Model-informed drug development and precision dosing (MIDD/MIPD) is achieved through quantitative pharmacology techniques, including population pharmacokinetic (PPK) modeling, population pharmacodynamics (PPD) modeling, pharmacokinetics/pharmacodynamics (PK/PD) modeling, physiologically based pharmacokinetics (PBPK) modeling, and model-based meta-analysis (MBMA). These models are used to improve the efficiency and reduce the cost and risk in drug development, and to provide the basis for precise drug use for patients in clinical practice. The core of MIDD/MIPD is modeling and simulation through artificial intelligence. The goal of this Research Topic is to promote drug development and individualized drug delivery.
For MIDD, based on different application scenarios, the PPK, PPD, PK/PD, PBPK, and MBMA models are used to assess and describe the fate of a drug in the body. Furthermore, the simulation method can be used in addition to virtually predict drug candidates for drug development to obtain an understanding of the therapeutic effects of uninitiated dosing regimens. This can be beneficial to reduce costs and increase efficiency.
For MIPD, based on clinical diagnosis and treatment process-related drugs data or drug trial data, the PPK, PPD, PK/PD, PBPK, and MBMA models can be built up to provide the basis for precise drug use for patients through modeling and simulation technology. MIPD can quantify the effects of different factors on drug absorption, distribution, metabolism, and excretion in specific disease states. Through the analysis of potential covariance, machine learning can be further used to recommend personalized doses for patients in clinical practice. This modeling would include optimizing the initial dose and making remedial dosing recommendations for delayed or missed doses.
The Research Topic welcomes the submission of original research and review articles focusing on MIDD/MIPD to improve the efficiency of drug research and development and to achieve personalized dose recommendations. Potential topics include, but are not limited to, the following:
1. Modeling and simulation for model-informed drug development and precision dosing (MIDD/MIPD) based on: a) population pharmacokinetic (PPK); b) population pharmacodynamics (PPD); c) pharmacokinetics/pharmacodynamics (PK/PD); d) physiologically based pharmacokinetics (PBPK); or e) model-based meta-analysis (MBMA).
2. Clinical pharmacology practice using MIDD/MIDP.
3. Optimization of initial doses using MIDD/MIDP.
4. Remedial dosing recommendations for delayed or missed doses using MIDD/MIDP.
5. MIDD/MIPD methodological study.
Please Note: Original research based solely on in silico techniques will not be considered for review.
Model-informed drug development and precision dosing (MIDD/MIPD) is achieved through quantitative pharmacology techniques, including population pharmacokinetic (PPK) modeling, population pharmacodynamics (PPD) modeling, pharmacokinetics/pharmacodynamics (PK/PD) modeling, physiologically based pharmacokinetics (PBPK) modeling, and model-based meta-analysis (MBMA). These models are used to improve the efficiency and reduce the cost and risk in drug development, and to provide the basis for precise drug use for patients in clinical practice. The core of MIDD/MIPD is modeling and simulation through artificial intelligence. The goal of this Research Topic is to promote drug development and individualized drug delivery.
For MIDD, based on different application scenarios, the PPK, PPD, PK/PD, PBPK, and MBMA models are used to assess and describe the fate of a drug in the body. Furthermore, the simulation method can be used in addition to virtually predict drug candidates for drug development to obtain an understanding of the therapeutic effects of uninitiated dosing regimens. This can be beneficial to reduce costs and increase efficiency.
For MIPD, based on clinical diagnosis and treatment process-related drugs data or drug trial data, the PPK, PPD, PK/PD, PBPK, and MBMA models can be built up to provide the basis for precise drug use for patients through modeling and simulation technology. MIPD can quantify the effects of different factors on drug absorption, distribution, metabolism, and excretion in specific disease states. Through the analysis of potential covariance, machine learning can be further used to recommend personalized doses for patients in clinical practice. This modeling would include optimizing the initial dose and making remedial dosing recommendations for delayed or missed doses.
The Research Topic welcomes the submission of original research and review articles focusing on MIDD/MIPD to improve the efficiency of drug research and development and to achieve personalized dose recommendations. Potential topics include, but are not limited to, the following:
1. Modeling and simulation for model-informed drug development and precision dosing (MIDD/MIPD) based on: a) population pharmacokinetic (PPK); b) population pharmacodynamics (PPD); c) pharmacokinetics/pharmacodynamics (PK/PD); d) physiologically based pharmacokinetics (PBPK); or e) model-based meta-analysis (MBMA).
2. Clinical pharmacology practice using MIDD/MIDP.
3. Optimization of initial doses using MIDD/MIDP.
4. Remedial dosing recommendations for delayed or missed doses using MIDD/MIDP.
5. MIDD/MIPD methodological study.
Please Note: Original research based solely on in silico techniques will not be considered for review.
