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Public Health Impact of Using Biosimilars, Is Automated Follow up Relevant?

1
Compliance Department, Amgen SAS, 92100 Boulogne-Billancourt, France
2
Faculty of Pharmaceutical and Biological Sciences, University of Nantes, 44035 Nantes, France
3
University of Nantes, INSERM UMR1229, RMeS, Regenerative Medicine and Skeleton, ONIRIS, 44322 Nantes, France
4
Central Pharmacy, University Public Hospitals of Nantes, 44093 Nantes, France
5
Université de Nantes, CRCINA, F-44000 Nantes, France
6
Sponsor Department, University Public Hospitals of Nantes, 44093 Nantes, France
7
Law and Social Change Laboratory, Faculty of Law and Political Sciences, University of Nantes, CNRS UMR6297, 44300 Nantes, France
8
Oncology Data Factory and Analytics Department, Institut de Cancérologie de l’Ouest, 44800 Nantes-Angers, France
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(1), 186; https://doi.org/10.3390/ijerph18010186
Received: 21 November 2020 / Revised: 17 December 2020 / Accepted: 19 December 2020 / Published: 29 December 2020
(This article belongs to the Special Issue Biosimilars: Economic, Health Policy, and Public Health Issues)
Biologic reference drugs and their copies, biosimilars, have a complex structure. Biosimilars need to demonstrate their biosimilarity during development but unpredictable variations can remain, such as micro-heterogeneity. The healthcare community may raise questions regarding the clinical outcomes induced by this micro-heterogeneity. Indeed, unwanted immune reactions may be induced for numerous reasons, including product variations. However, it is challenging to assess these unwanted immune reactions because of the multiplicity of causes and potential delays before any reaction. Moreover, safety assessments as part of preclinical studies and clinical trials may be of limited value with respect to immunogenicity assessments because they are performed on a standardised population during a limited period. Real-life data could therefore supplement the assessments of clinical trials by including data on the real-life use of biosimilars, such as switches. Furthermore, real-life data also include any economic incentives to prescribe or use biosimilars. This article raises the question of relevance of automating real life data processing regarding Biosimilars. The objective is to initiate a discussion about different approaches involving Machine Learning. So, the discussion is established regarding implementation of Neural Network model to ensure safety of biosimilars subject to economic incentives. Nevertheless, the application of Machine Learning in the healthcare field raises ethical, legal and technical issues that require further discussion. View Full-Text
Keywords: machine learning; biosimilars; immunogenicity; economic incentives; safety machine learning; biosimilars; immunogenicity; economic incentives; safety
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MDPI and ACS Style

Perpoil, A.; Grimandi, G.; Birklé, S.; Simonet, J.-F.; Chiffoleau, A.; Bocquet, F. Public Health Impact of Using Biosimilars, Is Automated Follow up Relevant? Int. J. Environ. Res. Public Health 2021, 18, 186. https://doi.org/10.3390/ijerph18010186

AMA Style

Perpoil A, Grimandi G, Birklé S, Simonet J-F, Chiffoleau A, Bocquet F. Public Health Impact of Using Biosimilars, Is Automated Follow up Relevant? International Journal of Environmental Research and Public Health. 2021; 18(1):186. https://doi.org/10.3390/ijerph18010186

Chicago/Turabian Style

Perpoil, Antoine; Grimandi, Gael; Birklé, Stéphane; Simonet, Jean-François; Chiffoleau, Anne; Bocquet, François. 2021. "Public Health Impact of Using Biosimilars, Is Automated Follow up Relevant?" Int. J. Environ. Res. Public Health 18, no. 1: 186. https://doi.org/10.3390/ijerph18010186

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