Model-based meta-analysis (MBMA) helps sponsors to make the wisest, most informed decisions about the next steps in their drug’s development and market positioning.
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.
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.
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.
Clinical pharmacology accounts for about 50% of a drug label. Its scope ranges from facilitating the discovery of new target molecules to determining the effects of drugs in different populations. From both industry-wide and regulatory perspectives, the levers of clinical pharmacology can address the huge challenges of late-stage attrition and increase the efficiency of drug development in the quest to bring the “ball” into the end zone.
The identification of different responsibilities, under the clear leadership of the medical writer, is necessary to improve the quality of clinical study protocols – to prevent problems and mistakes that can result later, during conduct of the clinical trial, or afterwards, when reporting on trial results.