Translational Scoring of Candidate Treatments for Alzheimer's Disease: A Systematic Approach

Translatability scoring in prospective and retrospective COVID drug development cases

BACKGROUND

The ongoing pandemic of severe acute respiratory syndrome coronavirus 2 has led to an enormous surge of clinical research. So far, the speed and success rate of related drug development projects, especially of vaccines, is unprecedented. For the first time, this situation allowed for the opportunistic evaluation of a translatability score, originally proposed in 2009, in a prospective manner.

METHODS

Several vaccines and treatments under development in clinical phase III trials were selected for translational scoring with the translatability score. Six prospective and six retrospective case studies were performed. The scores had to be determined for a fictive date before any results of the phase III trial were reported in any media. Spearman correlation analysis and a Kruskal Wallis test were performed for statistical evaluation.

RESULTS

A significant correlation between the translatability scores and the clinical outcomes in translation was found, as judged on the basis of positive/intermediate/negative endpoint studies or market approval. The Spearman correlation analysis of all cases (r = 0.91, p < 0.001), the prospective cases alone (r = 0.93, p = 0.008), and the retrospective cases alone (r = 0.93, p = 0.008) showed a strong correlation between the score and outcome; R2 demonstrated a score-derived determination of outcomes by 86%.

CONCLUSIONS

The score detects strengths and weaknesses of a given project, resulting in the opportunity of selective amelioration of a project, as well as prospective portfolio risk balancing. Its substantial predictive value that has been demonstrated here for the first time could be of particular interest for biomedical industry (pharmaceutical and device manufacturers), funding agencies, venture capitalists, and researchers in the area. Future evaluations will have to address the generalizability of results obtained in an exceptional pandemic situation, and the potential adaptations of weighing factors/items to particular therapeutic areas.

Improving Translational Paradigms in Drug Discovery and Development

Despite improved knowledge regarding disease causality, new drug targets, and enabling technologies, the attrition rate for compounds entering clinical trials has remained consistently high for several decades, with an average 90% failure rate. These failures are manifested in an inability to reproduce efficacy findings from animal models in humans and/or the occurrence of unexpected safety issues, and reflect failures in T1 translation. Similarly, an inability to sequentially demonstrate compound efficacy and safety in Phase IIa, IIb, and III clinical trials represents failures in T2 translation. Accordingly, T1 and T2 translation are colloquially termed 'valleys of death'. Since T2 translation dealt almost exclusively with clinical trials, T3 and T4 translational steps were added, with the former focused on facilitating interactions between laboratory- and population-based research and the latter on 'real world' health outcomes. Factors that potentially lead to T1/T2 compound attrition include: the absence of biomarkers to allow compound effects to be consistently tracked through development; a lack of integration/'de-siloing' of the diverse discipline-based and technical skill sets involved in drug discovery; the industrialization of drug discovery, which via volume-based goals often results in quantity being prioritized over quality; inadequate project governance and strategic oversight; and flawed decision making based on unreliable/irreproducible or incomplete data. A variety of initiatives have addressed this problem, including the NIH National Center for Advancing Translational Sciences (NCATS), which has focused on bringing an unbiased academic perspective to translation, to potentially revitalize the process. This commentary provides an overview of the basic concepts involved in translation, along with suggested changes in the conduct of biomedical research to avoid valleys of death, including the use of Translational Scoring as a tool to avoid translational attrition and the impact of the FDA Accelerated Approval Pathway in lowering the hurdle for drug approval. © 2021 Wiley Periodicals LLC.

Sustainable Drug Discovery of Multi-Target-Directed Ligands for Alzheimer's Disease

The multifactorial nature of Alzheimer's disease (AD) is a reason for the lack of effective drugs as well as a basis for the development of "multi-target-directed ligands" (MTDLs). As cases increase in developing countries, there is a need of new drugs that are not only effective but also accessible. With this motivation, we report the first sustainable MTDLs, derived from cashew nutshell liquid (CNSL), an inexpensive food waste with anti-inflammatory properties. We applied a framework combination of functionalized CNSL components and well-established acetylcholinesterase (AChE)/butyrylcholinesterase (BChE) tacrine templates. MTDLs were selected based on hepatic, neuronal, and microglial cell toxicity. Enzymatic studies disclosed potent and selective AChE/BChE inhibitors (5, 6, and 12), with subnanomolar activities. The X-ray crystal structure of 5 complexed with BChE allowed rationalizing the observed activity (0.0352 nM). Investigation in BV-2 microglial cells revealed antineuroinflammatory and neuroprotective activities for 5 and 6 (already at 0.01 μM), confirming the design rationale.

Quantifying misfolded protein oligomers as drug targets and biomarkers in Alzheimer and Parkinson diseases

Protein misfolding and aggregation are characteristic of a wide range of neurodegenerative disorders, including Alzheimer and Parkinson diseases. A hallmark of these diseases is the aggregation of otherwise soluble and functional proteins into amyloid aggregates. Although for many decades such amyloid deposits have been thought to be responsible for disease progression, it is now increasingly recognized that the misfolded protein oligomers formed during aggregation are, instead, the main agents causing pathological processes. These oligomers are transient and heterogeneous, which makes it difficult to detect and quantify them, generating confusion about their exact role in disease. The lack of suitable methods to address these challenges has hampered efforts to investigate the molecular mechanisms of oligomer toxicity and to develop oligomer-based diagnostic and therapeutic tools to combat protein misfolding diseases. In this Review, we describe methods to quantify misfolded protein oligomers, with particular emphasis on diagnostic applications as disease biomarkers and on therapeutic applications as target biomarkers. The development of these methods is ongoing, and we discuss the challenges that remain to be addressed to establish measurement tools capable of overcoming existing limitations and to meet present needs.