{"doi":"10.3389/frai.2022.660581","title":"Targeted Screening for Alzheimer's Disease Clinical Trials Using Data-Driven Disease Progression Models","abstract":"Heterogeneity in Alzheimer's disease progression contributes to the ongoing failure to demonstrate efficacy of putative disease-modifying therapeutics that have been trialed over the past two decades. Any treatment effect present in a subgroup of trial participants (responders) can be diluted by non-responders who ideally should have been screened out of the trial. How to identify (screen-in) the most likely potential responders is an important question that is still without an answer. Here, we pilot a computational screening tool that leverages recent advances in data-driven disease progression modeling to improve stratification. This aims to increase the sensitivity to treatment effect by screening out non-responders, which will ultimately reduce the size, duration, and cost of a clinical trial. We demonstrate the concept of such a computational screening tool by retrospectively analyzing a completed double-blind clinical trial of donepezil in people with amnestic mild cognitive impairment (clinicaltrials.gov: NCT00000173), identifying a data-driven subgroup having more severe cognitive impairment who showed clearer treatment response than observed for the full cohort.","journal":"Frontiers in Artificial Intelligence","year":2022,"id":270174,"datarank":0.6560772730418674,"base_score":2.70805020110221,"endowment":2.70805020110221,"self_citation_contribution":0.40620753016533157,"citation_network_contribution":0.24986974287653582,"self_endowment_contribution":0.40620753016533157,"citer_contribution":0.24986974287653582,"corpus_percentile":null,"corpus_rank":null,"citation_count":14,"citer_count":10,"citers_with_citation_signal":10,"citers_with_endowment":10,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9534,"is_data_producer":true,"deposit_databanks":{"ClinicalTrials.gov":["NCT00000173"]},"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":803954,"name":"Cameron Shand","orcid":"0000-0002-1299-890X","position":1,"is_corresponding":false},{"id":320896,"name":"David M. Cash","orcid":"0000-0001-7833-616X","position":2,"is_corresponding":false},{"id":244799,"name":"Daniel C. Alexander","orcid":"0000-0003-2439-350X","position":3,"is_corresponding":false},{"id":242544,"name":"Frederik Barkhof","orcid":"0000-0003-3543-3706","position":4,"is_corresponding":false},{"id":318443,"name":"Neil P. Oxtoby","orcid":"0000-0003-0203-3909","position":0,"is_corresponding":true}],"reference_count":33,"raw_metadata":null,"created_at":"2026-07-19T00:27:26.772098Z","pmid":"35719690","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}