Stage: Early stage preclinical discovery
Area: Drug discovery
Patent: Not filed yet
Alzheimer’s disease (AD) affects over 35 million people worldwide and causes formidable economic challenges. Since 2003, over 250 drug candidates, predominantly targeting two pathological proteins, amyloid-β (Aβ) and pathological Tau, have been tested in clinical trials for AD, but most of them have failed. There is a need to pursue new mechanistic studies in order to better understand the underlying causes of AD, and to discover new drug targets.
Mitochondria operate as cellular “powerhouses” and play a pivotal role in neuroplasticity and memory, thus dysfunction in mitochondria can impair neuronal function and trigger neurodegeneration. Mitochondria are constantly exposed to stress and damage; to cope, dysfunctional mitochondria must be specifically and efficiently eliminated via a cellular self-clearance system, “mitophagy”. Mitophagy is impaired in the elderly, leading to the accumulation of damaged mitochondria.
Evandro Fang’s lab was one of the first research teams to propose defective mitophagy as a key driver in AD initiation and progression and to demonstrate its causative role; they have demonstrated the effectiveness of mitophagy induction in inhibiting memory loss in multiple AD animal models. Large-scale omics and functional studies using post-mortem brain tissues and iPSCs from AD identified impaired mitochondrial function and impairment of mitochondria-related pathways as major changes in AD.
Recently, Fang lab established an artificial intelligence (Fang-AI) coupled with a wet lab validation platform, which enabled the successful identification of two lead mitophagy-inducing compounds (EFF-AA and EFF-BA) as drug candidates for AD. Machine learning followed by medicinal chemistry will be used to increase ‘solubility’, ‘activity’, ‘bioavailability’ and to reduce ‘toxicity’ of these compounds. Wet lab techniques will be used to validate bioactivity and anti-AD function of the new compounds.
Fang lab also aims to use the Fang-AI + wet lab validation platform to screen new mitophagy inducers from the Finnish Institute of Molecular Medicine (FIMM), consisting of 140,000 compounds.
Pre-Clinical Studies 1a: Toxicity assays for FIMM hits
Required Funding: $26,815
Duration: 3 Months
Pre-Clinical Studies 2a: Toxicity and efficacy of EFF-AA/EFF-BA
Required Funding: $81,565
Duration: 3 Months
Pre-Clinical Studies 1b: Mitophagy assays of FIMM hits
Required Funding: $63,500
Duration: 7 Months
Pre-Clinical Studies 2b: Chemical synthesis of EFF-AA/EFF-BA analogues
Required Funding: $63,500
Duration: 6 Months
Evandro Fang is a pioneering world expert, with years of experience and strong track record in mitophagy, neurodegeneration and ageing research.
This project will help to improve our basic understanding around the link between mitophagy and Alzheimer's disease. It has a straightforward, well-defined and comprehensive experimental plan, using a platform which has already identified 2 lead compounds and has the potential, with medicinal chemistry support, to discover entirely novel chemical entities. Preliminary data shows the lead compounds can activate mitophagy, prevent memory loss and confer healthspan/lifespan improvements in C. elegans. The effect size was quite small and whether these results will translate to higher organisms remains to be known, however the funding will allow for mouse studies to test this.
Despite Alzheimer’s disease receiving substantial global funding, successes in early stage drug discovery have not translated to human trials. However, impairment of mitophagy is likely a shared cause of different neurodegenerative diseases (such as Parkinson’s disease, Huntington’s disease and Amyotrophic Lateral Sclerosis) and thus mitophagy activation via pharmaceutical approaches could be a druggable target for a wide range of neurodegenerative diseases and even ageing per se.
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The vote has passed, the decision is made: Evandro Fang Lab will be the third research organisation to fund their longevity research via an IP-NFT.
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