MétaCan
Menu
Retour à la cohorte
Enregistrement W4379650819 · doi:10.1136/annrheumdis-2023-eular.1464

AB1591 POLICY DRIVERS FOR MARKET PENETRATION OF ANTI-TNF BIOSIMILARS: MULTI-COUNTRY COMPARISONS

2023· article· en· W4379650819 sur OpenAlexafffundabout
Wei Zhang, Daphne Guh, Huaibo Sun, Angela Tam, Nick Bansback, Aidan Hollis, Paul Grootendorst, Aslam H. Anis

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineImmunology and Microbiology
ThématiqueBiosimilars and Bioanalytical Methods
Établissements canadiensUniversity of TorontoUniversity of CalgaryCentre for Advancing Health OutcomesUniversity of British Columbia
Organismes subventionnairesUCB PharmaJazz PharmaceuticalsNordic Pharma GroupMylanBiogenSanofiMerckCanadian Institutes of Health ResearchNovartisPfizerEli Lilly and CompanyBristol-Myers Squibb
Mots-clésBiosimilarProcurementInfliximabMedicinePenetration (warfare)Market penetrationMarket shareBusinessMarketingOperations researchTumor necrosis factor alphaInternal medicineEngineering

Résumé

récupéré en direct d'OpenAlex

<h3>Background</h3> Health systems across countries have used different policy measures (e.g. price discounts, tendering, mandating switches) to encourage the introduction of biosimilars but their differential impact on market penetration is unknown. <h3>Objectives</h3> To evaluate the impact of policy measures on market penetration of anti-TNF biosimilars. <h3>Methods</h3> Quarterly IQVIA MIDAS sales data from 2012-2021 for infliximab, etanercept and adalimumab in 5 countries (Canada, France, Germany, Italy and the United Kingdom (UK)) that used different policy tools were used. Biosimilar market penetration was measured by dividing the number of defined daily dose units (DDDs) of biosimilars sold by the total number of DDDs of the originator and biosimilars sold. Market penetration since the first sale date of the biosimilars was captured by product, setting (hospital vs. retail), and country. Policy impact was examined by comparing market penetration among different policy scenarios (Table 1). <h3>Results</h3> Biosimilars for all three anti-TNFs had higher volume share over time (Figure 1) in the UK than Germany, suggesting that higher prescribing quotas among new and existing patients increases the market penetration of biosimilars given comparable demand-side policies. Since some anti-TNFs are dispensed only in hospitals in some countries, the settings are somewhat different. In France, infliximab biosimilars in hospital setting had faster penetration than other anti-TNF biosimilars in retail setting, indicating that tendering works better than price-links to increase biosimilar uptake. However, infliximab biosimilars in France had slower penetration than in Italy despite the higher discount price-link but absent quotas in France. Similarly, biosimilars had higher volume share over time in UK than Italy, which also suggests that higher prescribing quotas have a greater impact than price-links. Without price-link and tendering measures, Canada had the slowest penetration. By the end of our study period, the limited rollout of mandatory switching policies (3/10 provinces) for existing patients may not be sufficient in fostering market penetration, despite widespread implementation of mandatory prescribing for new patients. <h3>Conclusion</h3> Through comparisons between and within countries, we found that higher prescribing quotas or switching for existing patients and tendering are the key policy drivers for market penetration of anti-TNF biosimilars. <h3>References</h3> [1] Vogler S, Schneider P, Zuba M, Busse R, Panteli D. Policies to Encourage the Use of Biosimilars in European Countries and Their Potential Impact on Pharmaceutical Expenditure. <i>Frontiers in Pharmacology</i>. 2021;12. Accessed December 15, 2022. https://www.frontiersin.org/articles/10.3389/fphar.2021.625296 [2] McClean AR, Law MR, Harrison M, Bansback N, Gomes T, Tadrous M. Uptake of biosimilar drugs in Canada: analysis of provincial policies and usage data. <i>CMAJ</i>. 2022;194(15):E556-E560. doi:10.1503/cmaj.211478 [3] NHS England. <i>Commissioning Framework for Biological Medicines</i>. NHS England; 2017. Accessed December 15, 2022. https://www.england.nhs.uk/wp-content/uploads/2017/09/biosimilar-medicines-commissioning-framework.pdf <h3>Acknowledgements</h3> We acknowledge the funding support the Canadian Institutes of Health Research Project Grant (PJT-178132). <h3>Disclosure of Interests</h3> Wei Zhang Grant/research support from: Pfizer, Tilray, and bioMérieux Canada for projects unrelated to the present study., Daphne Guh: None declared, Huiying Sun: None declared, Alexander Tam Consultant of: I was previously employed at a market access research company. In that capacity, I generated reports for health technology companies. Companies were: Novartis AG, Merck &amp; Co., Pfzier Inc., Biogen Inc., Sanofi, Mylan N.V., Bristol-Myers Squibb, Jazz Pharmaceuticals, and Roche Diagnostics., Nick Bansback: None declared, Aidan Hollis: None declared, Paul Grootendorst Consultant of: I wrote expert reports on behalf of both of branded and generic drug companies. None were specifically related to drugs/devices for use in rheumatology., Grant/research support from: Sanofi co-sponsored (along with a public organization) a post- doctoral fellowship that I supervised., Aslam Anis Grant/research support from: I have previously received grants from Beijing Genomics Institute, AbbVie, Abbott Laboratories Ltd. and Sanofi-Aventis Canada Inc to conduct work unrelated to the present study.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,372
Score d'incertitude au seuil0,836

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,048
Tête enseignante GPT0,344
Écart entre enseignants0,296 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission3
Résumé présentoui

Explorer davantage

Même sujetBiosimilars and Bioanalytical MethodsTravaux en français237 207