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Section 1 - Advancing Alzheimer’s Disease Therapies in a Collaborative Science Ecosystem

Published online by Cambridge University Press:  03 March 2022

Jeffrey Cummings
Affiliation:
University of Nevada, Las Vegas
Jefferson Kinney
Affiliation:
University of Nevada, Las Vegas
Howard Fillit
Affiliation:
Alzheimer’s Drug Discovery Foundation
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Alzheimer's Disease Drug Development
Research and Development Ecosystem
, pp. 1 - 72
Publisher: Cambridge University Press
Print publication year: 2022

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References

References

Scheltens, P, Blennow, K, Breteler, MM, et al. Alzheimer’s disease. Lancet 2016; 388: 505–17.CrossRefGoogle ScholarPubMed
Masters, CL, Bateman, R, Blennow, K, et al. Alzheimer’s disease. Nat Rev Dis Primers 2015; 1: 15056.CrossRefGoogle ScholarPubMed
Alzheimer’s Association. Alzheimer’s disease facts and figures. Alzheimer Dement 2019; 15: 321–87.Google Scholar
Alzheimer’s Disease International. World Alzheimer Report 2015: The Global Impact of Dementia. London: Alzheimer’s Disease International; 2015.Google Scholar
Cummings, JL, Morstorf, T, Zhong, K. Alzheimer’s disease drug-development pipeline: few candidates, frequent failures. Alzheimers Res Ther 2014; 6: 37.Google Scholar
Wang, X, Sun, G, Feng, T, et al. Sodium oligomannate therapeutically remodels gut microbiota and suppresses gut bacterial amino acids-shaped neuroinflammation to inhibit Alzheimer’s disease progression. Cell Res 2019; 29: 787803.CrossRefGoogle ScholarPubMed
Servick, K. Doubts persist for claimed Alzheimer’s drug. Science 2019; 366: 1298.Google Scholar
Cummings, J, Ritter, A, Zhong, K. Clinical trials for disease-modifying therapies in Alzheimer’s disease: a primer, lessons learned, and a blueprint for the future. J Alzheimers Dis 2018; 64: S322.Google Scholar
Cummings, J, Fox, N. Defining disease modifying therapy for Alzheimer’s disease. J Prev Alzheimers Dis 2017; 4: 109–15.Google Scholar
Cummings, J. Disease modification and neuroprotection in neurodegenerative disorders. Transl Neurodegener 2017; 6: 25.CrossRefGoogle ScholarPubMed
Fauman, EB, Rai, BK, Huang, ES. Structure-based druggability assessment: identifying suitable targets for small molecule therapeutics. Curr Opin Chem Biol 2011; 15: 463–8.CrossRefGoogle ScholarPubMed
Ambure, P, Roy, K. Advances in quantitative structure–activity relationship models of anti-Alzheimer’s agents. Expert Opin Drug Discov 2014; 9: 697723.Google Scholar
Gimenez, BG, Santos, MS, Ferrarini, M, et al. Evaluation of blockbuster drugs under the rule-of-five. Pharmazie 2010; 65: 148–52.Google ScholarPubMed
Leeson, PD. Molecular inflation, attrition and the rule of five. Adv Drug Deliv Rev 2016; 101: 2233.CrossRefGoogle ScholarPubMed
Hughes, JP, Rees, S, Kalindjian, SB, et al. Principles of early drug discovery. Br J Pharmacol 2011; 162: 1239–49.CrossRefGoogle ScholarPubMed
Dragunow, M. High-content analysis in neuroscience. Nat Rev Neurosci 2008; 9: 779–88.CrossRefGoogle ScholarPubMed
Alqahtani, S, Mohamed, LA, Kaddoumi, A. Experimental models for predicting drug absorption and metabolism. Expert Opin Drug Metab Toxicol 2013; 9: 1241–54.CrossRefGoogle ScholarPubMed
Redfern, WS, Carlsson, L, Davis, AS, et al. Relationships between preclinical cardiac electrophysiology, clinical QT interval prolongation and torsade de pointes for a broad range of drugs: evidence for a provisional safety margin in drug development. Cardiovasc Res 2003; 58: 3245.Google Scholar
Bass, AS, Cartwright, ME, Mahon, C, et al. Exploratory drug safety: a discovery strategy to reduce attrition in development. J Pharmacol Toxicol Methods 2009; 60: 6978.Google Scholar
Freed, LM. Dose selection for first-in-human (FIH) trials: regulatory perspective. In Krishna, R, ed., Dose Optimization in Drug Development. New York, NY: Taylor & Francis Group, LLC; 2006: 4560.CrossRefGoogle Scholar
Presta, LG. Selection, design, and engineering of therapeutic antibodies. J Allergy Clin Immunol 2005; 116: 731–6.Google Scholar
Pul, R, Dodel, R, Stangel, M. Antibody-based therapy in Alzheimer’s disease. Expert Opin Biol Ther 2011; 11: 343–57.CrossRefGoogle ScholarPubMed
Sabbagh, JJ, Kinney, JW, Cummings, JL. Alzheimer’s disease biomarkers in animal models: closing the translational gap. Am J Neurodegener Dis 2013; 2: 108–20.Google ScholarPubMed
Puzzo, D, Gulisano, W, Palmeri, A, et al. Rodent models for Alzheimer’s disease drug discovery. Expert Opin Drug Discov 2015; 10: 703–11.CrossRefGoogle ScholarPubMed
Choi, SH, Kim, YH, Hebisch, M, et al. A three-dimensional human neural cell culture model of Alzheimer’s disease. Nature 2014; 515: 274–8.CrossRefGoogle ScholarPubMed
Liu, Q, Waltz, S, Woodruff, G, et al. Effect of potent gamma-secretase modulator in human neurons derived from multiple presenilin 1-induced pluripotent stem cell mutant carriers. JAMA Neurol 2014; 71: 1481–9.Google Scholar
Umscheid, CA, Margolis, DJ, Grossman, CE. Key concepts of clinical trials: a narrative review. Postgrad Med 2011; 123: 194204.CrossRefGoogle ScholarPubMed
Cummings, JL. Translational scoring of candidate treatments for Alzheimer’s disease: a systematic approach. Dement Geriatr Cogn Disord 2020; 49: 2237.CrossRefGoogle ScholarPubMed
Emilien, G, van Meurs, W, Maloteaux, JM. The dose–response relationship in phase I clinical trials and beyond: use, meaning, and assessment. Pharmacol Ther 2000; 88: 3358.CrossRefGoogle ScholarPubMed
Cummings, J. Lessons learned from Alzheimer disease: clinical trials with negative outcomes. Clin Transl Sci 2018; 11: 147–52.CrossRefGoogle ScholarPubMed
Dubois, B, Feldman, HH, Jacova, C, et al. Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria. Lancet Neurol 2014; 13: 614–29.Google Scholar
Rosen, WG, Mohs, RC, Davis, KL. A new rating scale for Alzheimer’s disease. Am J Psychiatry 1984; 141: 1356–64.Google Scholar
Morris, JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 1993; 43: 2412–14.CrossRefGoogle ScholarPubMed
Cummings, JL. Optimizing phase II of drug development for disease-modifying compounds. Alzheimers Dement 2008; 4: S1520.CrossRefGoogle ScholarPubMed
Cummings, J, Feldman, HH, Scheltens, P. The “rights” of precision drug development for Alzheimer’s disease. Alzheimers Res Ther 2019; 11: 76.Google Scholar
Greenberg, BD, Carrillo, MC, Ryan, JM, et al. Improving Alzheimer’s disease phase II clinical trials. Alzheimers Dement 2013; 9: 3949.Google Scholar
Gray, JA, Fleet, D, Winblad, B. The need for thorough phase II studies in medicines development for Alzheimer’s disease. Alzheimers Res Ther 2015; 7: 67.Google Scholar
Bateman, RJ, Munsell, LY, Morris, JC, et al. Human amyloid-beta synthesis and clearance rates as measured in cerebrospinal fluid in vivo. Nat Med 2006; 12: 856–61.Google Scholar
Kennedy, ME, Stamford, AW, Chen, X, et al. The BACE1 inhibitor verubecestat (MK-8931) reduces CNS beta-amyloid in animal models and in Alzheimer’s disease patients. Sci Transl Med 2016; 8: 363ra150.CrossRefGoogle ScholarPubMed
Portelius, E, Zetterberg, H, Dean, RA, et al. Amyloid-beta(1–15/16) as a marker for gamma-secretase inhibition in Alzheimer’s disease. J Alzheimers Dis 2012; 31: 335–41.Google Scholar
Sevigny, J, Suhy, J, Chiao, P, et al. Amyloid PET screening for enrichment of early-stage Alzheimer disease clinical trials: experience in a Phase 1b clinical trial. Alzheimer Dis Assoc Disord 2016; 30: 17.Google Scholar
Sperling, RA, Jack, CR, Jr., Black, SE, et al. Amyloid-related imaging abnormalities in amyloid-modifying therapeutic trials: recommendations from the Alzheimer’s Association Research Roundtable Workgroup. Alzheimers Dement 2011; 7: 367–85.Google Scholar
Sperling, R, Salloway, S, Brooks, DJ, et al. Amyloid-related imaging abnormalities in patients with Alzheimer’s disease treated with bapineuzumab: a retrospective analysis. Lancet Neurol 2012; 11: 241–9.CrossRefGoogle ScholarPubMed
Babiloni, C, Lizio, R, Marzano, N, et al. Brain neural synchronization and functional coupling in Alzheimer’s disease as revealed by resting state EEG rhythms. Int J Psychophysiol 2016; 103: 88102.CrossRefGoogle ScholarPubMed
Sperling, RA, Dickerson, BC, Pihlajamaki, M, et al. Functional alterations in memory networks in early Alzheimer’s disease. Neuromolecular Med 2010; 12: 2743.Google Scholar
Cummings, J, Zhong, K, Cordes, D. Drug development in Alzheimer’s disease: the role of default mode network assessment in phase II. US Neurol 2017; 13: 67.Google Scholar
Sevigny, J, Chiao, P, Bussiere, T, et al. The antibody aducanumab reduces Abeta plaques in Alzheimer’s disease. Nature 2016; 537: 50–6.CrossRefGoogle ScholarPubMed
Sheiner, LB. Learning versus confirming in clinical drug development. Clin Pharmacol Ther 1997; 61: 275–91.CrossRefGoogle ScholarPubMed
Crous-Bou, M, Minguillon, C, Gramunt, N, et al. Alzheimer’s disease prevention: from risk factors to early intervention. Alzheimers Res Ther 2017; 9: 71.CrossRefGoogle ScholarPubMed
Food and Drug Administration. Early Alzheimer’s Disease: Developing Drugs for Treatment. Guidance for Industry. US Department of Health and Human Services Food and Drug Administration Center for Drug Evaluation and Research (CDER) Center for Biologics Evaluation and Research (CBER); 2018.Google Scholar
Cummings, JL, Fox, N. Defining disease modification for Alzheimer’s disease clinical trials. J Prev Alzheimers Dis 2017; 4: 109–15.Google Scholar
Jack, CR, Jr., Bennett, DA, Blennow, K, et al. NIA-AA Research Framework: toward a biological definition of Alzheimer’s disease. Alzheimers Dement 2018; 14: 535–62.Google Scholar
Molinuevo, JL, Ayton, S, Batrla, R, et al. Current state of Alzheimer’s fluid biomarkers. Acta Neuropathol 2018; 136: 821–53.Google Scholar
Leber, P. Guidelines for the Clinical Evaluation of Antidementia Drugs. First draft. Technical Report. FDA Neuro-Pharm Group; 1990.Google Scholar
Karin, A, Hannesdottir, K, Jaeger, J, et al. Psychometric evaluation of ADAS-cog and NTB for measuring drug response. Acta Neurol Scand 2014; 129: 114–22.Google Scholar
Schmitt, FA, Ashford, W, Ernesto, C, et al. The Severe Impairment Battery: concurrent validity and the assessment of longitudinal change in Alzheimer’s disease. The Alzheimer’s Disease Cooperative Study. Alzheimer Dis Assoc Disord 1997; 11: S51–6.CrossRefGoogle ScholarPubMed
Galasko, D, Bennett, D, Sano, M, et al. An inventory to assess activities of daily living for clinical trials in Alzheimer’s disease. The Alzheimer’s Disease Cooperative Study. Alzheimer Dis Assoc Disord 1997; 11: S33–9.Google Scholar
Sikkes, SA, Pijnenburg, YA, Knol, DL, et al. Assessment of instrumental activities of daily living in dementia: diagnostic value of the Amsterdam Instrumental Activities of Daily Living Questionnaire. J Geriatr Psychiatry Neurol 2013; 26: 244–50.Google Scholar
Zarit, SH, Reever, KE, Bach-Peterson, J. Relatives of the impaired elderly: correlates of feelings of burden. Gerontologist 1980; 20: 649–55.CrossRefGoogle ScholarPubMed
Logsdon, RG, Gibbons, LE, McCurry, SM, et al. Assessing quality of life in older adults with cognitive impairment. Psychosom Med 2002; 64: 510–19.Google Scholar
Wimo, A, Winblad, B. Resource utilisation in dementia: RUD lite. Brain Aging 2003; 3: 4859.Google Scholar
Donohue, MC, Sperling, RA, Salmon, DP, et al. The Preclinical Alzheimer Cognitive Composite: measuring amyloid-related decline. JAMA Neurol 2014; 71: 961–70.CrossRefGoogle ScholarPubMed
Langbaum, JB, Ellison, NN, Caputo, A, et al. The Alzheimer’s Prevention Initiative Composite Cognitive Test: a practical measure for tracking cognitive decline in preclinical Alzheimer’s disease. Alzheimers Res Ther 2020; 12: 66.Google Scholar
Bateman, RJ, Benzinger, TL, Berry, S, et al. The DIAN-TU Next Generation Alzheimer’s prevention trial: adaptive design and disease progression model. Alzheimers Dement 2017; 13: 819.Google Scholar
Solomon, A, Kivipelto, M, Molinuevo, JL, et al. European Prevention of Alzheimer’s Dementia Longitudinal Cohort Study (EPAD LCS): study protocol. BMJ Open 2019; 8: e021017.Google Scholar
Cummings, JL, Froelich, L, Black, SE, et al. Randomized, double-blind, parallel-group, 48-week study for efficacy and safety of a higher-dose rivastigmine patch (15 vs. 10 cm(2)) in Alzheimer’s disease. Dement Geriatr Cogn Disord 2012; 33: 341–53.Google Scholar
Farlow, M, Veloso, F, Moline, M, et al. Safety and tolerability of donepezil 23 mg in moderate to severe Alzheimer’s disease. BMC Neurol 2011; 11: 5764.CrossRefGoogle ScholarPubMed
Cummings, J, Reiber, C, Kumar, P. The price of progress: funding and financing Alzheimer’s disease drug development. Alzheimers Dement (N Y) 2018; 4: 330–43.Google Scholar
DeTure, MA, Dickson, DW. The neuropathological diagnosis of Alzheimer’s disease. Mol Neurodegener 2019; 14: 32.CrossRefGoogle ScholarPubMed
Gersdorf, T, He, VF, Schlesinger, A, et al. Demystifying industry–academia collaboration. Nat Rev Drug Discov 2019; 18: 743–4.Google Scholar
Silva, PJ, Ramos, KS. Academic medical centers as innovation ecosystems: evolution of industry partnership models beyond the Bayh–Dole Act. Acad Med 2018; 93: 1135–41.CrossRefGoogle ScholarPubMed
Yokley, BH, Hartman, M, Slusher, BS. Role of academic drug discovery in the quest for new CNS therapeutics. ACS Chem Neurosci 2017; 8: 429–31.Google Scholar
Ganem, D. Physician–scientist careers in the biotechnology and pharmaceutical industries. J Infect Dis 2018; 218: S204.Google Scholar
Slusher, BS, Conn, PJ, Frye, S, et al. Bringing together the academic drug discovery community. Nat Rev Drug Discov 2013; 12: 811–12.Google Scholar
Wiederrecht, GJ, Hill, RG, Beer, MS. Partnership between small biotech and big pharma. IDrugs 2006; 9: 560–4.Google Scholar
Finkbeiner, S. Bridging the valley of death of therapeutics for neurodegeneration. Nat Med 2010; 16: 1227–32.Google Scholar
Parrish, MC, Tan, YJ, Grimes, KV, et al. Surviving in the valley of death: opportunities and challenges in translating academic drug discoveries. Annu Rev Pharmacol Toxicol 2019; 59: 405–21.Google Scholar
Goldman, DP, Fillit, H, Neumann, P. Accelerating Alzheimer’s disease drug innovations from the research pipeline to patients. Alzheimers Dement 2018; 14: 833–6.Google Scholar
Reis, SE, Berglund, L, Bernard, GR, et al. Reengineering the national clinical and translational research enterprise: the strategic plan of the National Clinical and Translational Science Awards Consortium. Acad Med 2010; 85: 463–9.Google Scholar
Grill, JD, Di, L, Lu, PH, et al. Estimating sample sizes for predementia Alzheimer’s trials based on the Alzheimer’s Disease Neuroimaging Initiative. Neurobiol Aging 2013; 34: 6272.Google Scholar
Holland, D, McEvoy, LK, Desikan, RS, et al. Enrichment and stratification for predementia Alzheimer disease clinical trials. PLoS One 2012; 7: e47739.Google Scholar
Kohannim, O, Hua, X, Hibar, DP, et al. Boosting power for clinical trials using classifiers based on multiple biomarkers. Neurobiol Aging 2010; 31: 1429–42.Google Scholar
McEvoy, LK, Edland, SD, Holland, D, et al. Neuroimaging enrichment strategy for secondary prevention trials in Alzheimer disease. Alzheimer Dis Assoc Disord 2010; 24(3): 269–77.CrossRefGoogle ScholarPubMed
Hendrix, JA, Finger, B, Weiner, MW, et al. The Worldwide Alzheimer’s Disease Neuroimaging Initiative: an update. Alzheimers Dement 2015; 11: 850–9.Google Scholar
Iwatsubo, T, Iwata, A, Suzuki, K, et al. Japanese and North American Alzheimer’s Disease Neuroimaging Initiative studies: harmonization for international trials. Alzheimers Dement 2018; 14: 1077–87.Google Scholar
Grill, JD, Raman, R, Ernstrom, K, et al. Comparing recruitment, retention, and safety reporting among geographic regions in multinational Alzheimer’s disease clinical trials. Alzheimers Res Ther 2015; 7: 39.Google Scholar
Henley, DB, Dowsett, SA, Chen, YF, et al. Alzheimer’s disease progression by geographical region in a clinical trial setting. Alzheimers Res Ther 2015; 7: 43.Google Scholar
Moulder, KL, Snider, BJ, Mills, SL, et al. Dominantly Inherited Alzheimer Network: facilitating research and clinical trials. Alzheimers Res Ther 2013; 5: 48.Google Scholar
Tariot, PN, Lopera, F, Langbaum, JB, et al. The Alzheimer’s Prevention Initiative Autosomal-Dominant Alzheimer’s Disease Trial: a study of crenezumab versus placebo in preclinical PSEN1 E280A mutation carriers to evaluate efficacy and safety in the treatment of autosomal-dominant Alzheimer’s disease, including a placebo-treated noncarrier cohort. Alzheimers Dement (N Y) 2018; 4: 150–60.Google Scholar
Lopez Lopez, C, Tariot, PN, Caputo, A, et al. The Alzheimer’s Prevention Initiative Generation Program: study design of two randomized controlled trials for individuals at risk for clinical onset of Alzheimer’s disease. Alzheimers Dement (N Y) 2019; 5: 216–27.Google Scholar
Ayutyanont, N, Langbaum, JB, Hendrix, SB, et al. The Alzheimer’s Prevention Initiative Composite Cognitive Test score: sample size estimates for the evaluation of preclinical Alzheimer’s disease treatments in presenilin 1 E280A mutation carriers. J Clin Psychiatry 2014; 75: 652–60.Google Scholar
Langlois, CM, Bradbury, A, Wood, EM, et al. Alzheimer’s Prevention Initiative Generation Program: development of an ApoE genetic counseling and disclosure process in the context of clinical trials. Alzheimers Dement (N Y) 2019; 5: 705–16.Google Scholar
Ritchie, CW, Molinuevo, JL, Truyen, L, et al. Development of interventions for the secondary prevention of Alzheimer’s dementia: the European Prevention of Alzheimer’s Dementia (EPAD) project. Lancet Psychiatry 2016; 3: 179–86.Google Scholar
Vermunt, L, Veal, CD, Ter Meulen, L, et al. European Prevention of Alzheimer’s Dementia Registry: recruitment and prescreening approach for a longitudinal cohort and prevention trials. Alzheimers Dement 2018; 14: 837–42.Google Scholar
Gregory, S, Wells, K, Forysth, K, et al. Research participants as collaborators: background, experience and policies from the PREVENT Dementia and EPAD programmes. Dementia (London) 2018; 17: 1045–54.Google ScholarPubMed
Romero, K, de Mars, M, Frank, D, et al. The Coalition Against Major Diseases: developing tools for an integrated drug development process for Alzheimer’s and Parkinson’s diseases. Clin Pharmacol Ther 2009; 86: 365–7.CrossRefGoogle ScholarPubMed
Romero, K, Ito, K, Rogers, JA, et al. The future is now: model-based clinical trial design for Alzheimer’s disease. Clin Pharmacol Ther 2015; 97: 210–14.Google Scholar
Cummings, J, Lee, G, Ritter, A, Sabbagh M, Zhong K. Alzheimer’s disease drug development pipeline: 2020. Alzheimers Dement (N Y) 2020; 6: e12050.Google Scholar
Aisen, P, Sperling, R, Cummings, J, et al. The Trial-Ready Cohort for Preclinical/Prodromal Alzheimer’s Disease (TRC-PAD) project: an overview. J Prev Alzheimers Dis 2020; 7: 208–12.Google Scholar
Cummings, J, Aisen, P, Barton, R, et al. Re-engineering Alzheimer clinical trials: Global Alzheimer’s Platform network. J Prev Alzheimers Dis 2016; 3: 114–20.Google ScholarPubMed
Lamberti, MJ, Wilkinson, M, Harper, B, et al. Assessing study start-up practices, performance, and perceptions among sponsors and contract research organizations. Ther Innov Regul Sci 2018; 52: 572–8.Google Scholar
Drabu, S, Gupta, A, Bhadauria, A. Emerging trends in contract research industry in India. Contemp Clin Trials 2010; 31: 419–22.Google Scholar
Jack, CR, Jr., Albert, MS, Knopman, DS, et al. Introduction to the recommendations from the National Institute on Aging–Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 2011; 7: 257–62.Google Scholar
Prina, AM, Mayston, R, Wu, YT, et al. A review of the 10/66 dementia research group. Soc Psychiatry Psychiatr Epidemiol 2019; 54: 110.CrossRefGoogle ScholarPubMed
Abdin, E, Vaingankar, JA, Picco, L, et al. Validation of the short version of the 10/66 dementia diagnosis in multiethnic Asian older adults in Singapore. BMC Geriatr 2017; 17: 94.Google Scholar
Stewart, R, Guerchet, M, Prince, M. Development of a brief assessment and algorithm for ascertaining dementia in low-income and middle-income countries: the 10/66 short dementia diagnostic schedule. BMJ Open 2016; 6: e010712.Google Scholar
Winblad, B, Amouyel, P, Andrieu, S, et al. Defeating Alzheimer’s disease and other dementias: a priority for European science and society. Lancet Neurol 2016; 15: 455532.Google Scholar
Georges, J, Jansen, S, Jackson, J, et al. Alzheimer’s disease in real life: the dementia carer’s survey. Int J Geriatr Psychiatry 2008; 23: 546–51.Google Scholar
Keller, K, Briggs, L, Riley, E. Alzheimer’s Disease: A Center for Strategic Philanthropy Giving Smarter Guide, 2018; Available at: https://milkeninstitute.org/sites/default/files/reports-pdf/FINAL-Alz-GSG2.pdf.Google Scholar
Hara, Y, McKeehan, N, Fillit, HM. Translating the biology of aging into novel therapeutics for Alzheimer disease. Neurology 2019; 92: 8493.CrossRefGoogle ScholarPubMed
Lopez, JC, Suojanen, C. Harnessing venture philanthropy to accelerate medical progress. Nat Rev Drug Discov 2019; 18: 809–10.CrossRefGoogle ScholarPubMed
Food and Drug Administration. Formal Meetings Between the FDA and Sponsors or Applicants of PDUFA Products: Guidance for Industry. US Department of Health and Human Services Food and Drug Administration. Center for Drug Evaluation and Research (CDER) Center for Biologics Evaluation and Research (CBER); 2017.Google Scholar
Orr, D, Baram-Tsabari, A, Landsman, K. Social media as a platform for health-related public debates and discussions: the polio vaccine on Facebook. Isr J Health Policy Res 2016; 5: 34.CrossRefGoogle ScholarPubMed
Kravitz, RL, Bell, RA. Media, messages, and medication: strategies to reconcile what patients hear, what they want, and what they need from medications. BMC Med Inform Decis Mak 2013; 13: S5.Google Scholar
Schulz, KF, Altman, DG, Moher, D, et al. CONSORT 2010 statement: updated guidelines for reporting parallel group randomized trials. Ann Intern Med 2010; 152: 726–32.Google Scholar
Galkina Cleary, E, Beierlein, JM, Khanuja, NS, et al. Contribution of NIH funding to new drug approvals 2010–2016. Proc Natl Acad Sci USA 2018; 115: 2329–34.Google Scholar
Kosik, KS, Sejnowski, TJ, Raichle, ME, et al. A path toward understanding neurodegeneration. Science 2016; 353: 872–3.Google Scholar
Saville, BR, Berry, SM. Efficiencies of platform clinical trials: a vision of the future. Clin Trials 2016; 13: 358–66.Google Scholar
Adaptive Platform Trials C. Adaptive platform trials: definition, design, conduct and reporting considerations. Nat Rev Drug Discov 2019; 18: 797807.Google Scholar
Kennedy, RE, Cutter, GR, Wang, G, et al. Challenging assumptions about African American participation in Alzheimer disease trials. Am J Geriatr Psychiatry 2017; 25: 1150–9.Google Scholar
Hall, AK, Mills, SL, Lund, PK. Clinician-investigator training and the need to pilot new approaches to recruiting and retaining this workforce. Acad Med 2017; 92: 1382–9.Google Scholar
Gehr, S, Garner, CC, Kleinhans, KN. Translating academic careers into industry healthcare professions. Nat Biotechnol 2020; 38: 758–63.Google Scholar
Thornicroft, G, Lempp, H, Tansella, M. The place of implementation science in the translational medicine continuum. Psychol Med 2011; 41: 2015–21.Google Scholar
Fort, DG, Herr, TM, Shaw, PL, et al. Mapping the evolving definitions of translational research. J Clin Transl Sci 2017; 1: 60–6.Google Scholar
Dilworth-Anderson, P. Introduction to the science of recruitment and retention among ethnically diverse populations. Gerontologist 2011; 51: S14.Google Scholar
Bauer, MS, Kirchner, J. Implementation science: what is it and why should I care? Psychiatry Res 2020; 283: 112376.Google Scholar
Sheeran, P, Klein, WM, Rothman, AJ. Health behavior change: moving from observation to intervention. Annu Rev Psychol 2017; 68: 573600.Google Scholar
Rouse, R, Zineh, I, Strauss, DG. Regulatory science: an underappreciated component of translational research. Trends Pharmacol Sci 2018; 39: 225–9.Google Scholar

References

Newton, RD. The identity of Alzheimer’s disease and senile dementia and their relationship to senility. J Ment Sci 1948; 94: 225–49.Google Scholar
Neumann, MA, Cohn, R. Incidence of Alzheimer’s disease in large mental hospital; relation to senile psychosis and psychosis with cerebral arteriosclerosis. AMA Arch Neurol Psychiatry 1953; 69: 615–36.Google Scholar
Roth, M, Tomlinson, BE, Blessed, G. Correlation between scores for dementia and counts of ‘senile plaques’ in cerebral grey matter of elderly subjects. Nature 1966; 209: 109–10.Google Scholar
Tomlinson, BE, Blessed, G, Roth, M. Observations on the brains of demented old people. J Neurol Sci 1970; 11: 205–42.Google Scholar
Tomlinson, BE, Blessed, G, Roth, M. Observations on the brains of non-demented old people. J Neurol Sci 1968; 7: 331–56.Google Scholar
Terry, RD, Gonatas, NK, Weiss, M. The ultrastructure of the cerebral cortex in Alzheimer’s disease. Trans Am Neurol Assoc 1964; 89: 12.Google Scholar
Katzman, R. Editorial: The prevalence and malignancy of Alzheimer disease. A major killer. Arch Neurol 1976; 33: 217–18.Google Scholar
Davies, P, Maloney, AJ. Selective loss of central cholinergic neurons in Alzheimer’s disease. Lancet 1976; 2: 1403.Google Scholar
Bowen, DM. Biochemistry of dementias. Proc R Soc Med 1977; 70: 351–3.Google Scholar
Whitehouse, PJ, Price, DL, Clark, AW, Coyle, JT, DeLong, MR. Alzheimer disease: evidence for selective loss of cholinergic neurons in the nucleus basalis. Ann Neurol 1981; 10: 122–6.Google Scholar
Summers, WK, Majovski, LV, Marsh, GM, Tachiki, K, Kling, A. Oral tetrahydroaminoacridine in long-term treatment of senile dementia, Alzheimer type. N Engl J Med 1986; 315: 1241–5.Google Scholar
Atri, A. Current and future treatments in Alzheimer’s disease. Semin Neurol 2019; 39: 227–40.Google Scholar
Leber, P. Guidelines for the Clinical Evaluation of Antidementia Drugs. First draft. Technical Report. FDA Neuro-Pharm Group; 1990.Google Scholar
Folstein, MF, Folstein, SE, McHugh, PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12: 189–98.Google Scholar
Guy, W. Clinical Global Impressions. ECDEU Assessment Manual for Psychopharmacology – Revised. Rockville, MD: US Department of Health, Education, and Welfare, Public Health Service, Alcohol, Drug Abuse, and Mental Health Administration, National Institute of Mental Health, Psychopharmacology Research Branch, Division of Extramural Research Programs; 1976: 218–22.Google Scholar
Rosen, WG, Mohs, RC, Davis, KL. A new rating scale for Alzheimer’s disease. Am J Psychiatry 1984; 141: 1356–64.Google Scholar
Farlow, M, Gracon, SI, Hershey, LA, et al. A controlled trial of tacrine in Alzheimer’s disease. The Tacrine Study Group. JAMA 1992; 268: 2523–9.Google Scholar
Davis, KL, Thal, LJ, Gamzu, ER, et al. A double-blind, placebo-controlled multicenter study of tacrine for Alzheimer’s disease. The Tacrine Collaborative Study Group. N Engl J Med 1992; 327: 1253–9.Google Scholar
Food and Drug Administration. Early Alzheimer’s Disease: Developing Drugs for Treatment. Guidance for Industry. US Department of Health and Human Services Food and Drug Administration Center for Drug Evaluation and Research (CDER) Center for Biologics Evaluation and Research (CBER); 2018.Google Scholar
Glenner, GG, Wong, CW. Alzheimer’s disease: initial report of the purification and characterization of a novel cerebrovascular amyloid protein. Biochem Biophys Res Commun 1984; 120: 885–90.Google Scholar
Glenner, GG. Alzheimer’s disease. The commonest form of amyloidosis. Arch Pathol Lab Med 1983; 107: 281–2.Google Scholar
Grundke-Iqbal, I, Iqbal, K, Quinlan, M, et al. Microtubule-associated protein tau. A component of Alzheimer paired helical filaments. J Biol Chem 1986; 261: 6084–9.Google Scholar
Hardy, J, Selkoe, DJ. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science 2002; 297: 353–6.Google Scholar
Schenk, D, Barbour, R, Dunn, W, et al. Immunization with amyloid-beta attenuates Alzheimer-disease-like pathology in the PDAPP mouse. Nature 1999; 400: 173–7.Google Scholar
Gilman, S, Koller, M, Black, RS, et al. Clinical effects of Abeta immunization (AN1792) in patients with AD in an interrupted trial. Neurology 2005; 64: 1553–62.Google Scholar
Holmes, C, Boche, D, Wilkinson, D, et al. Long-term effects of Abeta42 immunisation in Alzheimer’s disease: follow-up of a randomised, placebo-controlled phase I trial. Lancet 2008; 372: 216–23.Google Scholar
Salloway, S, Sperling, R, Fox, NC, et al. Two phase 3 trials of bapineuzumab in mild-to-moderate Alzheimer’s disease. N Engl J Med 2014; 370: 322–33.Google Scholar
Salloway, S, Sperling, R, Gilman, S, et al. A phase 2 multiple ascending dose trial of bapineuzumab in mild to moderate Alzheimer disease. Neurology 2009; 73: 2061–70.Google Scholar
Doody, RS, Farlow, M, Aisen, PS, et al. Phase 3 trials of solanezumab for mild-to-moderate Alzheimer’s disease. N Engl J Med 2014; 370: 311–21.Google Scholar
Bullain, S, Doody, R. What works and what does not work in Alzheimer’s disease? From interventions on risk factors to anti-amyloid trials. J Neurochem 2020; 155: https://doi.org/10.1111/jnc.15023.Google Scholar
van Dyck, CH. Anti-amyloid-β monoclonal antibodies for Alzheimer’s disease: pitfalls and promise. Psychiatry 2018; 83: 311–19.Google Scholar
Green, RC, Schneider, LS, Amato, DA, et al. Effect of tarenflurbil on cognitive decline and activities of daily living in patients with mild Alzheimer disease: a randomized controlled trial. JAMA 2009; 302: 2557–64.Google Scholar
Imbimbo, BP. Why did tarenflurbil fail in Alzheimer’s disease? J Alzheimers Dis 2009; 17: 757–60.Google Scholar
Doody, RS, Raman, R, Farlow, M, et al. A phase 3 trial of semagacestat for treatment of Alzheimer’s disease. N Engl J Med 2013; 369: 341–50.Google Scholar
Egan, MF, Kost, J, Voss, T, et al. Randomized trial of verubecestat for prodromal Alzheimer’s disease. N Engl J Med 2019; 380: 1408–20.Google Scholar
Hara, Y, McKeehan, N, Fillit, HM. Translating the biology of aging into novel therapeutics for Alzheimer disease. Neurology 2019; 92: 8493.Google Scholar
Clark, CM, Pontecorvo, MJ, Beach, TG, et al. Cerebral PET with florbetapir compared with neuropathology at autopsy for detection of neuritic amyloid-beta plaques: a prospective cohort study. Lancet Neurol 2012; 11: 669–78.Google Scholar
McNamee, LM, Walsh, MJ, Ledley, FD. Timelines of translational science: from technology initiation to FDA approval. PLoS One 2017; 12: e0177371.Google Scholar
Endo, A. A historical perspective on the discovery of statins. Proc Jpn Acad Ser B Phys Biol Sci 2010; 86: 484–93.Google Scholar
Qaseem, A, Snow, V, Cross, TJ Jr., et al. Current pharmacologic treatment of dementia: a clinical practice guideline from the American College of Physicians and the American Academy of Family Physicians. Ann Intern Med 2008; 148: 370–8.Google Scholar
Cummings, J, Ritter, A, Zhong, K. Clinical trials for disease-modifying therapies in Alzheimer’s disease: a primer, lessons learned, and a blueprint for the future. J Alzheimers Dis 2018; 64: S322.Google Scholar
Cummings, J. Lessons learned from Alzheimer disease: clinical trials with negative outcomes. Clin Transl Sci 2018; 11: 147–52.Google Scholar
Cummings, J, Lee, G, Ritter, A, Sabbagh M, Zhong K. Alzheimer’s disease drug development pipeline: 2020. Alzheimers Dement (N Y) 2020; 6: e12050.Google Scholar
Cummings, J, Blennow, K, Johnson, K, et al. Anti-tau trials for Alzheimer’s disease: a report from the EU/US/CTAD Task Force. J Prev Alzheimers Dis 2019; 6: 157–63.Google Scholar
Heneka, MT, Carson, MJ, El Khoury, J, et al. Neuroinflammation in Alzheimer’s disease. Lancet Neurol 2015; 14: 388405.Google Scholar
Miguel-Alvarez, M, Santos-Lozano, A, Sanchis-Gomar, F, et al. Non-steroidal anti-inflammatory drugs as a treatment for Alzheimer’s disease: a systematic review and meta-analysis of treatment effect. Drugs Aging 2015; 32: 139–47.Google Scholar
Hampel, H, Caraci, F, Cuello, AC, et al. A path toward precision medicine for neuroinflammatory mechanisms in Alzheimer’s disease. Front Immunol 2020; 11: 456.Google Scholar
Wang, X, Sun, G, Geng, M. Sodium oligomannate therapeutically remodels gut microbiota and suppresses gut bacterial amino acids: shaped neuroinflammation to inhibit Alzheimer’s disease progression. Cell Res 2019; 29: 787803.Google Scholar
Xia, C, Dickerson, BC. Multimodal PET imaging of amyloid and tau pathology in Alzheimer disease and non-Alzheimer disease dementias. PET Clin 2017; 12: 351–9.Google Scholar
Risacher, SL, Saykin, AJ. Neuroimaging in aging and neurologic diseases. Handb Clin Neurol 2019; 167: 191227.Google Scholar
Sevigny, J, Suhy, J, Chiao, P, et al. Amyloid PET screening for enrichment of early-stage Alzheimer disease clinical trials: experience in a phase 1b clinical trial. Alzheimer Dis Assoc Disord 2016; 30: 17.Google Scholar
Sevigny, J, Chiao, P, Bussière, T, et al. The antibody aducanumab reduces Abeta plaques in Alzheimer’s disease. Nature 2016; 537: 50–6.Google Scholar
Schindler, SE, Bollinger, JG, Ovod, V, et al. High-precision plasma beta-amyloid 42/40 predicts current and future brain amyloidosis. Neurology 2019; 93: e164759.Google Scholar
Barthelemy, NR, Bateman, RJ, Hirtz, C, et al. Cerebrospinal fluid phospho-tau T217 outperforms T181 as a biomarker for the differential diagnosis of Alzheimer’s disease and PET amyloid-positive patient identification. Alzheimers Res Ther 2020; 12: 26.Google Scholar
Jack, CR, Jr., Bennett, DA, Blennow, K, et al. NIA–AA Research Framework: toward a biological definition of Alzheimer’s disease. Alzheimers Dement 2018; 14: 535–62.Google Scholar
Dhana, K, Evans, DA, Rajan, KB, Bennett, DA, Morris, MC. Healthy lifestyle and the risk of Alzheimer dementia: findings from 2 longitudinal studies. Neurology 2020; 95: e374–83.Google Scholar
Kivipelto, M, Ngandu, T. Good for the heart and good for the brain? Lancet Neurol 2019; 18: 327–8.Google Scholar
Andrieu, S, Coley, N, Lovestone, S, Aisen, PS, Bruno Vellas, B. Prevention of sporadic Alzheimer’s disease: lessons learned from clinical trials and future directions. Lancet Neurol 2015; 14: 926–44.Google Scholar
Lopez Lopez, C, Tariot, PN, Caputo, A, et al. The Alzheimer’s Prevention Initiative Generation Program: study design of two randomized controlled trials for individuals at risk for clinical onset of Alzheimer’s disease. Alzheimers Dement (N Y) 2019; 5: 216–27.Google Scholar
Alzheimer’s Association. Changing the Trajectory of Alzheimer’s Disease: How a treatment by 2025 Saves Lives and Dollars. Chicago, IL: Alzheimer’s Association; 2015.Google Scholar

References

Cacace, R, Sleegers, K, Van Broeckhoven, C. Molecular genetics of early-onset Alzheimer’s disease revisited. Alzheimers Dement 2016; 12: 733–48.Google Scholar
Joe, E, Ringman, JM. Cognitive symptoms of Alzheimer’s disease: clinical management and prevention. BMJ 2019; 367: l6217.Google Scholar
Cummings, J, Lee, G, Ritter, A, Sabbagh, M, Zhong, K. Alzheimer’s disease drug development pipeline: 2019. Alzheimers Dement (N Y) 2019; 5: 272–93.Google Scholar
Hardy, J. The discovery of Alzheimer-causing mutations in the APP gene and the formulation of the “amyloid cascade hypothesis”. FEBS J 2017; 284: 1040–4.Google Scholar
George-Hyslop, PH, Petit, A. Molecular biology and genetics of Alzheimer’s disease. CR Biol 2005; 328: 119–30.Google Scholar
Jack, CR, Jr., Knopman, DS, Jagust, WJ, et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol 2013; 12: 207–16.Google Scholar
McDade, E, Wang, G, Gordon, BA, et al. Longitudinal cognitive and biomarker changes in dominantly inherited Alzheimer disease. Neurology 2018; 91: e1295–306.Google Scholar
Khanna, MR, Kovalevich, J, Lee, VM, Trojanowski, JQ, Brunden, KR. Therapeutic strategies for the treatment of tauopathies: hopes and challenges. Alzheimers Dement 2016; 12: 1051–65.Google Scholar
Arriagada, PV, Growdon, JH, Hedleywhyte, ET, Hyman, BT. Neurofibrillary tangles but not senile plaques parallel duration and severity of Alzheimers disease. Neurology 1992; 42: 631–9.Google Scholar
Teng, E, Ward, M, Manser, PT, et al. Cross-sectional associations between [(18)F]GTP1 tau PET and cognition in Alzheimer’s disease. Neurobiol Aging 2019; 81: 138–45.Google Scholar
Malik, M, Parikh, I, Vasquez, JB, et al. Genetics ignite focus on microglial inflammation in Alzheimer’s disease. Mol Neurodegener 2015; 10: 52.Google Scholar
Taniguchi, S, Suzuki, N, Masuda, M, et al. Inhibition of heparin-induced tau filament formation by phenothiazines, polyphenols, and porphyrins. J Biol Chem 2005; 280: 7614–23.Google Scholar
Honson, NS, Johnson, RL, Huang, WW, et al. Differentiating Alzheimer disease-associated aggregates with small molecules. Neurobiol Dis 2007; 28: 251–60.Google Scholar
Crowe, A, Ballatore, C, Hyde, E, Trojanowski, JQ, Lee, VMY. High throughput screening for small molecule inhibitors of heparin-induced tau fibril formation. Biochem Biophys Res Commun 2007; 358: 16.Google Scholar
Crowe, A, Huang, W, Ballatore, C, et al. The identification of aminothienopyridazine inhibitors of tau assembly by quantitative high-throughput screening. Biochemistry 2009; 48: 7732–45.Google Scholar
Pickhardt, M, Gazova, Z, von Bergen, M, et al. Anthraquinones inhibit tau aggregation and dissolve Alzheimer’s paired helical filaments in vitro and in cells. J Biol Chem 2005; 280: 3628–35.Google Scholar
Crowe, A, James, MJ, Lee, VM, et al. Aminothienopyridazines and methylene blue affect tau fibrillization via cysteine oxidation. J Biol Chem 2013; 288: 11024–37.Google Scholar
Pickhardt, M, Tassoni, M, Denner, P, et al. Screening of a neuronal cell model of tau pathology for therapeutic compounds. Neurobiol Aging 2019; 76: 2434.Google Scholar
Khlistunova, I, Biernat, J, Wang, YP, et al. Inducible expression of tau repeat domain in cell models of tauopathy: aggregation is toxic to cells but can be reversed by inhibitor drugs. J Biol Chem 2006; 281: 1205–14.Google Scholar
Crowe, A, Henderson, MJ, Anderson, J, et al. Compound screening in cell-based models of tau inclusion formation: comparison of primary neuron and HEK293 cell assays. J Biol Chem 2020; 295: 4001–13.Google Scholar
Guo, JL, Narasimhan, S, Changolkar, L, et al. Unique pathological tau conformers from Alzheimer’s brains transmit tau pathology in nontransgenic mice. J Exp Med 2016; 213: 2635–54.Google Scholar
McCormick, AV, Wheeler, JM, Guthrie, CR, Liachko, NF, Kraemer, BC. Dopamine D2 receptor antagonism suppresses tau aggregation and neurotoxicity. Biol Psychiatry 2013; 73: 464–71.Google Scholar
Kow, RL, Sikkema, C, Wheeler, JM, et al. DOPA decarboxylase modulates tau toxicity. Biol Psychiatry 2018; 83: 438–46.Google Scholar
Ballatore, C, Lee, VMY, Trojanowski, JQ. Tau-mediated neurodegeneration in Alzheimer’s disease and related disorders. Nat Rev Neurosci 2007; 8: 663–72.Google Scholar
Tell, V, Hilgeroth, A. Recent developments of protein kinase inhibitors as potential AD therapeutics. Front Cell Neurosci 2013; 7:189.Google Scholar
Martin, L, Latypova, X, Wilson, CM, et al. Tau protein kinases: involvement in Alzheimer’s disease. Ageing Res Rev 2013; 12: 289309.Google Scholar
Zeb, A, Son, M, Yoon, S, et al. Computational simulations identified two candidate inhibitors of CDK5/p25 to abrogate tau-associated neurological disorders. Comput Struct Biotechnol J 2019; 17: 579–90.Google Scholar
Shukla, R, Munjal, NS, Singh, TR. Identification of novel small molecules against GSK3beta for Alzheimer’s disease using chemoinformatics approach. J Mol Graph Model 2019; 91: 91104.Google Scholar
Lin, CH, Hsieh, YS, Wu, YR, et al. Identifying GSK-3beta kinase inhibitors of Alzheimer’s disease: virtual screening, enzyme, and cell assays. Eur J Pharm Sci 2016; 89: 11–19.Google Scholar
Bhat, RV, Andersson, U, Andersson, S, et al. The conundrum of GSK3 inhibitors: is it the dawn of a new beginning? J Alzheimers Dis 2018; 64: S547–54.Google Scholar
Dehdashti, SJ, Zheng, W, Gever, JR, et al. A high-throughput screening assay for determining cellular levels of total tau protein. Curr Alzheimer Res 2013; 10: 679–87.Google Scholar
Wang, C, Ward, ME, Chen, R, et al. Scalable production of iPSC-derived human neurons to identify tau-lowering compounds by high-content screening. Stem Cell Reports 2017; 9: 1221–33.Google Scholar
Silva, MC, Nandi, GA, Tentarelli, S, et al. Prolonged tau clearance and stress vulnerability rescue by pharmacological activation of autophagy in tauopathy neurons. Nat Commun 2020; 11: 3258.Google Scholar
Coussens, NP, Sittampalam, GS, Guha, R, et al. Assay Guidance Manual: quantitative biology and pharmacology in preclinical drug discovery. Clin Transl Sci 2018; 11: 461–70.Google Scholar
Zhang, JH, Chung, TDY, Oldenburg, KR. A simple statistical parameter for use in evaluation and validation of high throughput screening assays. J Biomol Screen 1999; 4: 6773.Google Scholar
Dandapani, S, Rosse, G, Southall, N, Salvino, JM, Thomas, CJ. Selecting, acquiring, and using small molecule libraries for high-throughput screening. Curr Protocol Chem Biol 2012; 4: 177–91.Google Scholar
Caldwell, GW. In silico tools used for compound selection during target-based drug discovery and development. Expert Opin Drug Discov 2015; 10: 901–23.Google Scholar
Pardridge, WM. The blood–brain barrier: bottleneck in brain drug development. NeuroRx 2005; 2: 314.Google Scholar
Hitchcock, SA. Blood–brain barrier permeability considerations for CNS-targeted compound library design. Curr Opin Chem Biol 2008; 12: 318–23.Google Scholar
Lipinski, CA, Lombardo, F, Dominy, BW, Feeney, PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliver Rev 1997; 23: 325.Google Scholar
Dahlin, JL, Nissink, JW, Strasser, JM, et al. PAINS in the assay: chemical mechanisms of assay interference and promiscuous enzymatic inhibition observed during a sulfhydryl-scavenging HTS. J Med Chem 2015; 58: 2091–113.Google Scholar
Bruns, RF, Watson, IA. Rules for identifying potentially reactive or promiscuous compounds. J Med Chem 2012; 55: 9763–72.Google Scholar
Wager, TT, Hou, X, Verhoest, PR, Villalobos, A. Central nervous system multiparameter optimization desirability: application in drug discovery. ACS Chem Neurosci 2016; 7: 767–75.Google Scholar
Hopkins, AL, Keseru, GM, Leeson, PD, Rees, DC, Reynolds, CH. The role of ligand efficiency metrics in drug discovery. Nat Rev Drug Discov 2014; 13: 105–21.Google Scholar
Meanwell, NA. Improving drug design: an update on recent applications of efficiency metrics, strategies for replacing problematic elements, and compounds in nontraditional drug space. Chem Res Toxicol 2016; 29: 564616.Google Scholar
Dimitriadi, M, Hart, AC. Neurodegenerative disorders: insights from the nematode Caenorhabditis elegans. Neurobiol Dis 2010; 40: 411.Google Scholar
McGurk, L, Berson, A, Bonini, NM. Drosophila as an in vivo model for human neurodegenerative disease. Genetics 2015; 201: 377402.Google Scholar
Bicker, J, Alves, G, Fortuna, A, Falcao, A. Blood–brain barrier models and their relevance for a successful development of CNS drug delivery systems: a review. Eur J Pharm Biopharm 2014; 87: 409–32.Google Scholar
Kovalevich, J, Cornec, AS, Yao, Y, et al. Characterization of brain-penetrant pyrimidine-containing molecules with differential microtubule-stabilizing activities developed as potential therapeutic agents for Alzheimer’s disease and related tauopathies. J Pharmacol Exp Ther 2016; 357: 432–50.Google Scholar
Di, L, Umland, JP, Chang, G, et al. Species independence in brain tissue binding using brain homogenates. Drug Metab Dispos 2011; 39: 1270–7.Google Scholar
Di, L, Rong, H, Feng, B. Demystifying brain penetration in central nervous system drug discovery. Miniperspective. J Med Chem 2013; 56: 212.Google Scholar
Benet, LZ, Zia-Amirhosseini, P. Basic principles of pharmacokinetics. Toxicol Pathol 1995; 23: 115–23.Google Scholar
Gaskill, BN, Garner, JP. Power to the people: power, negative results and sample size. J Am Assoc Lab Anim Sci 2020; 59: 916.Google Scholar
Snyder, HM, Shineman, DW, Friedman, LG, et al. Guidelines to improve animal study design and reproducibility for Alzheimer’s disease and related dementias: for funders and researchers. Alzheimers Dement 2016; 12: 1177–85.Google Scholar
Guo, JL, Buist, A, Soares, A, et al. The dynamics and turnover of tau aggregates in cultured cells: insights into therapies for tauopathies. J Biol Chem 2016; 291: 13175–93.Google Scholar
Sankaranarayanan, S, Barten, DM, Vana, L, et al. Passive immunization with phospho-tau antibodies reduces tau pathology and functional deficits in two distinct mouse tauopathy models. PLoS One 2015; 10: e0125614.Google Scholar
He, Z, Guo, JL, McBride, JD, et al. Amyloid-beta plaques enhance Alzheimer’s brain tau-seeded pathologies by facilitating neuritic plaque tau aggregation. Nat Med 2018; 24: 2938.Google Scholar
Sopko, R, Golonzhka, O, Arndt, J, et al. Characterization of tau binding by gosuranemab. Neurobiol Dis 2020; 146: 105120.Google Scholar

References

Gardner, RC, Valcour, V, Yaffe, K. Dementia in the oldest old: a multi-factorial and growing public health issue. Alzheimers Res Ther 2013; 5: 27.Google Scholar
Corrada, MM, Berlau, DJ, Kawas, CH. A population-based clinicopathological study in the oldest-old: the 90+ study. Curr Alzheimer Res 2012; 9: 709–17.Google Scholar
Alzheimer, A. Über eine eigenartige Erkrankung der Hirnrinde. Allg Z Psychiat 1907; 64: 146–8.Google Scholar
Fischer, O. Miliare Nekrosen mit drusigen Wucherungen der Neurofibrillen, eine regelmässige Veränderung der Hirnrinde bei seniler Demenz. Monatsschr Psychiatr Neurol 1907; 22: 361–72.Google Scholar
Cummings, JL, Morstorf, T, Zhong, K. Alzheimer’s disease drug-development pipeline: few candidates, frequent failures. Alzheimers Res Ther 2014; 6: 37.Google Scholar
Allgaier, M, Allgaier, C. An update on drug treatment options of Alzheimer’s disease. Front Biosci 2014; 19: 1345–54.Google Scholar
Braak, H, Braak, E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol 1991; 82: 239–59.Google Scholar
Mirra, SS, Heyman, A, McKeel, D, et al. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part II. Standardization of the neuropathologic assessment of Alzheimer’s disease. Neurology 1991; 41: 479–86.Google Scholar
Haroutunian, V, Schnaider-Beeri, M, Schmeidler, J, et al. Role of the neuropathology of Alzheimer disease in dementia in the oldest-old. Arch Neurol 2008; 65: 1211–17.Google Scholar
Boyle, PA, Yu, L, Wilson, RS, et al. Person-specific contribution of neuropathologies to cognitive loss in old age. Ann Neurol 2018; 83: 7483.Google Scholar
Voorhees, JR, Remy, MT, McDaniel, LM, et al. P7C3 compounds protect a rat model of Alzheimer’s disease from cognitive decline, depressive-like behavior, and neuronal cell death without affecting neuroinflammation or amyloid–tau pathology. Biol Psychiatry 2018; 84: 488–98.Google Scholar
DiMasi, JA, Grabowski, HG, Hansen, RW. Innovation in the pharmaceutical industry: new estimates of R&D costs. J Health Econ 2016; 47: 2033.Google Scholar
Conley, A, Key, A, Blackford, J, et al. Functional activity of the muscarinic positive allosteric modulator VU319 during a Phase 1 single ascending dose study. Am J Geriatr Psychiatry 2020; 28: S114–15.Google Scholar

References

Ballard, C, Aarsland, D, Cummings, J, et al. Drug repositioning and repurposing for Alzheimer disease. Nat Rev Neurol 2020; 16: 661–73.Google Scholar
Corbett, A, Pickett, J, Burns, A, et al. Drug repositioning for Alzheimer’s disease. Nat Rev Drug Discov 2012; 11: 833–46.Google Scholar
Hou, Y, Zhou, L, Yang, QD, et al. Changes in hippocampal synapses and learning-memory abilities in a streptozotocin treated rat model and intervention by using fasudil hydrochloride. Neuroscience 2012; 200: 120–9.Google Scholar
Rush, T, Martinez-Hernandez, J, Dollmeyer, M, et al. Synaptotoxicity in Alzheimer’s disease involved a dysregulation of actin cytoskeleton dynamics through cofilin 1 phosphorylation. J Neurosci 2018; 38: 10349–61.Google Scholar
Yu, JZ, Li, YH, Liu, CY, et al. Multitarget therapeutic effect of fasudil in APP/PS1transgenic mice. CNS Neurol Disord Drug Targets 2017; 16: 199209.Google Scholar
Hamano, T, Shirafuji, N, Yen, SH, et al. Rho-kinase ROCK inhibitors reduce oligomeric tau protein. Neurobiol Aging 2020; 89: 4154.Google Scholar
Zhang, X, Ye, P, Wang, D, et al. Involvement of RhoA/ROCK signaling in Aβ-induced chemotaxis, cytotoxicity and inflammatory response of microglial BV2 cells. Cell Mol Neurobiol 2019; 39: 637–50.Google Scholar
Chen, J, Sun, Z, Jin, M, et al. Inhibition of AGEs/RAGE/Rho/ROCK pathway suppresses non-specific neuroinflammation by regulating BV2 microglial M1/M2 polarization through the NF-κB pathway. J Neuroimmunol 2017; 305: 108–14.Google Scholar
Elliott, C, Rojo, AI, Ribe, E, et al. A role for APP in Wnt signalling links synapse loss with β-amyloid production. Transl Psychiatry 2018; 8: 179.Google Scholar
Guo, MF, Zhang, HY, Li, YH, et al. Fasudil inhibits the activation of microglia and astrocytes of transgenic Alzheimer’s disease mice via the downregulation of TLR4/Myd88/NF-κB pathway. J Neuroimmunol 2020; 346: 577284.Google Scholar
Vicari, RM, Chaitman, B, Keefe, D, et al.; Fasudil study group. Efficacy and safety of fasudil in patients with stable angina: a double-blind, placebo-controlled, phase 2 trial. J Am Coll Cardiol 2005; 46: 1803–11.Google Scholar
Kamei, S, Oishi, M, Takasu, T. Evaluation of fasudil hydrochloride treatment for wandering symptoms in cerebrovascular dementia with 31P-magnetic resonance spectroscopy and Xe-computed tomography. Clin Neuropharmacol 1996; 19: 428–38.Google Scholar
Fukumoto, Y, Yamada, N, Matsubara, H, et al. Double-blind, placebo-controlled clinical trial with a rho-kinase inhibitor in pulmonary arterial hypertension. Circ J 2013; 77: 2619–25.Google Scholar
Yan, B, Sun, F, Duan, L, et al. Curative effect of fasudil injection combined with nimodipine on Alzheimer disease of elderly patients. J Clin Med Pract 2011; 14: 36.Google Scholar
Winblad, B. Giacobini, E. Frölich, L. et al. Phenserine efficacy in Alzheimer’s disease. J Alzheimers Dis 2010; 22: 1201–8.Google Scholar
Lahiri, DK, Alley, GM, Tweedie, D, et al. Differential effects of two hexahydropyrroloindole carbamate-based anticholinesterase drugs on the amyloid beta protein pathway involved in Alzheimer’s disease. Neuromol Med 2007; 9: 157–68.Google Scholar
Tabrez, S, Damanhouri, GA. Computational and kinetic studies of acetylcholine esterase inhibition by phenserine. Curr Pharm Des 2019; 25: 2108–12.Google Scholar
Lilja, AM, Röjdner, J, Mustafiz, T, et al. Age-dependent neuroplasticity mechanisms in Alzheimer Tg2576 mice following modulation of brain amyloid-β levels. PLoS One 2013; 8: e58752.Google Scholar
Lilja, AM, Luo, Y, Yu, QS, et al. Neurotrophic and neuroprotective actions of (−)- and (+)-phenserine, candidate drugs for Alzheimer’s disease. PLoS One 2013; 8: e54887.Google Scholar
Sugaya, K, Kwak, YD, Ohmitsu, O, et al. Practical issues in stem cell therapy for Alzheimer’s disease. Curr Alzheimer Res 2007; 4: 370–7.Google Scholar
Greig, NH, Sambamurti, K, Yu, QS, et al. An overview of phenserine tartrate, a novel acetylcholinesterase inhibitor for the treatment of Alzheimer’s disease. Curr Alzheimer Res 2005; 2: 281–90.Google Scholar
Schneider, LS, Lahiri, DK. The perils of Alzheimer’s drug development. Curr Alzheimer Res 2009; 6: 77–8.Google Scholar
Powell-Doherty, RD, Abbott, ARN, Nelson, LA, Bertke, AS. Amyloid-β and p-tau anti-threat response to herpes simplex virus 1 infection in primary adult murine hippocampal neurons. J Virol 2020; 94: e01874–19.Google Scholar
Wozniak, MA, Frost, AL, Preston, CM, Itzhaki, RF. Antivirals reduce the formation of key Alzheimer’s disease molecules in cell cultures acutely infected with herpes simplex virus type 1. PLoS One 2011; 6: e25152.Google Scholar
Tzeng, NS, Chung, CH, Lin, FH, et al. Anti-herpetic medications and reduced risk of dementia in patients with herpes simplex virus infections: a nationwide, population based cohort study in Taiwan. Neurotherapeutics 2008; 15: 417–29.Google Scholar
Chen, VC, Wu, SI, Huang, KY, et al. Herpes zoster and dementia: a nationwide population-based cohort study. J Clin Psychiatry 2018; 79: 16m11312;DOI: http://doi.org/10.4088/JCP.16m11312.Google Scholar
Bae, S, Yun, SC, Kim, MC, et al. Association of herpes zoster with dementia and effect of antiviral therapy on dementia: a population-based cohort study. Eur Arch Psychiatry Clin Neurosci 2020;DOI: http://doi.org/10.1007/s00406-020-01157-4.Google Scholar
Xu, W, Yang, Y, Yuan, G, et al. Exendin-4, a glucagon-like peptide-1 receptor agonist, reduces Alzheimer disease-associated tau hyperphosphorylation in the hippocampus of rats with type 2 diabetes. J Investig Med 2015; 63: 267–72.Google Scholar
Perry, T, Lahiri, DK, Sambamurti, K, et al. Glucagon-like peptide-1 decreases endogenous amyloid-beta peptide (Abeta) levels and protects hippocampal neurons from death induced by Abeta and iron. J Neurosci Res 2003; 72: 603–12.Google Scholar
Takach, O, Gill, TB, Silverman, MA. Modulation of insulin signaling rescues BDNF transport defects independent of tau in amyloid-β oligomer-treated hippocampal neurons. Neurobiol Aging 2015; 36: 1378–82.Google Scholar
Wang, X, Wang, L, Xu, Y, et al. Intranasal administration of exendin-4 antagonizes Aβ31-35-induced disruption of circadian rhythm and impairment of learning and memory. Aging Clin Exp Res 2016; 28: 1259–66.Google Scholar
Solmaz, V, Çınar, BP, Yiğittürk, G, et al. Exenatide reduces TNF-α expression and improves hippocampal neuron numbers and memory in streptozotocin treated rats. Eur J Pharmacol 2015; 765: 482–7.Google Scholar
Bomba, M, Ciavardelli, D, Silvestri, E, et al. Exenatide promotes cognitive enhancement and positive brain metabolic changes in PS1-KI mice but has no effects in 3×Tg-AD animals. Cell Death Dis 2013; 4: e612.Google Scholar
Long-Smith, CM, Manning, S, McClean, PL, et al. The diabetes drug liraglutide ameliorates aberrant insulin receptor localisation and signalling in parallel with decreasing both amyloid-β plaque and glial pathology in a mouse model of Alzheimer’s disease. Neuromol Med 2013; 15: 102–14.Google Scholar
Qi, L, Ke, L, Liu, X, et al. Subcutaneous administration of liraglutide ameliorates learning and memory impairment by modulating tau hyperphosphorylation via the glycogen synthase kinase-3β pathway in an amyloid β protein induced Alzheimer disease mouse model. Eur J Pharmacol 2016; 15: 2332.Google Scholar
Gejl, M, Brock, B, Egefjord, L, et al. Blood–brain glucose transfer in Alzheimer’s disease: effect of GLP-1 analog treatment. Sci Rep 2017; 7: 17490.Google Scholar
Edison, P, Femminella, G, Holmes, C, et al. Evaluation of liraglutide in treatment for Alzheimer’s disease. Clinical Trials in Alzheimer’s Disease (CTAD) Congress, November 4–7, 2020.Google Scholar
Mullins, RJ, Mustapic, M, Chia, CW, et al. A pilot study of exenatide actions in Alzheimer’s disease. Curr Alzheimer Res 2019; 16: 741–52.Google Scholar
Gerstein, HC, Colhoun, HM, Dagenais, GR, et al Dulaglutide and cardiovascular outcomes in type 2 diabetes (REWIND): a double-blind, randomised placebo-controlled trial. Lancet 2019; 394: 121–30.Google Scholar
Ballard, C, Nørgaard, CH, Friedrich, S, et al. Liraglutide and semaglutide: pooled post-hoc analysis to evaluate risk of dementia in patients with type 2 diabetes. Alzheimer’s Association International Conference, 2020.Google Scholar
Lamb, J, Crawford, ED, Peck, D, et al. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science 2006; 313: 1929–35.Google Scholar
Subramanian, A, Narayan, R, Corsello, SM, et al. A next generation connectivity map: L1000 platform and the first 1,000,000 profiles. Cell 2017; 171: 1437–52.Google Scholar
Williams, G. SPIEDw: a searchable platform-independent expression database web tool. BMC Genomics 2013; 14: 765.Google Scholar
Williams, G, Gatt, A, Clarke, E, et al. Drug repurposing for Alzheimer’s disease based on transcriptional profiling of human iPSC-derived cortical neurons. Transl Psychiatry 2019; 9: 220.Google Scholar
Bertram, L, Tanzi, RE. Alzheimer disease risk genes: 29 and counting. Nat Rev Neurol 2019; 15: 191–2.Google Scholar
Rothstein, JD, Patel, S, Regan, MR, et al. Beta-lactam antibiotics offer neuroprotection by increasing glutamate transporter expression. Nature 2005; 433: 73–7.Google Scholar
Cudkowicz, ME, Titus, S, Kearney, M, et al. Safety and efficacy of ceftriaxone for amyotrophic lateral sclerosis: a multi-stage, randomised, double-blind, placebo-controlled trial. Lancet Neurol 2014; 13: 1083–91.Google Scholar
Singleton, AB, Farrer, M, Johnson, J, et al. Alpha-synuclein locus triplication causes Parkinson’s disease. Science 2003; 302: 841.Google Scholar
Mittal, S, Bjørnevik, K, Im, DS, et al. β2-Adrenoreceptor is a regulator of the α-synuclein gene driving risk of Parkinson’s disease. Science 2017; 357: 891–8.Google Scholar

References

Hippius, H, Neundorfer, G. The discovery of Alzheimer’s disease. Dialogues Clin Neurosci 2003; 5: 101–8.Google Scholar
Corriveau, RA, Koroshetz, WJ, Gladman, JT, et al. Alzheimer’s Disease-Related Dementias Summit 2016: national research priorities. Neurology 2017; 89: 2381–91.Google Scholar
Alzheimer’s Association. 2016 Alzheimer’s disease facts and figures. Alzheimers Dement 2016; 12: 459509.Google Scholar
Alzheimer’s Association. 2020 Alzheimer’s disease facts and figures. Alzheimers Dement 2020; 17: 327406.Google Scholar
Cummings, JL, Morstorf, T, Zhong, K. Alzheimer’s disease drug-development pipeline: few candidates, frequent failures. Alzheimers Res Ther 2014; 6: 37.Google Scholar
Avorn, J. The $2.6 billion pill: methodologic and policy considerations. N Engl J Med 2015; 372: 1877–9.Google Scholar
Fleming, N. How artificial intelligence is changing drug discovery. Nature 2018; 557: S55–7.Google Scholar
Zhou, Y, Wang, F, Tang, J, et al. Artificial intelligence in COVID-19 drug repurposing. Lancet Digit Health 2020; 2: E667–76.Google Scholar
Vamathevan, J, Clark, D, Czodrowski, P, et al. Applications of machine learning in drug discovery and development. Nat Rev Drug Discov 2019; 18: 463–77.Google Scholar
Schneider, P, Walters, WP, Plowright, AT, et al. Rethinking drug design in the artificial intelligence era. Nat Rev Drug Discov 2020; 19: 353–64.Google Scholar
Beecham, GW, Bis, JC, Martin, ER, et al. The Alzheimer’s Disease Sequencing Project: study design and sample selection. Neurol Genet 2017; 3: e194.Google Scholar
Petersen, RC, Aisen, PS, Beckett, LA, et al. Alzheimer’s Disease Neuroimaging Initiative (ADNI): clinical characterization. Neurology 2010; 74: 201–9.Google Scholar
Wishart, DS, Feunang, YD, Guo, AC, et al. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res 2018; 46: D1074–82.Google Scholar
Ursu, O, Holmes, J, Knockel, J, et al. DrugCentral: online drug compendium. Nucleic Acids Res 2017; 45: D932–9.Google Scholar
Zhou, Y, Fang, J, Bekris, L, et al. AlzGPS: a genome-wide positioning systems platform to catalyze multi-omics for Alzheimer’s therapeutic discovery. Alzheimers Res Ther 2021; 13: 24.Google Scholar
O’Boyle, NM. Towards a universal SMILES representation: a standard method to generate canonical SMILES based on the InChI. J Cheminform 2012; 4: 22.Google Scholar
Lipinski, CA. Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov Today Technol 2004; 1: 337–41.Google Scholar
Rogers, D, Hahn, M. Extended-connectivity fingerprints. J Chem Inf Model 2010; 50: 742–54.Google Scholar
Jaeger, S, Fulle, S, Turk, S . Mol2vec: unsupervised machine learning approach with chemical intuition. J Chem Inf Model 2018; 58: 2735.Google Scholar
LeCun, Y, Bengio, Y, Hinton, G. Deep learning. Nature 2015; 521: 436–44.Google Scholar
Rumelhart, DE, Hinton, GE, Williams, RJ. Learning representations by back-propagating errors. Nature 1986; 323: 533–6.Google Scholar
Cai, C, Guo, P, Zhou, Y, et al. Deep learning-based prediction of drug-induced cardiotoxicity. J Chem Inf Model 2019; 59: 1073–84.Google Scholar
Wu, Z, Ramsundar, B, Feinberg, EN, et al. MoleculeNet: a benchmark for molecular machine learning. Chem Sci 2018; 9: 513–30.Google Scholar
Pardridge, WM. Alzheimer’s disease drug development and the problem of the blood–brain barrier. Alzheimers Dement 2009; 5: 427–32.Google Scholar
Cheng, F, Li, W, Liu, G, et al. In silico ADMET prediction: recent advances, current challenges and future trends. Curr Top Med Chem 2013; 13: 1273–89.Google Scholar
Shen, J, Cheng, F, Xu, Y, et al. Estimation of ADME properties with substructure pattern recognition. J Chem Inf Model 2010; 50: 1034–41.Google Scholar
Shaker, B, Yu, MS, Song, JS, et al. LightBBB: computational prediction model of blood–brain-barrier penetration based on LightGBM. Bioinformatics 2021; 37:1135–9.Google Scholar
Miao, R, Xia, LY, Chen, HH, et al. Improved classification of blood–brain-barrier drugs using deep learning. Sci Rep 2019; 9: 8802.Google Scholar
Saxena, D, Sharma, A, Siddiqui, MH, et al. Blood brain barrier permeability prediction using machine learning techniques: an update. Curr Pharm Biotechnol 2019; 20: 1163–71.Google Scholar
Cheng, F, Kovacs, IA, Barabasi, AL. Network-based prediction of drug combinations. Nat Commun 2019; 10: 1197.Google Scholar
Bakkar, N, Kovalik, T, Lorenzini, I, et al. Artificial intelligence in neurodegenerative disease research: use of IBM Watson to identify additional RNA-binding proteins altered in amyotrophic lateral sclerosis. Acta Neuropathol 2018; 135: 227–47.Google Scholar
Wang, Q, Chen, R, Cheng, F, et al. A Bayesian framework that integrates multi-omics data and gene networks predicts risk genes from schizophrenia GWAS data. Nat Neurosci 2019; 22: 691–9.Google Scholar
Fang, J, Zhang, P, Wang, Q, et al. Network-based translation of GWAS findings to pathobiology and drug repurposing for Alzheimer’s disease. bioRxiv 2020;DOI: http://doi.org/10.1101/2020.01.15.20017160.Google Scholar
Cheng, F, Desai, RJ, Handy, DE, et al. Network-based approach to prediction and population-based validation of in silico drug repurposing. Nat Commun 2018; 9: 2691.Google Scholar
Greene, JA, Loscalzo, J. Putting the patient back together: social medicine, network medicine, and the limits of reductionism. N Engl J Med 2017; 377: 2493–9.Google Scholar
Zeng, X, Song, X, Ma, T, et al. Repurpose open data to discover therapeutics for COVID-19 using deep learning. J Proteome Res 2020; 19: 4624–36.Google Scholar
Santos, R, Ursu, O, Gaulton, A, et al. A comprehensive map of molecular drug targets. Nat Rev Drug Discov 2017; 16: 1934.Google Scholar
Zeng, X, Zhu, S, Lu, W, et al. Target identification among known drugs by deep learning from heterogeneous networks. Chem Sci 2020; 11: 1775–97.Google Scholar
Zeng, X, Zhu, S, Liu, X, et al. deepDR: a network-based deep learning approach to in silico drug repositioning. Bioinformatics 2019; 35: 5191–8.Google Scholar
Fang, J, Pieper, AA, Nussinov, R, et al. Harnessing endophenotypes and network medicine for Alzheimer’s drug repurposing. Med Res Rev 2020; 40: 2386–426.Google Scholar
Hampel, H, Williams, C, Etcheto, A, et al. A precision medicine framework using artificial intelligence for the identification and confirmation of genomic biomarkers of response to an Alzheimer’s disease therapy: analysis of the blarcamesine (ANAVEX2-73) Phase 2a clinical study. Alzheimers Dement (N Y) 2020; 6: e12013.Google Scholar
Simpraga, S, Alvarez-Jimenez, R, Mansvelder, HD, et al. EEG machine learning for accurate detection of cholinergic intervention and Alzheimer’s disease. Sci Rep 2017; 7: 5775.Google Scholar
Park, JH, Cho, HE, Kim, JH, et al. Machine learning prediction of incidence of Alzheimer’s disease using large-scale administrative health data. NPJ Digit Med 2020; 3: 46.Google Scholar
Ma, J, Yu, MK, Fong, S, et al. Using deep learning to model the hierarchical structure and function of a cell. Nat Methods 2018; 15: 290–8.Google Scholar
Cheng, F, Ma, Y, Uzzi, B, et al. Importance of scientific collaboration in contemporary drug discovery and development: a detailed network analysis. BMC Biol 2020; 18: 138.Google Scholar
Tasaki, S, Gaiteri, C, Mostafavi, S, et al. The molecular and neuropathological consequences of genetic risk for Alzheimer’s dementia. Front Neurosci 2018; 12: 699.Google Scholar
Cheng, F, Zhao, J, Wang, Y, et al. Comprehensive characterization of protein–protein interactions perturbed by disease mutations. Nat Genet 2021; 53: 342–53.Google Scholar
Swarup, V, Hinz, FI, Rexach, JE, et al. Identification of evolutionarily conserved gene networks mediating neurodegenerative dementia. Nat Med 2019; 25: 152–64.Google Scholar
Wang, M, Li, A, Sekiya, M, et al. Transformative network modeling of multi-omics data reveals detailed circuits, key regulators, and potential therapeutics for Alzheimer’s disease. Neuron 2021; 109: 257–72.Google Scholar
Xu, J, Zhang, P, Huang, Y, et al. Multimodal single-cell/nucleus RNA-sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer’s disease. Genome Res 2021;DOI: http://doi.org/10.1101/gr.272484.120.Google Scholar