Computer Modeling Useful for Planning a Drug Trial
Until recently, the clinical research sector has had difficulty adopting computer modeling and simulation due to a variety of factors. Among these have been, the uncertain regulatory challenges of modeling and simulation applications, a lack of large-population data, and complicated biological systems. These factors have all prevented the utiliziation of computer modeling. However, these barriers are slowly breaking down and more complex experiment blueprints are being brought forth.
The Applied Clinical Trials Online publication reports that models can now be used to predict the outcome of a clinical trial and test variance within a system. When planning a clinical trial and designing drug studies, models and simulations can help define risk and provide input on improving trial outcomes.
Drug development has become a complicated process in which predicting the health outcomes of patients and effectiveness of the medication can be difficult to accomplish. This is why, in 2004, the Food and Drug Administration (FDA) called for the development of predictive tools to reduce drug study failures. Computer-based predictive modeling is a beneficial method for improving clinical study efficiency and improving the rate of success in drug development.
Through the use of computer modeling when designing a clinical drug trial, it is possible to improve information sharing and collaboration among research development professionals. This helps remove errors and failures throughout the entire research trial lifecycle.
Drug Dosage Solutions
Computer modeling also provides a superior way to determine appropriate drug dosages including endpoints and predicted outcomes. This is especially useful for testing in more complex populations such as children, elderly, patients with injuries or disabilities, and those with renal failure.
Answers to Clinical Trial Design
Computer-based Modeling and simulation improves decision-making in the design of clinical trials and allows for problem solving with regard to the safety and efficacy of a new drug. In this scenario, a researcher would use a simulation to evaluate a number of different strategies for each of the different phases of a clinical trial based on safety, efficacy, and evidence from preclinical and early clinical results.
These simulations provide information to clinicians, statisticians, health economists, and regulatory affairs professionals for making informed decisions on drug development studies.
Over the last five years, the FDA has pushed forward quantitative modeling and trial simulation to improve drug dosing regimens and gain greater understanding of drug response and exposure. In fact, pharmacometric models have helped contribute to more drug approvals for dozens of applications.
While there are plenty of benefits to modeling and simulation, there are still some barriers standing in the way such as the time it consumes, the costs, and the lack of expertise for many startup companies. Essentially, a sponsor or contract research organization will need to discuss whether modeling and simulation will pay off in the long run with regard to trial predictability.
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Categories: Toxicology and Pharmacology