OracleBio’s recent GCP implementation was driven by Clinical Operations Manager, Alison Bigley. In this blog, Alison discusses why GCP is important, the current state of play with regulatory standards in image analysis and more…
What is Good Clinical Practice and why is it important?
Good Clinical Practice (GCP) is an internationally recognised quality standard. GCP standards include ethical, scientific and practical requirements to which all clinical research is conducted.
The primary principal of GCP is to assure that the rights, safety and well-being of clinical trial subjects are protected during every facet of medical research studies.
Work conducted in accordance with GCP ensures that sample analysis or evaluations, on a clinical trial study, provide credible data for the provision of regulatory submissions. For quantitative image analysis data to be included in a data package submitted to regulatory authorities, it is essential that it is generated using a workflow that is in full accordance with GCP principles.
How is GCP applied to Quantitative Image Analysis?
The principles associated with GCP standards are defined in a series of European directives, US regulations and UK statutory instruments. The implementation of processes, associated with standards, within a company are realised in European and UK guidelines and reflection papers e.g., International Council for Harmonisation (ICH) E6 (R2) ‘Good Clinical Practice’ guidelines. This information, although not currently specific to quantitative image analysis, provides a benchmark from which to build a quality framework aligned to quantitative image analysis workflow activities on GCP studies.
OracleBio’s quality framework involves 6 main foundations comprising of i) organisation, ii) systems, iii) study performance, iv) data management, v) clinical investigations and vi) quality management. Each component includes multiple clearly defined processes and activities to enable clinical QIA studies to be conducted in accordance with GCP standards. A quality management system enables all activities to be documented and retained as evidence of clinical studies performed to GCP.
What is the current state of play with regulatory standards in image analysis?
Quantitative image analysis is performed in relation to approved prognostic and predictive biomarkers e.g. human epidermal growth factor receptor 2 (HER2) for breast cancer and more recently programmed death-ligand 1 (PD-L1) for Non-small cell lung carcinoma. However, there are no explicitly defined regulatory standards in relation to generally performing quantitative image analysis and so establishing quality that meets with these high standards requires the interpretation and adaptation of the guidelines associated with GCP regulations.
OracleBio has spent 3 years implementing a quality framework designed around key GCP standards that also incorporates laboratory-based principles as defined in Good Laboratory Practices (GLP) standards.
Why would all image analysis studies not be conducted to GCP?
Not all clinical quantitative image analysis data is required for inclusion in regulatory submission packages. This includes exploratory investigation studies where a range of approaches to cellular analysis are utilised to further evaluate potential concepts around efficacy and safety on clinical samples. GCP processes require in depth verifications, procedures and associated written evidence in support of data packages, which can require a significant amount of time and resource, in addition to image analysis actuation. It is not always practicable to include such levels of detail for exploratory purposes.
How dependent is GCP image analysis on other parts of the clinical study workflow?
Quantitative image analysis is often seen as a means of simply obtaining automated counts from histology-stained sections in support of a pathologist’s assessment. However, all procedures leading up to computerised analysis can have either a deterministic or stochastic impact on the outputs and measures obtained from running QIA. This includes tissue sampling, processing, staining, scanning and image transfers. Therefore, the quality and significance of data generated by QIA is highly dependent on all preceding processes.
OracleBio work closely with our Clients leading up to and during a Clinical study, where QIA is a requirement, to ensure a comprehensive understanding of the impact of technical processes and biological requirements on subsequent QIA to ensure the validity and integrity of the final data.
What about ISO standards?
The International Organisation for Standardisation (ISO) is a group of standards primarily for quality management systems. Although not written to specifically guide QIA implementation this set of guidelines can also be utilised, along with the guidelines detailed above for GCP, to support quality framework implementation and improvements.
The United Kingdom Accreditation Service (UKAS) is a national accreditation body that assesses the competence of organisations to ISO standards enabling companies to demonstrate a certified level of quality.
OracleBio are looking to become accredited to specific ISO standards in relation to providing quality QIA, in due course, including ISO15189 for Medical Laboratories and ISO27001 for Information Security Management.
About the Author: Alison Bigley
Clinical Operations Manager at OracleBio
Alison has been at OracleBio since 2016 and recently led the implementation of GCP services at the company. Alison has considerable experience in histology, immunohistochemistry and imaging on projects across various therapeutic areas involving pre-clinical, safety and translational medicine.
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