By Matthew Adams
Reviewed by Danielle Ellis, B.Sc.
Understanding neurodegenerative diseases
Current treatment landscape
Emerging therapeutic strategies
Role of technology and AI
Challenges in drug development
Ethical and regulatory considerations
Future directions
Conclusion
References
Further reading
Neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease significantly impact the health of many people worldwide. Due to this impact, researchers around the globe are collaborating to develop targeted treatments. This article will discuss the background of these disorders and advances in neuropharmacology to treat them.
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Understanding neurodegenerative diseases
Although the exact pathophysiology of Parkinson’s disease (PD) and Alzheimer’s disease (AD) are different, both are marked by an accumulation of toxic proteins within the brain.
In PD, this protein, Alpha-synuclein, may first appear in the olfactory bulb or vagus nerve, spreading to substantia nigra. The substantia nigra is a key area of the brain for motor function, with the death of neurons in this area leading to a decrease in dopamine and the appearance of the motor symptoms typically seen in PD. 1
In AD, the accumulated proteins are amyloid beta (Aβ) and tau. These proteins appear as extracellular plaques of Aβ and intracellular tangles of tau protein. Recent evidence suggests these pathologies act synergistically, leading to cell death within the brain. 2 This cell death, in turn, produces the associated cognitive decline of AD.
Due to the complex and still not fully understood interactions between the accumulated proteins in PD and AD pathology and the brain, creating treatments that effectively target disease drivers has proven difficult.
The blood-brain barrier is considered a large contributor to the complexity of treating neurodegenerative disorders. Under normal conditions, the BBB is near-impermeable to most large molecules, such as drug molecules. 3 Therefore, drugs given intravenously or orally may not reach the brain, preventing efficacious treatment.
Current treatment landscape
Currently, the gold standard treatment for PD is Levodopa. Levodopa is a precursor molecule for dopamine, and the taking of Levodopa leads to increased dopamine levels within the brain. This rescues some of the symptoms of PD. 4 However, the treatment efficacy of Levodopa decreases over time, meaning patients will see decreased benefits from treatment after long-term use. 5
Currently, pharmacological treatments for AD are symptomatic only in that they do not stop or slow the progression of the disease. Cholinesterase inhibitors make up the largest class of current treatments. Cholinesterase inhibitors slow the breakdown of acetylcholine through the inhibition of acetylcholinesterase. This increases the levels of acetylcholine within the synaptic cleft. 6
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As mentioned, cholinesterase inhibitors only mitigate the decrease in cognitive function associated with AD and do not slow the pathophysiological drivers of the disease.
Overall, as these treatments do little to stop the pathophysiological changes in AD and PD, individuals still suffer from these diseases. This necessitates further exploration of treatments that can ultimately effectively target the drivers of the pathophysiological changes.
Emerging therapeutic strategies
A recent advance in treating AD is the development of monoclonal antibodies (MAB). The two recently approved MABs act through the targeting and removal of Aβ plaques, lowering the amyloid burden within the brain. These MABs have shown a 30% reduction in a patient’s clinical decline. Extending the time spent in the mild phase of the disease potentially boosts the quality of life for patients and carers. 7
Genetic therapies also offer an exciting route for further treatment options in neurodegenerative diseases. Potential options include the viral delivery of APOE*ε2 (an allele of the APOE gene that is protective against late-onset AD) into the brain. 8
Viral introduction of the APOEε2 allele has been trialed in primates. A study by Rosenberg et al. showed widespread distribution of APOEε2 after the introduction into the cerebrospinal fluid of the cisterna. 9
Role of technology and AI
Artificial intelligence (AI) and machine learning are tools currently used to accelerate the development of novel drugs for neurodegenerative diseases. Drug-protein interactions may be predicted by these tools, providing an in-silico snapshot of potentially unforeseen side effects. This prediction may also allow for the repurposing of drugs if a potential therapeutic protein reaction is suggested. 10
Not only can machine learning and AI streamline the development of drugs, but they may also be used to discover potential new therapeutics. AI can predict the 3D structure of target proteins. Through this, drugs may be designed to better target or interact with the proteins of interest. 11
Challenges in drug development
Due to the complexity of the pathophysiology and etiology of neurodegenerative diseases, developing drugs for these disorders can be particularly challenging. 12Furthermore, due to the nature of neurodegenerative diseases, drug trials aiming to treat such diseases last long periods. Long-term trials often face problems such as low patient retention, which can impact the validity of the research. 13
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Clinical trials for AD have long faced high failure rates, with the cost of developing these therapies and running these trials coming to over $5.7 billion. 12 To overcome these highlighted issues, researchers have suggested a number of potential solutions.
These include altering the study design by combining phase 1 and 2 trials to evaluate toxicity and efficacy. Additionally, patient recruitment and enrolment can be altered to increase trial success. Increasing patients’ knowledge of potential trials they could be enrolled in or a voluntary database of AD patients could expand researchers’ potential patient pool, streamlining the process. 12
Ethical and regulatory considerations
As AD and PD may alter a patient’s mental state, obtaining informed consent can present numerous challenges and considerations. The patient being sound of mind is critical to informed consent. 14
This has stoked calls for further research into whether patients with AD have decision-making capacity. 15 Policies detailing how to approach cases where the patient has a neurodegenerative disease are not well-defined, leading to potential inconsistencies in application. 15
Additionally, there is a potential risk for patients, as they do not fully understand the risks of such trials, which posits a real risk. This calls for researchers to clearly define regulatory frameworks used for obtaining informed consent when researching neurodegenerative disorders.
Future directions
While genetic therapies do hold promise for certain aetiologies of AD and PD, such as in clearly inherited cases like pathogenic APP or LRRK variants, it is unlikely they would be adopted wholesale for all cases.
Much like in MABs for AD, degrading Alpha-synuclein may hold promise for widespread treatment of PD. This may come in an MAB or through drugs that inhibit the uptake of Alpha-synuclein into neurons. 16
While MABs exist for AD, this is not an endpoint for treatments. Some concerns have been raised about the benefit-to-risk ratio for MABs, leading to further alternatives for treatment being considered. 17
Such alternatives may come in the form of tau protein clearers, which reduce the tau burden within the brain. Such immunotherapies are already being trialed, with active immunotherapy for tau clearance reaching phase 2. 6
Research into treating AD and PD is still a developing field, with a wealth of opportunities to benefit patients’ lives worldwide. AD and PD have a large global burden, with an estimated 22% of people over the age of 50 having AD. The World Health Organization estimates over 8.5 million people have PD globally. 18
These diseases place a large burden on patients, their families, and healthcare systems. 19 This means that their treatment benefits not only patients but also caregivers.
Conclusion
While there are challenges in the development of disease-modifying therapies for AD and PD, researchers are making leaps in the move to effective treatments. Tools such as AI and machine learning are streamlining the discovery of novel drugs. Genetic therapies also offer promising treatment paths for future research. These future treatments may have a huge impact on patients and caregivers worldwide, warranting widespread collaboration to further this research.
References
Poewe W, Seppi K, Tanner CM, et al. Parkinson disease. Nat Rev Dis Prim. 3(1). doi:10.1038/nrdp.2017.13
Busche MA, Hyman BT. Synergy between amyloid-β and tau in Alzheimer’s disease. Nat Neurosci. 2020;23(10):1183-1193. doi:10.1038/s41593-020-0687-6
Dotiwala A, McCausland C, Samra N. Anatomy, Head and Neck: Blood Brain Barrier. StatPearls Publishing, Treasure Island (FL); 2023. https://www.ncbi.nlm.nih.gov/books/NBK519556/.
Gandhi K, Saadabadi A. Levodopa (L-Dopa). Florida: StatPearls Publishing, Treasure Island (FL); 2023. https://www.ncbi.nlm.nih.gov/books/NBK482140/.
Marsden CD. Problems with long-term levodopa therapy for Parkinson’s disease. Clin Neuropharmacol. 1994;17 Suppl 2:S32-44. http://www.ncbi.nlm.nih.gov/pubmed/9358193.
Yiannopoulou KG, Papageorgiou SG. Current and Future Treatments in Alzheimer Disease: An Update. J Cent Nerv Syst Dis. 2020;12. doi:10.1177/1179573520907397
Cummings J. Anti-Amyloid Monoclonal Antibodies are Transformative Treatments that Redefine Alzheimer’s Disease Therapeutics. Drugs. 2023;83(7):569-576. doi:10.1007/s40265-023-01858-9
Li Z, Shue F, Zhao N, Shinohara M, Bu G. APOE2: protective mechanism and therapeutic implications for Alzheimer’s disease. Mol Neurodegener. 2020;15(1):1-19. doi:10.1186/s13024-020-00413-4
Rosenberg JB, Kaplitt MG, De BP, et al. AAVrh.10-Mediated APOE2 Central Nervous System Gene Therapy for APOE4-Associated Alzheimer’s Disease. Hum Gene Ther Clin Dev. 2018;29(1):24-47. doi:10.1089/humc.2017.231
Dara S, Dhamercherla S, Jadav SS, Babu CM, Ahsan MJ. Machine Learning in Drug Discovery: A Review. Vol 55. Springer Netherlands; 2022. doi:10.1007/s10462-021-10058-4
Çelik IN, Arslan FK, Tun R, Yildiz I. Artificial Intelligence on Drug Discovery and Development. Ankara Univ Eczac Fak Derg. 2022;46(2):400-427. doi:10.33483/jfpau.878041q
Cummings J, Aisen PS, Dubois B, et al. Drug development in Alzheimer’s disease: The path to 2025. Alzheimer’s Res Ther. 2016;8(1):1-12. doi:10.1186/s13195-016-0207-9
Poongothai S, Anjana RM, Aarthy R, et al. Strategies for participant retention in long term clinical trials: A participant -centric approaches. Perspect Clin Res. 2023;14(1):3-9. doi:10.4103/picr.picr_161_21
Satyanarayana Rao K. Informed consent: An ethical obligation or legal compulsion? J Cutan Aesthet Surg. 2008;1(1):33. doi:10.4103/0974-2077.41159
Kim SYH. The ethics of informed consent in Alzheimer disease research. Nat Rev Neurol. 2011;7(7):410-414. doi:10.1038/nrneurol.2011.76
Öksüz N, Öztürk Ş, Doğu O. Future Prospects in Parkinson’s Disease Diagnosis and Treatment. Noropsikiyatri Ars. 2022;59(Supplement 1):S36-S41. doi:10.29399/npa.28169
Lacorte E, Ancidoni A, Zaccaria V, et al. Safety and Efficacy of Monoclonal Antibodies for Alzheimer’s Disease: A Systematic Review and Meta-Analysis of Published and Unpublished Clinical Trials. J Alzheimer’s Dis. 2022;87(1):101-129. doi:10.3233/JAD-220046
WHO. Parkinson’s disease. World Health Organisation.
Burns A. The burden of Alzheimer’s disease. Int J Neuropsychopharmacol. 2000;3. doi:10.1093/ijnp/3.Supplement_2.S31
Further Reading
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