The Duty for Sponor Oversight in Clinical Trials E-Book

Doris Breiner

• Herausgeber: Books on Demand
• Kategorie: Wissenschaft und neue Technologien
• Serie: The Duty for Sponor Oversight in Clinical Trials
• Sprache: Englisch

Seitenzahl: 73

Veröffentlichungsjahr: 2022

Beschreibung

The first edition of the practical guide related to the topic The Duty for Sponsor Oversight in Clinical Research outlined the underlying requirements as well as possible approaches to implement it efficiently in small and mid-sized companies. This was based on a master's thesis released in April 2019. The next edition will focus on the Clinical Data Review which includes all aspects to be considered, for example, the outcome of the overall monitoring oversight activities. Furthermore, to describe and show examples of a standardized score assignment to ensure a unique process of the assessment.

Leseprobe

The Duty for Sponor Oversight in Clinical Trials

The Duty for Sponor Oversight in Clinical TrialsPreambleTable of Content1. Introduction2. Underlying Rationale and Assumptions to the Approach3. Definition of the Clinical Data Review4. Clinical Data Review Details5. Risk Score Calculation6. Safety Management and Reporting Review as well as Clinical Data Coding Review (ICH-GCP 5.16, 5.17)7. Quality Control8. Sponsor Oversight Plan – Cross References9. ConclusionReferencesList of TablesAbbreviationsCopyright

The Duty for Sponor Oversight in Clinical Trials

Preamble: The first edition of the practical guide related to the topic „ The Duty for Sponsor Oversight in Clinical Research“ outlined the underlying requirements as well as possible approaches to implement it efficiently in small and mid-sized companies. This was based on a master's thesis released in April 2019. The next edition will focus on the „ Clinical Data Review“ which includes all aspects to be considered, for example, the outcome of the overall monitoring oversight activities. Furthermore, to describe and show examples of a standardized score assignment to ensure a unique process of the assessment. In addition to that, the derived value could be considered and taken into account for the overall Good Clinical Practice (GCP) clinical trial compliance, concerning the „Clinical Data Review“. As shown in the first edition the aim was to connect the activities with the corresponding items of the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH-GCP) related to this topic. However, the existing guidances outline the requirements on what is expected to be submitted to the authorities for further judgement. The kind of approach is more or less as presented and discussed in the 1st edition up to the responsible sponsor. That means the underlying rationale for the presented approach refers to the requirements, discussions around the definition and content of the „Clinical Data Review“ interpretation by experts and quality assurance of any kind of business, even the information technology (IT). Finally, the defined goal was to enhance with that procedure the quality of the data set required for AMNOG and/or fast-track approval. Also, any changes related to the topic as such induced e.g. by new EU-Trials Regulation 536/2014 which became effective in 2022 are considered. Also, any outcome of further discussions over time with regard to the 1st edition „The Duty for Sponsor Oversight in Clinical Trials“ are summarised briefly below. 

Outcome of further discussions over the time, with regard to the content of the 1st edition summarized briefly.

General aspect: Additional information for the relevant factors related to the so-called „Data Integrity“: technical equipement, used systems assessed as „Fit for purpose“, complexicity of the established processes, human ressource (responsible leadership, understanding, implementation)

The  ALCOA Principle: in overall in the 1st edition the meaning behind that principle was pointed out. For consisteny purposes the acronym „ ALCO+Principles“ (attributable, legible,contemporaneous, original or true copy, accurate) should always be mentioned.

Thank you for the discussions to the topic as such already started in 2017/2018 and as always any comments and crtitics are welcome to ensure the data sets presented to the public and authorities are realibale, acurate, and properly processed to ensure the ALCO + Principles and the data intergrity in the clinical research.  

Berlin, 20-Dec-2022                                                                                                                                                                                                       Doris Breiner, MSc

Table of Content

1.      Introduction 

2.      Underlying Rationale and Assumptions to the Approach 

3.      Definition of the Clinical Data Review

4.      Clinical Data Review Details

5.      Risk Score Calculation 

6.      Clinical Data and Coding Review  

7.      Quality Control 

8.      Sponsor Oversight Plan – Cross References 

9.      Conclusion

References

List of Tables

Abbreviations 

1. Introduction

Access to the marketing authorization of new pharmaceutical or biotechnology compounds requires specified data. Also, the proper clinical data documentation from the phase 1 study onwards is mandatory. This 2nd edition of the practical guide does not focus on and does not include the requirements for the study of drug manufacturing or so-called “Good Manufacturing Practice” (GMP), nor the requirements for the AMNOG in detail, as those are very specific. However, the quality aspects concerning the clinical data may contribute providing a comprehensive, consistent data set fulfilling the requirements for the AMNOG assessment by the G-BA (Gemeinsamer Bundesausschuss). The AMNOG procedure is solely applicable to Germany to allow the determination of additional benefits of a new treatment option, in comparison to a comparable, already established one. It serves as the basis for the pricing of the product between the health institution and the pharmaceutical manufacturer [1]. Also, for products with fast-track approval like, for example, granted by the Food and Drug Administration (FDA), the full submission package is not required to apply for that kind of authorisation [2]. The so-called rolling submission is at least sufficient, in case the first efficacy and safety data showed no severe safety concerns or insufficient efficacy results. However, over time it was seen that not in all cases enough safety and efficacy data were provided, this also applied to data concerning the changes in the quality of life. Also, the fulfilment of the sponsor oversight in terms of quality management showed gaps. Hence, the standardised “Clinical Data Review” which would include the outcome of the co-monitoring as well as the monitoring performance may contribute to allowing a higher quality of these preliminary data. Furthermore, the so-called “Benefit-Risk-Assessment”, to ensure patient safety and to justify the clinical trial could continue as planned, would be based on a set of data that was established in a risk-based, standardised manner.

In this second edition of the practical guide, it will therefore be shown how this task could be established in rather small, mid-sized companies or the field of academic research. In addition to that, some examples are presented with a clear and reasonable approach how to perform a “Clinical Data Review”, by the assignment of a pre-defined score assessment. Finally, to calculate the overall GCP compliance of the clinical data based on the outcome of the score assignment.

An example is referenced and shows on how the different components of the “Clinical Data Review” could be weighted in percentage. Already in 2009 the approach, for an efficient medical data review in exploratory drug development, was presented by others e.g. the pharmaceutical industry. At that time already the „Tibco Spotfire“, real-time analytical software was used. By using this software the reviewer could mine through large amounts of data quickly and efficiently. The data were presented in different visual formats. Ideas on how to “Improve the Clinical Data Review Process“, came up and could be retrieved via, for example,” a blog post published early in 2017.

The overall aim assumed is to ensure a stable, robust data set e.g., to apply for a fast-track approval which also would allow a firstly sufficient AMNOG assessment in Germany. The task as such could also be outsourced to a Contract Research Organisation (CRO) or Consultancy especially to avoid any conflict about a neutral and unbiased assessment. In that case, nevertheless, the sponsor keeps the overall responsibility of the data and the duty for sponsor oversight of outsourced activities remains effective.

Certainly, the fully automated review programming may allow tackling and limiting the resources required for that. It would not replace the visual view of an experienced medical or scientific person as such. The approach includes defining selection criteria for the patients per site and corresponding data items expected to be part of the data export to ensure a wide range of different data items to be reviewed. As pointed out by Perkin Elmer’s Clinical Analytics solutions [3] in the White Paper „Overcoming Common Challenges of Clinical Data Review“, the task is described as an intrinsic component of clinical development. The goal is to ensure patient safety, determine drug efficacy, and assess the data quality. Part of this analysis involves a broad variety of clinical trial data as well as the integration of data from multiple sources to extract actionable insights [3]. Taking the complexities into account the aim of the practical guide is to align those different aspects to finally integrate the outcome of the review into a number to indicate the percentage of the GCP clinical trial compliance concerning the “Clinical Data Review”.

For sure some limitations of the concept may be present and would be identified over the time. Because of this, after the establishment of any new procedure, an observation period of at least three to five years should show the risks and benefit of the taken approach.

2. Underlying Rationale and Assumptions to the Approach