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Record W4389775441 · doi:10.1212/wnl.0000000000207958

FDA Patient-Focused Drug Development Guidances

2023· article· en· W4389775441 on OpenAlexaff
Anne T. Berg, Natasha N. Ludwig, Mary Wojnaroski, Chere A. T. Chapman, Rebecca Hommer, Gabrielle Conecker, JayEtta Hecker, Jenny Downs

Bibliographic record

VenueNeurology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsTechnical University of Nova Scotia
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsDrug developmentClinical trialMedicineDiseaseLimitingIntensive care medicineFood and drug administrationDrugPsychologyPsychiatryRisk analysis (engineering)Pathology

Abstract

fetched live from OpenAlex

Developmental and epileptic encephalopathies (DEE) are rare, often monogenic neurodevelopmental conditions. Most affected individuals have refractory seizures. All have multiple severe impairments which can be as life-limiting as or more limiting than the seizures themselves. Mechanism- and gene-targeted therapies for these individually rare, genetic conditions hold hope for treatment, amelioration of disease expression, and even cure. The near absence of fit-for-purpose (FFP) clinical outcome assessments (COA) to establish the benefits for nonseizure outcomes of these new therapies in clinical trials poses significant challenges to drug development. The Food and Drug Administration Patient-Focused Drug Development guidance series provides direction for how to overcome these challenges and to ensure FFP measures are available for trials. The goal is to have measures that address outcomes of importance to patients and caregivers, reliably and accurately measure the outcome in the spectrum of abilities for the target disease, and are sensitive to meaningful change over time. The guidances identify 3 primary strategies: (1) directly adopting and implementing available outcome measures; (2) creating measures de novo; and (3) a middle path of adapting or modifying existing measures. Emphasized throughout the guidances is the indispensable and extensive role of the patient or caregiver to assuring the goal of having fit measures is achieved. This review specifically considers the difficulties of adopting available COAs in severely impaired patient groups and ways to adapt or modify existing COAs to be FFP as encouraged in the guidances. Adaptations include alternative scoring, use of assessments in out-of-intended age ranges, and modifications for individuals with sensory or motor impairments. Some additional considerations that may facilitate achieving adequate clinical outcome measures, especially for rare diseases, include use of personalized endpoints, merging of existing COAs, and developing a consortium of rare DEE advocates and researchers to ensure fitness of adapted COAs across multiple rare disease groups. The FDA guidances help ensure that clinical trials targeting nonseizure outcomes, especially in severely impaired populations, will have adequately valid and sensitive outcome measures. This in turn will strengthen the ability of trials to provide informative tests of whether treatments provide meaningful therapeutic efficacy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.215
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations36
Published2023
Admission routes1
Has abstractyes

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