US Pharm. 2017;42(1):8-11.
Complex neurodegenerative diseases affect millions of Americans and include such conditions as Alzheimer’s disease (AD), Parkinson’s disease, and amyotrophic lateral sclerosis (ALS).
Overview and Scope of the Problem
In the United States, approximately 5.4 million individuals are affected by AD, the most common form of dementia in the U.S.; about 1 in 9 persons aged >65 years have the disease.1 AD is the sixth-leading cause of death and was responsible for 84,000 deaths in the U.S. in 2013.1
AD and other dementias are responsible for $236 billion in healthcare spending per year in the U.S., including long-term care and hospice.1 One in every five Medicare dollars goes toward the care of individuals with dementia. In addition to the patients, the disease takes an enormous toll on caregivers who care for the affected family member around the clock. This uncompensated care is estimated to have an economic value of $221 billion and results in health issues and lost productivity for the caregivers. By 2050, without a cure or major treatment breakthrough, the cost of AD care is expected to spiral to $1 trillion in the U.S.1
Approximately 60,000 people in the U.S. are diagnosed each year with Parkinson’s disease, another neurodegenerative condition that causes a progressive movement disorder.2 Over one million persons in the U.S. and 10 million individuals worldwide are afflicted by this disease. The economic cost of Parkinson’s, including medical care and time lost from work, is estimated at $25 billion in the U.S.2
ALS, another devastating neurodegenerative disease, results in progressive loss of motor neurons and eventual paralysis of the affected individual. This disease is well known because of the late baseball player Lou Gehrig and theoretical physicist Stephen Hawking, both afflicted with the disease. In the U.S., approximately 6,000 individuals are diagnosed with this disease every year, and the prevalence of ALS is about 20,000 at any given time.3 The disease usually strikes individuals in the prime of their life, between age 40 and 70 years, with the average being 55. About 10% of ALS is familial, and a genetic mutation can be identified in 60% to 70% of individuals with familial ALS.3
Current Pharmacologic/Therapeutic Approaches
Neither AD, Parkinson’s disease, nor ALS can be cured with current pharmacologic approaches, and intensive efforts are underway to develop novel and more effective therapeutics. Current pharmacologic therapies for AD are very limited and include five FDA-approved drugs: donepezil (Aricept), galantamine (Razadyne), memantine (Namenda), rivastigmine (Exelon), and donepezil combined with memantine (Namzaric).1 AD is associated with the loss of cholinergic neurons in the brain.4 Cholinesterase inhibitors (donepezil, galantamine, and rivastigmine) inhibit the break-down of the neurotransmitter acetylcholine in synaptic clefts and enhance neurotransmission; these drugs are efficacious in ameliorating symptoms in mild-to-moderate AD, but have a modest effect at best.4
Memantine is an N-methyl-d-aspartate (NMDA) receptor antag-onist.5 NMDA receptors constitute a glutamate receptor subfamily that is broadly involved in brain function.5 In AD, excessive exposure to the neurotransmitter glutamate is thought to stimulate excessive entry of calcium ions into neurons, resulting in neuronal injury or death.6 Memantine is believed to work by blocking calcium ion flow through ion channels associated with NMDA receptors.5,6
Memantine is an uncompetitive, low-affinity, open channel blocker, and works primarily when the ion channels are excessively open, but does not interfere with normal channel function.6 Memantine is currently the only FDA-approved drug for AD that is considered neuroprotective because it protects neurons from the effects of the excessive release of glutamate.5,6
Parkinson’s disease is characterized by loss of dopaminergic neurons in the part of the brain known as the substantia nigra.7 Dopamine is involved in the transmission of signals that control body movements. Pharmacologic treatment consists of drugs that increase or substitute for dopamine and thereby stimulate dopamine receptors in the brain. Levodopa passes through the blood-brain barrier and is converted into dopamine in the brain. Levodopa is combined with carbidopa to protect levodopa from premature conversion to dopamine outside the brain. Carbidopa-levodopa is the most effective treatment for Parkinson’s.7
In addition, dopamine agonists, which mimic the actions of dopamine in the brain, can be used; examples include pramipexole (Mirapex), ropinirole (Requip), rotigotine (Neupro transdermal), and apomorphine (Apokyn). MAO-B inhibitors such as selegiline (Eldepryl, Zelapar) and rasagiline (Azilect) help prevent metabolism of brain dopamine by blocking the enzyme monoamine oxidase B. Catechol-O-methyl-transferase (COMT) inhibitors such as entacapone (Comtan) and tolcapone (Tasmar) also prolong the effects of levodopa therapy.7
There is only one FDA-approved agent that has beneficial effects for patients with ALS—riluzole (Rilutek, Teglutik)—which extends life, or the time to tracheostomy, for several months.3 Riluzole is a neuroprotective drug that downregulates glutamatergic neurotransmission in the brain via several mechanisms.8 This agent inhibits the release of glutamate from neurons due to inactivation of voltage-dependent sodium channels on glutamatergic nerve terminals.8 The drug is also a noncompetitive blocker of NMDA receptors in the brain.8 Finally, the drug stimulates the reuptake of glutamate in synapses.9
Despite the progress that has been made with the aforemen-tioned pharmaceuticals, none of these agents is curative. Because of the aging population in the U.S., there is a critical need for more effective agents. By 2050, the cost of care for neurodegenerative diseases could consume the entire gross national product of the U.S. unless more effective interventions are discovered.6
Status of the Pipeline and Future Directions
There is a political initiative to develop drugs that can prevent or modify the course of neurodegenerative diseases by 2025.10 However, the current scientific reality is that there are only likely to be a few viable candidates among drugs in the pipeline by that time—unless there are novel insights and breakthroughs. At present, there are five active immunotherapies, 11 passive immunotherapies, and 55 small molecules being evaluated in phase I to III clinical trials for AD.8 It is expected that only a few of these will be approved by 2025.10 In order to accelerate the development of successful disease-preventing or disease-modifying drugs, a greater understanding of the neurodegenerative diseases is required, and novel ground-breaking approaches to drug discovery are needed. One important area is the discovery of new biomarkers, which can be used to predict onset, validate the diagnosis of, and monitor progression and remission of neurodegenerative diseases. Coupled with the discovery of biomarkers, there is great promise that advanced computer analytics can be employed using enormous databases of biomarker and clinical data to develop hypotheses and help shape the direction of future research for preventive and effective disease-modifying pharmaceuticals.
Biomarkers have been defined as a “broad subcategory of medical signs—that is, objective indications of medical state observed from outside the patient—who can be measured accurately and reproducibly.”11 Using this broad definition, a biomarker could be anything from vital signs (pulse and blood pressure) to complex laboratory test or imaging results. The exact relationship between a proposed biomarker and the risk of developing a disease, establishing the diagnosis of the disease, monitoring the progression of the disease, or tracking the remission of the disease needs to be established through research. Hence, the validity of a biomarker with respect to hard clinical endpoints must be validated.
Well-validated biomarkers are sometimes used as surrogate endpoints in the evaluation of responses to pharmaceutical agents.11 One common example is the use of glycosylated hemoglobin (A1C) in predicting microvascular outcomes in clinical trials of pharmaceutical agents for diabetes.
In the neurosciences arena, there are a myriad of possible biomarkers. These could include clinical signs; features from the clinical neurologic examination; neurologic diagnostic study results (e.g., EEG, electrophysiology measurements); laboratory biochemical measurements on blood and cerebrospinal fluid (CSF); and analysis of DNA, RNA, genomics, proteomics, cellular electrophysiology, and neuroimaging (positron emission tomography [PET] and MRI).11
At the present time, there are several known diagnostic biomarkers for AD, including the measurement of amyloid beta 42 peptide (A42) and tau protein (total tau or phosphorylated tau [P-tau]) in CSF.10 Diagnostic imaging biomarkers for AD in the neuroimaging category include PET imaging with amyloid or tau tracers. Certain MRI-related neuroimaging biomarkers are useful as AD progression markers. However, to date there are no validated, qualified biomarkers to be used as surrogate endpoints in clinical trials of pharmaceuticals for AD. Unless there is a major breakthrough, no such biomarker is expected to be available by 2025.10
A biomarker that can serve as a surrogate endpoint would need to accurately predict clinical benefit and would greatly simplify the clinical trials of pharmaceutical agents. Hence, identification of such biomarkers for AD and other neurodegenerative diseases is a high priority; biomarkers have been identified as one of 12 emerging technologies that will revolutionize neurologic and psychiatric care.12
Big Data, Advanced Analytics, and Artificial Intelligence
A massive collection of data aggregated from multiple sources and stored in a computer system for analysis is termed “big data.”13 Such data collections can range in size from hundreds of terabytes to hundreds of petabytes (1 petabyte = 1 quadrillion bytes). To put this into perspective, it is estimated that the human brain can store 2.5 petabytes of memories.14 IBM has developed a computer storage drive as large as 120 petabytes.15
In neuroscience research, a big data collection could include all scientific peer-reviewed literature from the last three decades (in electronic format), all known information about the human genome, all known information about protein crystal structure, and everything known about neuroanatomy, neurophysiology, cellular signaling and physiology, neuroelectrophysiology, neuroimaging data, organic chemistry, and the structure of all known organic compounds. This research could also include clinical data collections from thousands of patients affected by neurodegenerative diseases (as stored in de-identified electronic health records). This massive array of data would be more than any one human researcher could ever absorb and analyze in a lifetime. However, the availability of advanced analytics running on supercomputers could use such data collections to generate new hypotheses.
Current massively parallel supercomputers can now achieve computational speeds in excess of tens of quadrillions of floating point operations per second (petaflops). The first super-computers were built primarily by Seymour Cray at Control Data Corporation in the 1960s and 1970s and featured a few parallel processors.16 The IBM Blue Gene/P, in contrast, has 250,000 parallel processors. This machine has been used to simulate the function of the human brain.16 IBM has launched its artificial intelligence interface, known as Watson, which can process natural language and learn concepts. IBM terms this “a cognitive technology that can think like a human.”17 Watson is now teaming up with neuroscience researchers to help focus on the challenge of developing cures for neuro-degenerative diseases.18
Ironically, Stephen Hawking warned us about the potential dangers of artificial intelligence,19 but when used in a constructive fashion, artificial intelligence, supercomputers, and big data might help us with our most challenging medical problems.
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2. Parkinson’s Disease Foundation. Statistics on Parkinson’s. www.pdf.org/en/parkinson_statistics. Accessed November 19, 2016.
3. ALS Association. Facts you should know. www.alsa.org/about-als/facts-you-should-know.html. Accessed November 19, 2016.
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17. IBM Corporation. Go beyond artificial intelligence with Watson. www.ibm.com/watson/. Accessed November 19, 2016.
18. IBM Corporation. Canadian neuroscience leaders tap IBM Watson to speed time to discovering new drugs for Parkinson’s disease. Press release. October 12, 2016. www.ibm.com/news/ca/en/2016/10/12/w711820i37027w27.html. Accessed November 19, 2016.
19. Cellan-Jones R. Stephen Hawking warns artificial intelligence could end mankind. BBC News. December 2, 2014. www.bbc.com/news/technology-30290540. Accessed November 19, 2016.
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