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Samenvatting Lecture 6 - Clinical Trials and Clinical Development AM_1180 (AM_1180)
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Lecture 6Introduction
● Biggest fear of drug developers: rejection of their outcome/investigations.
● To reduce the chance of rejection: termination of development → because
it's not ethical to redo a finished trial.
● What we want to do: keep close contact with regulators to know their expectations,
whether their CDP (clinical development plan) is good.
● Cover-your-ass management (CYA): as an investigator, eliminating all chances of
being responsible for no valuable data.
● R2 Addendum is new and adds quality management rules in IGH-GCP, it
incorporates RBCM (Risk Based Compliance monitoring). Is defined in chapter
5.0 (sponsor responsibility), but it is so important that it is put at the beginning of the
ICH-GCP.
● What is the impact of Risk Based Approach? Ensuring awareness of all the risks
related to trials and not minimizing but assessing all risks
● What is the probability of them occurring? On these basis you decide which risks are
allowed and which are prevented.
● Source data verification (SDV): process of verifying data that the data indeed came
from participants.
○ Thus sponsors monitor the quality of the data and do 100% SDV.
○ Investigators and trial site verify the database.
● The focus on quality control is not the same: low-experienced trial sites are higher
risk than high-experienced trial sites.
Why the R2 Addendum→ can't do analysis with data until database-lock (DBL)
because of bias.
● New opportunities to increase efficiency and focus on relevant activities
○ Evolutions in technology → electronic data capture (EDC):
computerized system to collect clinical trial data.
○ Risk management processes
● Centralized monitoring offers greater advantage
○ Early access to trial data
○ Running risk analysis
Side-note: The protocol beforehand needs to include the analysis that you will do.
What we can do: look at the general data and compare them with other data.
Like risk analysis with centralized monitoring→ take all the data and analyze it
for sites that have outliers. Potentially find errors and solve them in those sites.
R2 required quality management process steps→ 7 steps of Process Quality
Management:
● Critical process and data identification→ look at trial data and identify
critical data points (risks):
○ Identified during development of protocol
○ Critical Ensure human subject protection • Reliability of trial results
○ Reliability of trial results→ data points (e.g size of tumor,
concentration) that are rare. Critical data is for example the data
that is used to analyze primary end points.
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, ● Risk identification→ e.g with tumor measurement: not standardized units.
○ Risks to critical trial processes
○ Risks to the critical data points: skewed or not generated properly
○ System level: risks are (consent, safety reporting).
○ Trial level: risks are specific trial and protocol.
● Risk evaluation→ evaluate risks against controls.
○ Change occurrence of the risks vs the detectability
○ The impact on subject protection and reliability of trial
results
○ Remedial actions: what can we do to reduce it. (ICH-
GCP does not mention this, but we take it into
account)
○ The surface area indicates the overall risk. The
smaller the risk evaluation (surface area), the better.
● Risk control→ reduce or accept risks. The approach is proportional to
significance.
○ At all levels (trial & system level)
○ Predefined quality tolerance limits: to what extent we accept risks. It tells
when we need to take action (after x amount of time) and what controls to
take.
● Risk communication
○ Quality management plan including risk management plan
○ Facilitate review
○ This is a continuous process
● Risk review→ risks we can and cannot afford (see ICH-GCP centralized
monitoring)
○ Continuous review of risks
○ Quality tolerance limits
○ Emerging knowledge
● Risk reporting→ predefine the risk as much as you can, but keep the list
updated during the trial (because risks can change during trial). The CSR
should include:
○ Quality management approach
○ Important deviations form tolerance
○ Remedial actions
ICH-GCP E6 (R2) describes centralized monitoring as: Review, that may include
Statistical analyses, of accumulating data from centralized monitoring can be used to:
● Identify missing data, inconsistent data, data outliers, unexpected lack of variability
and protocol deviations.
● Examine data trends such as the range, consistency, and variability of data within
and across sites.
● Evaluate for systematic or significant errors in data collection and reporting at a site
or across sites; or potential data manipulation or data integrity problems.
● Analyze site characteristics and performance metrics.
● Select sites and/or processes for targeted on-site monitoring.
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