By combining disparate data into coherent mechanistic models, quantitative systems pharmacology is becoming a key tool for picking the right dose for first-in-human trials and other early make-or-break decisions.
Orphan drugs affect 350,000 people worldwide, including 10% of the US population and 1 in 25 Europeans. Model-informed drug development (MIDD) approaches, such as PBPK and PopPK have been embraced by sponsors and regulators, and play a key role in modernizing and accelerating orphan drug development.
Traditional toxicology methods, using in vivo animal testing, is an unrealistic approach to predict chemical risk assessment. Mechanistic modeling and simulation tools such as PBPK and QST can expedite toxicological screening, support the prioritization for testing compounds that merit greater study, and reduce unnecessary animal testing.
Precision dosing is a crucial cornerstone of precision medicine that will provide patients the most efficacious medications with minimum probability of adverse events. Model-informed precision dosing, using quantitative modeling and simulation approaches, such as PBPK and NLME, can improve precision dosing in clinical care.
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Modeling and simulation can help guide critical decisions around dosing and toxicity, efficacy and mechanism of action, clinical trial design and cohort selection, and commercial probability of success as compared with existing therapies or others in development.
QSP models are inherently complex and difficult to use in a clinical setting. Rigorous model reduction methods alleviate the complexity, bolster the use of QSP models for valuable gains, resulting in the extraction of a practical useable model from biological understandings.
Mounting healthcare and R&D costs, high drug attrition rates leading to decreased numbers of new molecular entity approvals, and growing demands from regulators and payers indicate that a paradigm shift is needed to improve efficiency and productivity across the drug development continuum.