Solanezumab in‐depth outcomes

Lessons learned from the failure of solanezumab as a prospective treatment strategy for Alzheimer's disease

INTRODUCTION

In the last decade, the efforts conducted for discovering Alzheimer's Disease (AD) treatments targeting the best-known pathogenic factors [amyloid-β (Aβ), tau protein, and neuroinflammation] were mostly unsuccessful. Given that a systemic failure of Aβ clearance was supposed to primarily contribute to AD development and progression, disease-modifying therapies with anti-Aβ monoclonal antibodies (e.g. solanezumab, bapineuzumab, gantenerumab, aducanumab, lecanemab and donanemab) are ongoing in randomized clinical trials (RCTs) with contrasting results.

AREAS COVERED

The present Drug Discovery Case History analyzes the failures of RCTs of solanezumab on AD. Furthermore, the authors review the pharmacokinetics, pharmacodynamics, and tolerability effect of solanezumab from preclinical studies with its analogous m266 in mice. Finally, they describe the RCTs with cognitive, cerebrospinal fluid and neuroimaging findings in mild-to-moderate AD (EXPEDITION studies) and in secondary prevention studies (A4 and DIAN-TU).

EXPERT OPINION

Solanezumab was one of the first anti-Aβ monoclonal antibodies to be tested in preclinical and clinical AD showing to reduce brain Aβ level by acting on soluble monomeric form of Aβ peptide without significant results on deposits. Unfortunately, this compound showed to accelerate cognitive decline in both asymptomatic and symptomatic trial participants, and this failure of solanezumab further questioned the Aβ cascade hypothesis of AD.

Application of Bayesian methods to accelerate rare disease drug development: scopes and hurdles

Background

Design and analysis of clinical trials for rare and ultra-rare disease pose unique challenges to the practitioners. Meeting conventional power requirements is infeasible for diseases where sample sizes are inherently very small. Moreover, rare disease populations are generally heterogeneous and widely dispersed, which complicates study enrollment and design. Leveraging all available information in rare and ultra-rare disease trials can improve both drug development and informed decision-making processes.

Main text

Bayesian statistics provides a formal framework for combining all relevant information at all stages of the clinical trial, including trial design, execution, and analysis. This manuscript provides an overview of different Bayesian methods applicable to clinical trials in rare disease. We present real or hypothetical case studies that address the key needs of rare disease drug development highlighting several specific Bayesian examples of clinical trials. Advantages and hurdles of these approaches are discussed in detail. In addition, we emphasize the practical and regulatory aspects in the context of real-life applications.

Conclusion

The use of innovative trial designs such as master protocols and complex adaptive designs in conjunction with a Bayesian approach may help to reduce sample size, select the correct treatment and population, and accurately and reliably assess the treatment effect in the rare disease setting.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-022-02342-5.

Impact of Anti-amyloid-β Monoclonal Antibodies on the Pathology and Clinical Profile of Alzheimer's Disease: A Focus on Aducanumab and Lecanemab

Alzheimer's disease (AD) is the most prevalent form of age-related dementia in the world, and its main pathological features consist of amyloid-β (Aβ) plaque deposits and neurofibrillary tangles formed by hyperphosphorylated tau protein. So far, only a few AD treatments approved have been applied in the clinic, but the effects of these drugs are limited only for partial symptomatic relief to patients with AD and are unable to alter AD progression. Later, all efforts for AD treatments with targeting the pathogenic factors were unsuccessful over the past decades, which suggested that the pathogenesis of AD is complex. Recently, disease-modifying therapies (DMTs) that can change the underlying pathophysiology of AD, with anti-Aβ monoclonal antibodies (mabs) (e.g., aducanumab, bapineuzumab, gantenerumab, solanezumab, and lecanemab) have been developed successively and conducted in clinical trials based on the theory that a systemic failure of cell-mediated Aβ clearance contributes to AD occurrence and progression. In the review, we summarized recent studies on the therapeutic effects and clinical trial results of these mabs in patients with AD. Specifically, we focused on the discussion of the impact of aducanumab and lecanemab on AD pathology and clinical profiles. The review provides a possible evidence for applying immunotherapy with anti-Aβ mabs in AD and analyzes lessons learned from these clinical trials in order to further study the therapeutic and adverse effects of these anti-Aβ mabs on AD.

Fluid Biomarkers in Alzheimer’s Disease and Other Neurodegenerative Disorders: Toward Integrative Diagnostic Frameworks and Tailored Treatments

The diagnosis of neurodegenerative diseases (NDDs) represents an increasing social burden, with the unsolved issue of disease-modifying therapies (DMTs). The failure of clinical trials treating Alzheimer′s Disease (AD) so far highlighted the need for a different approach in drug design and patient selection. Identifying subjects in the prodromal or early symptomatic phase is critical to slow down neurodegeneration, but the implementation of screening programs with this aim will have an ethical and social aftermath. Novel minimally invasive candidate biomarkers (derived from blood, saliva, olfactory brush) or classical cerebrospinal fluid (CSF) biomarkers have been developed in research settings to stratify patients with NDDs. Misfolded protein accumulation, neuroinflammation, and synaptic loss are the pathophysiological hallmarks detected by these biomarkers to refine diagnosis, prognosis, and target engagement of drugs in clinical trials. We reviewed fluid biomarkers of NDDs, considering their potential role as screening, diagnostic, or prognostic tool, and their present-day use in clinical trials (phase II and III). A special focus will be dedicated to novel techniques for the detection of misfolded proteins. Eventually, an applicative diagnostic algorithm will be proposed to translate the research data in clinical practice and select prodromal or early patients to be enrolled in the appropriate DMTs trials for NDDs.