Integration of Clinical Pharmacology Knowledge

The typical drug development strategies include dose ranging and bridging studies. The dose ranging studies can be employed to model the concentration (or dose)-effect (desired/undesired) relationships. The clinical pharmacology characterization of a new drug involves a variety of bridging studies to understand the influence of prognostic factors, such as age, gender, smoking habit, food, hepatic/renal impairment, etc. Effectiveness and safety data may not be collected in these types of studies, but could be simulated from the previously developed model. A recent example from a new drug application review is noteworthy. The dose-pain relief (desired effect) and the concentration-heart rate (undesired effect) relationship of a new drug, were both developed by meta-analysis of various clinical studies.

In other studies, patients with severe renal impairment demonstrated a 60% decrease in the systemic clearance compared to that in normal subjects. The influence of a 60% change in the drug exposure on effectiveness and safety was simulated. Dosing without any adjustments in renal-impaired patients causes negligible increase in the probability of pain relief and heart rate. There is 100% probability that the increase in heart rate is within three beats per minute. Whether a particular probability of occurrence of a given magnitude of change, in the effectiveness and safety of drugs, due to prognostic factors, is clinically relevant or not has to be mutually discussed with the clinicians (domain-experts). The M&S offer a powerful method to integrate knowledge across a submitted application. Simulating the probability distributions of effectiveness and safety for the bridging studies would enable a more informed and scientifically sound decision-making regarding the necessity for a regulatory concern. Preserving and accessing the knowledge when necessary at a later point of time will be much easier and efficient. Further, such simulations can be instrumental in the determination of exposure-equivalence intervals for the approval of changes in the future formulations.

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