Over the past decades Raman spectroscopy has been extensively used both on an industrial and academic level. This has resulted in the development of numerous specialised Raman techniques and Raman active products, which in turn has led to the adoption and development of standards and norms pertaining to Raman unit’s calibration, performance validation and interoperability. Purpose of the present review is to list, classify and engage in a comprehensive analysis of the different standards, guides and practices relating to Raman spectroscopy. Primary aim of the review is to consider the commonalities and conflicts between these standards and norms and to identify any missing aspects. Standardisation in the field of Raman spectroscopy is dominated by the work of American institutions, namely the American Society of Testing Materials (ASTM or ASTM International), with several active standards in place pertaining to terminology, calibration, multivariate analysis and specific applications, and the National Institute of Standards and Technology (NIST), providing numerous standard reference materials. The industrial application of Raman spectroscopy is dominated by the pharmaceutical industry. As such, pharmacopoeias provide not only important information in relation to pharmaceutical-related applications of Raman spectroscopy, but also invaluable insight, usually by referring to ASTM and NIST standards, into the basic principles of Raman spectroscopy and important aspects that include calibration, validation, measurement and chemometric analysis processes. Given the fact that Raman spectroscopy is a modern and innovative field, the standardisation processes are complex and constantly evolving. Despite the seemingly high number of existing standards, the standardisation landscape is incomplete and has not been modernised according to the developments in Raman spectroscopy techniques in recent years. This is evident by the lack of protocols for numerous areas as well as by the fact that some of the existing standards have not been updated to reflect the advances in the technique. Therefore, it is important for the Raman community to actively engage in and contribute to a modernisation process that will result in updating exiting and introducing new terms, protocols and guides. Indeed, the development of optimised common standards would be extremely beneficial and would further foster the development and application of Raman spectroscopy techniques, most notably those of surface enhanced Raman spectroscopy and low-resolution portable analysers.

Raman spectroscopy is used in a wide variety of fields, and in a plethora of different configurations. Raman spectra of simple analytes can often be analyzed using univariate approaches and interpreted in a straightforward manner. For more complex spetral data such as time series or line profiles (1D), Raman maps (2D), or even volumes (3D), multivariate data analysis (MVDA) becomes a requirement. Even though there are some existing standards for creation, implementation, and validation of methods and models employed in industry and academics, further research and development in the field must contribute to their improvement. This review will cover, in broad terms, existing techniques as well as new developments for MVDA for Raman spectroscopic data, and in particular the use associated with instrumentation and data calibration. Chemometric models are often generated via fusion of analytical data from different sources, which enhances model discrimination and prediction abilities as compared to models derived from a single data source. For Raman spectroscopy, raw or unprocessed data is rarely ever used. Instead, spectra are usually corrected and manipulated, 1 often by case-specific rather than universal methods. Calibration models can be used to characterize qualitatively and/or quantitatively samples measured with the same instrumentation that was used to create the model. However, regular validation is required to ensure that aging or incorrect maintenance of the instrument does not alter the model’s predictions, particularly when applied in regulated fields such as pharmaceuticals. Furthermore, a model transfer may be required for different reasons, such as replacement or significant repair of the instrumentation. Modeling can also be used to consistently harmonize Raman spectroscopic data across several instrumental designs, accounting for variations in the resulting spectrum induced by different components. Data for Raman harmonization models should be processed in a protocolled manner, and the original data accessible to allow for model reconstruction or transfer when new data is added. Important processing steps will be the calibration of the spectral axes and instrument dependent effects, such as spectral resolution. In addition, data fusion and model transfer are essential for allowing new instrumentation to build on existing models to harmonize their own data. Ideally, an open access database would be created and maintained, for the purpose of allowing for continued harmonization of new Raman instruments using an outlined and accepted protocol.