a selective Aβ42-lowering agent.12 The data generated to date suggest that Flurizan modulates, rather than inhibits, γ-secretase to preferentially reduce the generation of the longer toxic Aβ42peptide and favor the production of shorter, less toxic forms. As a selective Aβ42-lowering agent, Flurizan does this without affecting the processing of other essential γ-secretase substrates such as Notch, which provides an advantage over direct γ-secretase inhibitors. The exact nature of Flurizan's interaction with γ-secretase complex is not fully understood. One hypothesis is that NSAIDs, including Flurizan, specifically lower Aβ42 through an allosteric binding mechanism that alters the conformation of the presenilin complex.13,14 More recent data indicate that Flurizan does not interact with the enzyme subunits but directly binds to the APP substrate.12 The authors suggest that drug binding shifts the position of the APP precursor in the plane of the membrane to alter the γ-secretase cleavage site. Additionally, Flurizan might inhibit Aβ aggregation since the minimal binding site is the same domain that is involved in fibrilization. In cell-based systems expressing human APP containing the "Swedish" mutation, Flurizan demonstrated selective Aβ42-lowering activity. A 50% reduction in Aβ42was observed in human H4 neuroglioma cells at 100 μM using the ELISA method15 and a 40% reduction was observed at 250 μM in human embryonic kidney cells.16 Potency was not improved in a broken-cell model using membrane preparations derived from Chinese Hamster Ovary (CHO) cells to directly measure the inhibition of -γ-secretase in vivo11 and in vitro. Inhibitory concentration (IC) values for Aβ42-lowering activity have not been reported. In comparison, several γ-secretase inhibitors that entered clinical development, including GSI-95317 and LY-450139,18 have IC50 in the low nanomolar range. Taken together, the ambiguity and controversy regarding the direct target that Flurizan interacts with and the weak in vitro potency in reducing Aβ42 production represent significant knowledge gaps, which increase the risk assumed in further drug development. Assuming that the amyloid cascade is correct and the reduction of Aβ can slow or halt disease progression, it is still unclear how much Aβ42 inhibition is required for clinical efficacy Data from PDAPP transgenic animals that were backcrossed into β-site of APP cleaving enzyme (BACE) heterozygous knockout mice with a partial reduction of BACE leads to about 12% reduction of soluble total Aβ in brain tissues.19,20 However, this level of reduction in soluble Aβ results in a much more substantial reduction in amyloid plaque load as the animal ages. Similarly, it is possible that in AD patients, a chronic treatment strategy with moderate amyloid reduction might lead to a more substantial impact on amyloid plaque deposition and on the rate of disease progression. One line of evidence comes from the fact that Down's syndrome patients, who process 50% more amyloid precursor protein in brain tissue because of an additional copy of the APP gene on chromosome 21, often develop AD-like pathology in the third and fourth decades, some 20–30 years earlier than the onset of the sporadic form of the disease. Conversely, one might speculate that reducing Aβ levels for even less than 50% could lead to a substantial delay in disease onset and progression. When administered orally to transgenic Tg2576 mice, Flurizan lowered Aβ42 in the brain but lacked a dose-proportional response. A 3-day subchronic dosing regime at 10, 25, and 50 mg/kg/day produced 26% (p < 0.01), 60% (p < 0.001), and 34% (p < 0.001) reduction of brain Aβ42 levels, respectively. Plasma Aβ40 and Aβ42 levels were decreased by30–50% but lacked direct correlation with brain Aβ levels. The average drug levels for the brain (1.5, 2.6, and 2.5 μM) and plasma (83,117, and 78 μM) at 2 hours after dosing were reported for 10, 25, and 50 mg/kg/day, respectively.15 Thus, corresponding brain-to-plasma ratios were poor (approximately 0.02), perhaps explaining the unpredictable pharmacokinetics (PK)/PD relationship. At best, an exposure multiple of approximately 0.2 was obtained in the brain, in which the concentrations reached approximately 50-fold lower drug levels than the estimated in vitro IC50 value for Aβ42-lowering activity.21 Similar studies performed independently in Tg2576 mice unexpectedly failed to detect significant reductions of Aβ42 levels in the brain.22 Thus, the reported in vivo PK/PD data did not provide robust evidence for Flurizan's activity as a selective Aβ42-lowering agent. Although Flurizan was well tolerated in humans, phase I single-dose PK data demonstrate that the exposure was not dose-proportional and plasma drug levels ranged from 131 to 483 μM.15,23 When administered orally twice a day in healthy elderly volunteers, Flurizan demonstrated a half-life of 6–8 hours and Cmax of 158 and 185 μM were achieved at Tmax of 1–2 hours (based on 400 and 800 mg b.i.d.). Th e CSF-to-plasma ratio of Flurizan was approximately 0.5%.24 These two doses were later tested in the larger phase II and phase III trials. Based on the preclinical data described above and assuming a similar brainto-plasma ratio (approximately 0.2), brain drug levels of 2.6–9.7 μM would achieve exposure multiples of only 0.03–0.1. Although it has been reported that Flurizan displays minimal enantiomeric bioinversion in humans,23 it is possible that any bioinversion could have further added complexity in understanding the in vivo PK/PD relationship. As a small molecule candidate for a central nervous system (CNS) disease, Flurizan does not have an optimal brain penetration profile and it is possible that drug levels may not have achieved concentrations necessary for efficacy. More significant early warning signs were raised by a clinical study with healthy elderly subjects: treatment with Flurizan for 21 days did not results in significant Aβ42 reduction measured by ELISA in either the plasma or the CSF compartment.24 When comparing baseline and posttreatment levels in the four treatment groups of placebo, 200 mg b.i.d., 400 mg b.i.d., and 800 mg b.i.d., reductions in either CSF Aβ42 or plasma Aβ42 were not detected and there was no evidence of selective modulation of Aβ species, as the proposed mechanism would suggest, even though the same surface-enhanced laser desorption/ionization time-of-fiight mass spectrometry (SEDLI-TOF) method did show a shift in Aβ37/Aβtotal and Aβ42/Aβtotalratios in conditioned media from cells treated with Flurizan in vitro.24 One caveat of the study results, as the authors argued, is that sampling time in the plasma and CSF may not have been optimal and drug activity might have been missed. In this study, only one time point was used for both predose baseline and on day 21 of the study for both plasma and CSF biomarker measurement. Since it has been reported that Aβ levels, especially in the CSF, can vary quite a bit depending on the time of collection and within hours in the same individual,25 it would be a more rigorous study design to assess plasma and CSF Aβ levels at multiple time points. At this point in clinical development, there is no clear evidence demonstrating that Flurizan engaged its target in human subjects. Several sensitive immunoassays have been developed to allow measurement of both plasma and CSF Aβ peptides and continuous sampling of the plasma and CSF from healthy subjects and AD patients is feasible.26 Moreover, gamma secretase inhibitors (GSIs) have demonstrated a dose-dependent Aβ lowering in the plasma compartment in both healthy subjects and AD patients.27,28 Reduction of Aβ42 by a variety of means is a widely pursued therapeutic strategy for AD and numerous compounds are under development. In such programs, biomarker evidence that a drug engages its target and can produce a biological response at nontoxic dose range should be considered as an essential criterion for advancing a drug candidate before substantial resources are committed and a larger number of AD patients are exposed for a longer time. Given the variability of clinical efficacy measures, most phase II trials are not powered to detect significant changes in the ADAS-Cog score or ADL. It is therefore even more important at this phase of AD drug development to incorporate biomarkers to gather supportive evidence of drug activity in the patient population. The most well-characterized biomarkers that track AD disease progression are imaging measures for brain atrophy (eg, structural magnetic resonance imaging [MRI]) or cerebral glucose metabolism (eg, 2-fiuoro-2-deoxy-D-glucose [FDG-PET]). It is true that although these imaging biomarkers have been shown by multiple groups to correlate with the disease and possibly disease progression,29–31 precisely how a therapeutic intervention would affect imaging measures is not fully understood. Nevertheless, with the extensive resources required to conduct large, long-term AD trials to test clinical efficacy and the high risk of failure of disease modifiers, it is prudent to buy down the risk of clinical development by including such imaging biomarkers as early as possible. The Flurizan phase II POC trial was a double-blind and placebo-controlled study over a 12-month period that did not include any imaging or biochemical biomarker measurements.32 Flurizan 400 mg b.i.d. or 800 mg b.i.d. dose did not reach statistical significance in reducing cognitive decline in AD, though for patients with milder symptoms, statistical significance was almost reached in the two functional scales (p= 0.059). There were other interesting signals that subsequently influenced the phase III study design. In subgroup analyses, the delayed deterioration in patients with mild disease receiving high doses of the drug and higher drug concentrations were associated with better outcomes.32 However, such subgroup analyses are known to be unreliable because of the small numbers and the possibility that patients in a particular subgroup had less aggressive disease. The fact that Flurizan showed dose-related effects on ADL and functional measures but not on cognitive measures was puzzling and should raise concerns, as functional measures are often more variable than the ADAS-Cog score in AD clinical trials. In addition, in the phase II trials patients with moderate disease had numerically worse scores for Flurizan and placebo patients who then started on the drug did not show benefit. These facts could be interpreted as additional negative signals against Flurizan's efficacy. As presented at the International Conference on Alzheimer's Disease (ICAD),33 the phase III study of Flurizan (tarenflurbil), known as Act-Earli-AD, was a well-powered, well-designed, and well-conducted trial in subjects with mild AD (mini-mental state examination [MMSE] 20–26). The 18-month study was designed to assess the potential effect of Flurizan on cognition, ADL, and global function but did not include any imaging or biochemical biomarker analysis. The treatment groups were well matched at baseline, placebo decline rates were as expected over the 18-month period, and Apolipoprotein E (ApoE) genotypes were representative of the typical AD population. No difference between placebo and treatment groups in clinical outcome measures left very little question about the Flurizan's of efficacy. It is recognized that sporadic AD is not a disease but likely a complex of pathology and from the AD patient groups with a likely difference in the rate of decline and response to candidate treatment. While numerous risk have been in AD patients, only the of the has been and the analysis of the is increasingly being into AD drug trials. protein has been proposed to be involved in and metabolism of amyloid peptides and have risk to develop AD at an earlier A analysis of did not a effect of Flurizan with placebo in the phase III study and further the of clinical AD patients have also been in clinical trials by disease severity, which may the drug response. For an Aβ-lowering it has been that more patients may show a clinical benefit. or patient groups have been based on cognitive rather than or criteria or the rate of of a response to Flurizan in the subgroup from the analysis of the phase II data to Myriad's decision to modify its phase III study design and on mild AD patients. In the of a whether this was a better strategy remains We a rigorous to AD treatments in of the and high risk involved in the clinical of candidate A robust biomarker data is to the risk of and phase II and phase III trials. We that for agents with proposed Aβ-lowering a analysis be in and to the PK/PD relationship in compartments such as the CSF, and brain (Figure The direct measurement of Aβ and rate in and of human CSF would offer a more direct of Aβ-lowering agents (Figure We also that in brain such as and cerebral glucose metabolism measured by be into POC As the and more patient selection using amyloid imaging might to select the most appropriate patients with amyloid pathology for POC studies in which both and amyloid species as well as amyloid deposition in the brain can be for therapeutic activity. Such POC studies and a shorter treatment a on cognitive and functional endpoints is not drug activity on such and biomarkers would increase the confidence in the clinical development program. Conversely, the of convincing biomarker results should a risk in further clinical testing. PK/PD analysis can be performed in multiple compartments across and rate of peptide can be measured in human CSF from of an with an in and a in the was at a rate of for or hours after an of 2 Plasma are through the other line and CSF through the in the CSF and from an during a in the CSF and plasma a level within an There was an in levels after the of into the was at The average CSF over hours from The were and the for each time point is shown for or sampling from to or There is no of the in the This is followed by an increase in which the levels of (approximately before over the hours of the In the Flurizan phase III failure should not have been A examination of the evidence to the study weak poor brain and a of target modulation in human subjects or AD patients. to AD patients were subsequently exposed to an treatment in the phase III study, resources in the process. The strategy with Flurizan did not include sufficient risk and multiple clinical decision based on biomarker data could have been

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,016
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,016
Score d'incertitude au seuil0,082

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0160,010
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0020,002
Science ouverte0,0010,001
Intégrité de la recherche0,0050,006
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,099
Tête enseignante GPT0,405
Écart entre enseignants0,305 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations31
Publié2009
Routes d'admission2
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