OPTIMISING DRUG DEVELOPMENT- A DYNAMIC APPROACH WITH MODEL AND SIMULATION STRATEGIES

Dr. Yuvraj Kaushal* and Dr. Pranav Goyal

In 2021, the Food and Drug Administration recognized the potential of modeling and simulation (M&S) tools in enhancing drug policy development, postmarket product evaluation, and premarket analysis. While mathematical modeling isn't new to drug research, pharmacokinetic/pharmacodynamic (PK/PD) modeling uniquely examines the interactions between drug kinetics and dynamics in the body. PK modeling quantifies drug absorption and distribution, whereas PD modeling assesses the biological response over time. M&S techniques support various FDA centers, such as CDER, CDRH, and NCTR, in product evaluation and safety assessments, particularly through physiologically based pharmacokinetic (PBPK) modeling. These models help predict drug bioequivalence, optimize dosing, and assess risks associated with new substances, as seen in the FDA's PHASE initiative for synthetic opioids. Recent collaborations have further advanced the use of mechanistic-based PBPK modeling for toxicology testing and impurity evaluation, reducing the need for extensive experimental studies. Despite the benefits, limitations exist, such as the simplification of complex biological systems and the challenge of modeling drug-drug interactions. Nevertheless, continuous advancements in computational techniques and clinical validations are essential to refine these models for better predictive accuracy and regulatory decision-making. The use of M&S in drug development and regulatory processes is expanding, with significant implications for improving drug safety, efficacy, and personalized medicine strategies.