Abstract
Alzheimer’s disease, having a large U.S. patient population, is associated with significant health and economic detriments. Historically, drug discovery efforts have yielded limited success, however, multimodal information and understandings on novel targets are improving. Scientific consensus suggests that the future Alzheimer’s landscape will resemble diabetes, with incremental treatment innovations over time. Organizations can build more predictive forecasts by modelling payer perspectives to pricing and adoption in this emergent space.
The Growing Burden of Alzheimer’s in the U.S.
Alzheimer’s disease is a growing problem in the United States. 5.8 million Americans aged 65 or older (1.7% of the population) suffer from Alzheimer’s, and it is currently the sixth-leading overall cause of death in this country [1–2]. The number of affected individuals is projected to reach 13.8 million by 2050 [1–3]. Current FDA-approved treatments manage dementia symptoms for a limited time, in some patients, by altering levels of brain activity [1]. Non-pharmacological options, such as cognitive therapy, improve cognition for a few months at best in some patients [1–4]. The search for disease-modifying therapeutics has had a 100% failure rate thus far [3].
A High Rate of Failure
Several factors may be responsible for the poor performance of past drug candidates. One important factor is that most drug candidates have been identified based on whether “model animals” that is, animals engineered to have symptoms that mimic Alzheimer’s disease show improvement upon treatment. Animal models are often engineered to match specific abnormalities observed in human patients with Alzheimer’s. Without knowing the underlying causes, it is impossible to mimic the full, human form of Alzheimer’s in an animal. The most well-documented such abnormality in Alzheimer’s is the buildup of amyloid beta (Aꞵ), a protein that forms toxic plaques around neurons and is thought to elicit neuronal death [1,5,7]. Animal models used to find Aꞵ-targeting candidates have been engineered to maximize the presence of Aꞵ plaques, under the assumption that Aꞵ plaques are a cause of Alzheimer’s dementia. The problem with this approach is that, if an abnormality is not a cause, but instead a symptom, of the disease, any drug candidates that result will likely not treat the disease in humans. Much funding in the last several years has focused on primarily finding drugs to target Aꞵ plaques, rather than other molecules that appear at abnormal levels in Alzheimer’s [7].
Promising Approaches
The failure of efforts to slow Alzheimer’s with Aꞵ-targeting drugs illustrates the importance of data-driven insights in finding new treatments. With much multimodal information becoming within reach about the whole patient picture in Alzheimer’s disease, from observations of mitochondrial and synaptic dysfunction to abnormalities in protein production to systemic changes that co-occur with Alzheimer’s, studies that integrate these datasets are likely to lead to helpful new directions in drug discovery [5]. In the near term, protein or enzyme targets that are revealed to have a positive relationship with dementia severity across patient profiles should be regarded as a first waypoint for drug discovery efforts. One such target that has been suggested is the Tau protein, another famous indicator of Alzheimer’s. Tau also accumulates abnormally, inside neurons, but has been traditionally assumed to be a downstream product of Aꞵ plaques. However, unlike brain Aꞵ levels, data indicates that Tau levels do appear to correlate with the severity of cognitive decline [5]. Investing in drugs to target this protein may take the field a bit closer to a treatment.
Implications for Cooperate Strategy & Market Access
It is likely that, in the near term, treatment innovations will be incremental, similar to a stepwise approach for illnesses observed in type-2 diabetes or hypertension. Small-emerging companies, account for 77% of Alzheimer’s clinical programs [9]. These companies are principally venture backed and/or have in place development partnerships with larger pharmaceutical organizations. Biopharmaceutical organizations can better position for opportunities and payer sensitivity thresholds in the Alzheimer’s landscape by developing a comprehensive overview on how key competitors are evolving across the industry, identifying the most relevant trends, and aligning with evolving regulatory guidelines. All of which underpin greater efficiency and effectiveness to capturing value in the Alzheimer’s clinical development arena.
Contributors
Dillon Shokar is a Growth Lead at Princeton Biopartners. He has significant experience in biopharmaceutical strategic consulting and venture capital. Prior experiences range from advising on go-to-market strategies for oncology therapies, to orchestrating growth-financing for health-technology companies. Dillon has an MSc in Biostatistics from King’s College London and a CFA in Financial Analysis.
Alyssa Wilson is a Subject Matter Expert at Princeton Biopartners. Previously she was a Postdoctoral Fellow at the Princeton Neuroscience Institute, where she worked on the relationship between response properties of different excitatory axon types. She received her PhD in Physics from Harvard University and MPhil in Physics from the University of Cambridge.
References
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8. Goldman Sachs research from Flynn, 2020
9. Volume IV: Alzheimer’s Disease Therapeutics, David Thomas, CFA, 2019