← 論文一覧に戻る

経口セマグルチド(リベルサス)のカーボンフットプリント推計:医薬品カーボンフットプリントモデルと製造業者ライフサイクル評価の比較分析

Estimating the carbon footprint of oral semaglutide (Rybelsus): a comparative analysis of the medicine carbon footprint model and manufacturer life-cycle assessment in pharmaceutical production (原題)

Louise Hansell, Wandi Zhu, Michelle Lynch, SL Hocking, David Stephen Celermajer, Fabian Sack

BMJ Open📚 査読済 / ジャーナル2026-09-01#炭素会計Origin: Global経営インパクト: 調達リスク対象セクター: pharmaceutical
DOI: 10.1136/bmjopen-2026-124968
原典: https://doi.org/10.1136/bmjopen-2026-124968

🤖 gxceed AI 要約

日本語

経口セマグルチド(リベルサス)について、簡易推計法である医薬品カーボンフットプリント(MCF)とノボノルディスク社のLCAを比較した。MCFは3・7・14mgで年8.9・20.0・39.3kgCO₂eとなり、LCA(17.0・25.2・39.9)より低く、特に低用量で乖離が大きい。固定費的な添加物・包装排出の配分差が原因で、境界の統一と透明性向上が課題と指摘する。

English

This study compares the medicine carbon footprint (MCF) framework against Novo Nordisk's manufacturer life-cycle assessment for oral semaglutide (Rybelsus). Annualised MCF estimates (8.9, 20.0, 39.3 kgCO2e/year for 3, 7, 14 mg) were lower than LCA values (17.0, 25.2, 39.9), with the largest gap at the lowest dose due to fixed excipient/packaging emissions. It highlights the need for harmonised boundaries and greater transparency in pharmaceutical carbon footprinting.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

医薬品の製品別カーボンフットプリントはScope 3(カテゴリ1)算定の難所であり、本稿は簡易推計法とLCAの乖離を示す。SSBJ・有報でのScope 3開示やサプライヤー排出データ整備を進める日本企業にとって、推計手法選択の実務的示唆を与える。

In the global GX context

Pharmaceutical product-level footprints sit squarely in Scope 3 Category 1, where disclosure quality varies widely. As ISSB/CSRD push for value-chain emissions transparency, this comparison of a rapid estimation tool against proprietary LCA data informs how companies and regulators judge the reliability of reported medicine footprints.

👥 読者別の含意

🔬研究者:簡易推計法とLCAの系統的乖離を定量化し、医薬品排出推計の方法論的限界を示す。

🏢実務担当者:自社製品のScope 3算定で簡易法とLCAの差を理解し、開示境界の設計に活用できる。

🏛政策担当者:医薬品の排出開示に統一境界と透明性を求める規制設計の根拠となりうる。

📄 Abstract(原文)

Objectives Pharmaceuticals are a major contributor to healthcare’s greenhouse gas emissions yet product-level carbon footprints are rarely disclosed. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are increasingly being used for the management of type 2 diabetes and people living with obesity, but their carbon impact remains poorly characterised. We aimed to compare carbon footprint estimates for oral semaglutide (Rybelsus), a peptide-based medicine, generated using the medicine carbon footprint (MCF) framework and manufacturer-reported life cycle assessment (LCA) data. Design and setting Comparative methodological analysis using cradle-to-gate boundaries to compare pharmaceutical carbon footprint estimates for oral semaglutide. Methods Per-tablet MCF estimates for 3, 7 and 14 mg Rybelsus were annualised and compared with product-specific LCA results reported by Novo Nordisk. Differences between methods were assessed descriptively across the three dose strengths. Absolute differences and symmetric percentage differences were calculated. Results Annualised MCF estimates were 8.9, 20.0 and 39.3 kg CO₂e/year for 3, 7 and 14 mg tablets, respectively. Corresponding EU LCA estimates were 17.0, 25.2 and 39.9 kgCO₂e/year. The mean symmetric percentage difference was −29%, with the largest discrepancy observed at the 3 mg dose (−62.6%) and the smallest difference at the 14 mg dose (−1.5%). Conclusion For oral semaglutide, MCF generated lower carbon footprint estimates than manufacturer-reported LCA values, particularly at lower doses, where fixed device/excipient and packaging emissions are proportionally larger. MCF offers a rapid, accessible and indicative estimation method when proprietary data are unavailable. Improved transparency and harmonised boundaries would strengthen comparability between pharmaceutical carbon footprint estimation approaches. These findings are specific to the Rybelsus formulation of oral semaglutide and may not be generalisable to other formulations or GLP-1 RAs.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。

gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。