Early Phase Clinical Trials Maxims
Over the last 30 years and thousands of early phase trials execution, SGS has acquired a unique expertise in early phase healthy subjects and patients clinical trials.
From drug development consultancy, preclinical data analysis, study design and first in human (FIH), to exploratory trials and proof of concept studies, we are pleased to share, through the following Maxims, the early phase clinical trial drug development fundamentals.
Maxim#1 Study Design
Analyze all pre-clinical data and optimize the study design
The moment when a new compound is ready to be tested in humans is exciting but challenging. It means the drug has successfully passed a battery of pre-clinical tests, but based on these, many important decisions for its clinical development need to be made such as:
To predict a drug’s behavior in humans, all relevant pre-clinical data should be thoroughly analyzed. Often, more data is needed than what is strictly required by the regulators depending on the pharmacological and safety profile. For study design there is also not one-size-fits all.
To learn more about how to analyze all pre-clinical data, and optimize study design with concrete case studies:
Maxim#2 Regulatory Proofed
Working closely with regulators is a key strategy for successful drug development, not a barrier to be sidestepped or overcome.
Building regulatory advice into a trial program is an effective strategy to mitigate the regulatory risk inherent in product development and improve the likelihood of early product approval.
Requesting scientific advice from the right regulatory body at the right time has become an essential tool to guide product development and to have answer on many aspects of the development program:
To learn more about scientific advices from regulators with concrete case studies:
Maxim#3 Consider Modeling & Simulation
Careful decision making is essential to minimize clinical development time, manage costs and improve the probability of commercial success.
Modeling and simulation (M&S) can be a very useful strategy to mitigate risks and to make better informed decisions.
M&S involves modeling compounds, mechanisms and disease level data based on historical observations and existing real life data. Computer simulations are run on these models to generate information that can be used to predict outcomes, thereby improving the quality, efficiency and cost-effectiveness of decision-making, both for internal and regulatory purposes.
M&S can be of help in several areas of drug development:
To further discover Modeling & Simulations uses in early phase clinical trials with concrete case studies: