A recent paper by Barbier et al. described the criteria to be considered when selecting best-value biological, emphasizing that more factors should be taken into account than only the price, and the authors proposed an updated approach - a model, and guidelines to assist healthcare professionals to make transparent and evidence-based decisions [1].
Best-value biological selection making: more to consider than only price
Biosimilars/Research | Posted 03/02/2023 0 Post your comment
With biosimilar medicines becoming available on the market, clinicians and pharmacists have multiple off-patent biological products to choose from. Moreover, there are often multiple biosimilars available per originator reference biological medicine. When making a choice between these available products, other criteria basing the selection on the broader value of the product besides the competitiveness of the product’s price are important and of value to take into account [1-3].
According to the author, basing the selection on the broader value of the product and not solely on price is also referred to as best-value biological selection making [3].
Earlier research found that hospital pharmacists experience difficulties with formulating and applying criteria besides price in the context of selection of off-patent biologicals and biosimilars, highlighting the need for guidance [1]. Over the past years, several scientific publications aimed to provide support to hospital pharmacists and other decision-makers in this context [4-6]. However, since then, the biosimilar product landscape and especially the experience with biosimilar evaluation and their use in clinical practice evolved significantly, making some of the earlier proposed criteria obsolete. Hence, a need for a reassessment and continued development of guidance was identified [1, 2].
To address this, Barbier et al. developed an up-to-date model to facilitate transparent best-value biological selection in the off-patent biological medicines segment and support decision-makers. The presented model was developed on the basis of established multi-criteria decision analysis (MCDA) tools for rational and transparent medicine selection, namely the System of Objectified Judgement Analysis and InforMatrix. Selection criteria included in the model were informed by earlier research, a literature search, and evaluation by the authors [2].
The developed model by Barbier et al. consist of three consecutive steps: (i) identification of relevant criteria; (ii) allocation of weights and define scoring system; (iii) evaluation of the different products, and includes up-to-date guidance on criteria that can be considered in the selection. Three main categories of criteria besides price were identified and included in the model: (i) product-driven criteria; (ii) service-driven criteria; and (iii) patient-driven criteria. Product-driven criteria include technical product features and licensed (or reimbursed) therapeutic indications. Service-driven criteria consist of supply conditions, value-added services and environment and sustainability criteria. Patient-driven criteria contain: product administration elements such as ease of use; and service elements such as patient support programmes. Furthermore, background is provided on the allocation of weights that may aid hospital pharmacists and clinicians with product decision-making in practice. For the allocation of weights it is important to consider that relative weighting of the criteria is largely context dependent and should be tailored to the decision-specific setting. Selection making should be measurable, objective, and transparent. Therefore, the selection criteria, their weights and scoring should be transparently defined in advance [1, 2].
Barbier et al. highlighted that the selection process can and may lead to not only one, but several best-value biologicals. Especially in settings where the market volume is large, selection of multiple winners should be strived for. Stimulating market plurality benefits both the sustainability of the market and the availability of biological medicines for patients [1, 7].
The practical model presented by Barbier et al. may support hospital pharmacists and clinicians with transparent and evidence-based best-value biological selection in clinical practice.
Conflict of interest
The authors of the research paper declared that there was no conflict of interest.
Abstracted by Dr Liese Barbier, Postdoctoral Researcher, Regulatory Evaluation and Market Access Biosimilars, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Belgium.
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Readers interested to learn more about European prescribers’ attitudes and beliefs on biologicals prescribing are invited to visit www.gabi-journal.net to view the following manuscript published in GaBI Journal:
European prescribers’ attitudes and beliefs on biologicals prescribing and automatic substitution
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References
1. Barbier L, Vandenplas Y, Boone N, et al. How to select a best-value biological medicine? A practical model to support hospital pharmacists. Am J Health Syst Pharm. 2022;79(22):2001-11.
2. Barbier L, Simoens S, Soontjens C, et al. Off-patent biologicals and biosimilars tendering in Europe - a proposal towards more sustainable practices. Pharmaceuticals. 2021;14(6):499.
3. NHS England. Commissioning framework for biological medicines (including biosimilar medicines) (2017). Available from: https://www.england.nhs.uk/wp-content/uploads/2017/09/biosimilar-medicines-commissioning-framework.pdf
4. Crommelin D, Bermejo T, Bissig M, et al. Pharmaceutical evaluation of biosimilars: important differences from generic low-molecular-weight pharmaceuticals. Eur J Hosp Pharm Sci. 2005;11:11-17.
5. Kramer I, Tredree R, Vulto A. Points to consider in the evaluation of biopharmaceuticals. Eur J Hosp Pharm-S P. 2008;14:73-6.
6. Boone N, van der Kuy H, Scott M, et al. How to select a biosimilar. Eur J Hosp Pharm. 2013;20:275-86.
7. Dranitsaris G, Jacobs I, Kirchhoff C, et al. Drug tendering: drug supply and shortage implications for the uptake of biosimilars. Clinicoecon Outcomes Res. 2017;9:573-84.
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