Scholarlink

<p>Raman spectroscopy is utilised extensively in pharmaceutical analysis for tasks such as drug discovery, quality control and active pharmaceutical ingredient (API) development. Despite this, access to open-source Raman spectral datasets for modelling and analysis is often a challenge. In laboratory settings, small spectral libraries are typically compiled for one-shot identification of intermediates or unknown chemicals, which restricts availability to comprehensive and high-quality reference data. In this work, we introduce a new open-source Raman dataset consisting of pure chemical compounds commonly employed in the development of APIs. By curating and publishing this dataset, we aim to provide the scientific community with access to high-quality, reusable data. Containing 3,510 samples spanning 32 compounds, this data can be utilised for referencing and can potentially facilitate in the development of more accurate and generalisable calibration models when access to reference data is limited.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Open-source Raman spectra of chemical compounds for active pharmaceutical ingredient development

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年3月24日

查看全文
  • Aaron R. Flanagan,
  • Frank G. Glavin

摘要

Raman spectroscopy is utilised extensively in pharmaceutical analysis for tasks such as drug discovery, quality control and active pharmaceutical ingredient (API) development. Despite this, access to open-source Raman spectral datasets for modelling and analysis is often a challenge. In laboratory settings, small spectral libraries are typically compiled for one-shot identification of intermediates or unknown chemicals, which restricts availability to comprehensive and high-quality reference data. In this work, we introduce a new open-source Raman dataset consisting of pure chemical compounds commonly employed in the development of APIs. By curating and publishing this dataset, we aim to provide the scientific community with access to high-quality, reusable data. Containing 3,510 samples spanning 32 compounds, this data can be utilised for referencing and can potentially facilitate in the development of more accurate and generalisable calibration models when access to reference data is limited.