MétaCan
Menu
Back to cohort
Record W4408317466 · doi:10.1186/s13722-025-00554-1

Lessons from the National institutes of health innovation corps program: defining barriers to developing and commercializing novel solutions for persons with opioid use disorder

2025· article· en· W4408317466 on OpenAlex
Matthew Heshmatipour, Tyler M. Duvernay, Desislava Z. Hite, Eboo Versi, M. Jo Hite, David Reeser, V.I. Prikhodko, Ariana M. Nelson, Bina Julian

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAddiction Science & Clinical Practice · 2025
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsEmergent BioSolutions (Canada)
FundersNational Institute on Drug Abuse
KeywordsPsychological interventionOpioid use disorderHealth careHealth psychologyPublic healthPublic relationsBusinessSubstance abuseVariety (cybernetics)MedicineNursingPsychiatryPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: Translating innovative research advancements into commercially viable medical interventions presents well-known challenges. However, there is limited understanding of how specific patient, clinical, social, and legal complexities have further complicated and delayed the development of new and effective interventions for Opioid Use Disorder (OUD). We present the following case studies to provide introductory clinical, social, and business insights for researchers, medical professionals, and entrepreneurs who are considering or are currently developing medical. METHODS: Four small business recipients of National Institute on Drug Abuse (NIDA) small business grant funding collected a total of 416 customer discovery interviews during the 2021 National Institutes of Health (NIH) Innovation-Corps (I-Corps) program. Each business received funding to advance an OUD-specific innovation: therapeutics (2 companies), medical device (1 company), and Software as a Medical Device (SaMD) (1 company). Interview participants included stakeholders from a variety of disciplines of Substance Use Disorders (SUD) healthcare including clinicians, first responders, policymakers, relevant manufacturers, business partners, advocacy groups, regulatory agencies, and insurance companies. RESULTS: Agnostic to the type of product (therapeutic, device, or SaMD), several shared barriers were identified: (1) There is a lack of standardization across medical providers for managing patients with OUD, resulting in diverse implementation practices due to a fragmented healthcare policy; (2) Underlying Social Determinants of Health (SDOH) present unique challenges to medical care and contribute to poor outcomes in OUD; (3) Stigma thwarts adoption, implementation, and the development of innovative solutions; (4) Constantly evolving public health trends and legal policies impact development and access to OUD interventions. CONCLUSION: It is critical for innovators to have early interactions with the full range of OUD stakeholders to identify and quantify true unmet needs and to properly position development programs for commercial success. The NIH I-Corps program provides a framework to educate researchers to support their product design and development plans to increase the probability of a commercially successful outcome to address the ongoing opioid epidemic.

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.

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)0.003
metaresearch head score (Gemma)0.033
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.193
GPT teacher head0.487
Teacher spread0.294 · 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