Model-Informed Drug Development (MIDD)
Model-Informed Drug Development (MIDD) is an approach to drug development that uses mathematical models to integrate information from various sources to inform drug development decisions. MIDD is also known as Quantitative Systems Pharmacology (QSP) or Pharmacometrics.
The aim of MIDD is to optimize drug development and improve decision-making by using quantitative models to describe the relationships between drug exposure, patient characteristics, disease progression, and clinical outcomes. The models can be used to simulate the effects of different dosing regimens, patient populations, and study designs, and to predict the likelihood of success in clinical trials.
MIDD involves the use of various modeling and simulation techniques, such as pharmacokinetic-pharmacodynamic (PK-PD) modeling, population PK modeling, disease progression modeling, exposure-response modeling, and clinical trial simulations. These techniques allow for the integration of preclinical data, clinical data, and other relevant information to inform drug development decisions.
MIDD can be used throughout the drug development process, from early discovery to post-marketing. In the early stages of drug development, MIDD can help identify promising drug candidates and optimize drug dosing regimens. In later stages of drug development, MIDD can inform clinical trial design, dosage selection, and regulatory submissions.
MIDD has several advantages over traditional drug development approaches, including reduced costs and timelines, improved efficiency, and better decision-making. MIDD can help to identify potential safety and efficacy issues early in the drug development process, reducing the risk of failure in later stages. It can also help to optimize dosing regimens to maximize efficacy and minimize adverse effects.
Overall, MIDD is an important tool for optimizing drug development and improving decision-making in drug development.